Preface Mobile Health or mHealth - The application of mobile devices, their components and related technologies to healthcare is improving patients’ access to treatment and advice. Now, in combination with connected diagnostic devices it offers new possibilities to diagnose, track and control infectious diseases and improve health system efficiencies. In this context we look at these technologies and highlight their promise but also the challenges in realising their potential to increase patient access to testing, aid in their treatment and improve the capability of public health authorities to monitor outbreaks, implement responses, and assess the impact of interventions across the world.
Paper-based lateral flow immunoassays (LFIAs) are one of the most widely used point-of-care (PoC) devices; however, their application in early disease diagnostics is often limited due to insufficient sensitivity for the requisite sample sizes and the short time frames of PoC testing. To address this, we developed a serum-stable, nanoparticle catalyst-labeled LFIA with a sensitivity surpassing that of both current commercial and published sensitivities for paper-based detection of p24, one of the earliest and most conserved biomarkers of HIV. We report the synthesis and characterization of porous platinum core–shell nanocatalysts (PtNCs), which show high catalytic activity when exposed to complex human blood serum samples. We explored the application of antibody-functionalized PtNCs with strategically and orthogonally modified nanobodies with high affinity and specificity toward p24 and established the key larger nanoparticle size regimes needed for efficient amplification and performance in LFIA. Harnessing the catalytic amplification of PtNCs enabled naked-eye detection of p24 spiked into sera in the low femtomolar range (ca. 0.8 pg·mL–1) and the detection of acute-phase HIV in clinical human plasma samples in under 20 min. This provides a versatile absorbance-based and rapid LFIA with sensitivity capable of significantly reducing the HIV acute phase detection window. This diagnostic may be readily adapted for detection of other biomolecules as an ultrasensitive screening tool for infectious and noncommunicable diseases and can be capitalized upon in PoC settings for early disease detection.
We report the thermodynamically controlled growth of solution-processable and free-standing nanosheets via peptide assembly in two dimensions. By taking advantage of self-sorting between peptide β-strands and hydrocarbon chains, we have demonstrated the formation of Janus 2D structures with single-layer thickness, which enable a predetermined surface heterofunctionalization. A controlled 2D-to-1D morphological transition was achieved by subtly adjusting the intermolecular forces. These nanosheets provide an ideal substrate for the engineering of guest components (e.g., proteins and nanoparticles), where enhanced enzyme activity was observed. We anticipate that sequence-specific programmed peptides will offer promise as design elements for 2D assemblies with face-selective functionalization.
Label-free surface-enhanced Raman spectroscopy (SERS) can interrogate systems by directly fingerprinting their components' unique physicochemical properties. In complex biological systems however, this can yield highly overlapping spectra that hinder sample identification. Here, we present an artificial-nose inspired SERS fingerprinting approach where spectral data is obtained as a function of sensor surface chemical functionality. Supported by molecular dynamics modeling, we show that mildly selective self-assembled monolayers can influence the strength and configuration in which analytes interact with plasmonic surfaces, diversifying the resulting SERS fingerprints. Since each sensor generates a modulated signature, the implicit value of increasing the dimensionality of datasets is shown using cell lysates for all possible combinations of up to 9 fingerprints. Reliable improvements in mean discriminatory accuracy towards 100% are achieved with each additional surface functionality. This arrayed label-free platform illustrates the wide-ranging potential of high-dimensionality artificial-nose based sensing systems for more reliable assessment of complex biological matrices.
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