Rational design of peptide-based fluorescent probe for sequential recognitions of Cu(II) ions and glyphosate: Smartphone, test strip, real sample and living cells applications

A new peptide-based fluorescent probe named DMDH with easy-to-synthesize, excellent stability, good water solubility and large Stokes shift (225 nm) was synthesized for highly selective sequential detections of copper ions (Cu2+) and glyphosate (Glyp). DMDH demonstrated great detection performance towards Cu2+via strong fluorescence quenching, and forming non-fluorescence DMDH-Cu2+ ensemble. As a new promising cascade probe, the fluorescence of DMDH-Cu2+ ensemble was significantly recovered based on displacement approach after glyphosate was added. Interestingly, the limit of detections (LODs) for Cu2+ and glyphosate were 40.6 nM and 10.6 nM, respectively, which were far lower than those recommended by the WHO guidelines for drinking water. More importantly, DMDH was utilized to evaluate Cu2+ and glyphosate content in three real water samples, demonstrating that its effectiveness in water quality monitoring. Additionally, it is worth noting that DMDH was also applied to analyze Cu2+ and glyphosate in living cells in view of significant cells permeability and low cytotoxicity. Moreover, DMDH soaked in filter paper was used to create qualitative test strips and visually identify Cu2+ and glyphosate through significant color changes. Furthermore, smartphone RGB color recognition provided a new method for semi-quantitative testing of Cu2+ and glyphosate in the absence of expensive instruments.

Recent advancements of smartphone-based sensing technology for diagnosis, food safety analysis, and environmental monitoring

The emergence of computationally powerful smartphones, relatively affordable high-resolution camera, drones, and robotic sensors have ushered in a new age of advanced sensible monitoring tools. The present review article investigates the burgeoning smartphone-based sensing paradigms, including surface plasmon resonance (SPR) biosensors, electrochemical biosensors, colorimetric biosensors, and other innovations for modern healthcare. Despite the significant advancements, there are still scarcity of commercially available smart biosensors and hence need to accelerate the rates of technology transfer, application, and user acceptability. The application/necessity of smartphone-based biosensors for Point of Care (POC) testing, such as prognosis, self-diagnosis, monitoring, and treatment selection, have brought remarkable innovations which eventually eliminate sample transportation, sample processing time, and result in rapid findings. Additionally, it articulates recent advances in various smartphone-based multiplexed bio sensors as affordable and portable sensing platforms for point-of-care devices, together with statistics for point-of-care health monitoring and their prospective commercial viability.

Smartphone-integrated ratiometric fluorescence sensing platform based on bimetallic metal-organic framework nanowires for anthrax biomarker detection

Developing an intelligent, sensitive, and visual strategy for quickly identifying anthrax biomarkers is crucial for ensuring food safety and preventing disease outbreaks. Herein, a smartphone-integrated ratiometric fluorescent sensing platform based on bimetallic metal-organic framework (Eux/Tb1-x-MOF) nanowires was designed for specific recognition of pyridine-2,6-dicarboxylic acid (DPA, anthrax biomarker). The Eux/Tb1-x-MOF was prepared by coordinating Eu3+ and Tb3+ with BBDC ligands, which exhibited a uniform fibrous morphology and dual-emission fluorescence at 543 and 614 nm. After the introduction of DPA, the red emission at 614 nm displayed obvious fluorescence quenching, while the green emission at 543 nm was gradually enhanced. The ratiometric sensing offered a wide linear equation in the range of 0.06-15 µg/mL and a low detection limit (LOD) of 20.69 ng/mL. Furthermore, a portable smartphone installing the color recognition application can achieve sensitive, real-time, and visual detection of DPA. As a simple and effective smartphone-assisted sensing platform, this work holds admirable promise to broaden the applications in biomarker real-time determinations and other fields.

A smartphone-based colorimetric assay using Au@Ag core-shell nanoparticles as the nanoprobes for visual tracing of fluvoxamine in biofluids as a common suicide drug

In the present study, bimetallic nanoparticles (NPs) consisting of gold (AuNPs) as the core and silver (AgNPs) as the shell have been synthesized and applied as the nanoprobe for detection of fluvoxamine (FXM) as the anti-depression drug. The physicochemical properties of the prepared citrate-capped Au@Ag core-shell NPs have been characterized by UV-Vis, Fourier-transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM) and scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) techniques. The design of the smartphone-based colorimetric FXM sensor relies on the fast hydrolysis of FXM under alkaline conditions by producing of 2-(Aminooxy)ethanamine without any significant peak at 400-700 nm. The interaction of the resulted molecule with the nanoprobe induced a red shift in the longitudinal localized surface plasmon resonance (LSPR) peak of the nanoprobe, which was accompanied by sharp and vivid color variations in the solution. A linear relationship between the absorption signal increasing by FXM concentration increasing from 1 µM to 10 µM presented a simple, low cost and minimally instrumented format for FXM quantification with a limit of detection (LOD) of 100 nM. The collected visual data with the elegant colorimetric response of the nanoprobe in the presence of FXM from Indian red to light red violet and bluish-purple color offered simple detection of FXM with the naked eye. The satisfactory results of the proposed cost-effective sensor in the rapid assay of FXM in human serum, urine, saliva and pharmaceutical samples guarantee the potential of the nanoprobe for on-site and visual determination of FXM in actual samples. The proposed sensor as the first non-invasive FXM sensor for saliva sample analysis may hold great promise to provide the technical support for the rapid and valid detection of FXM for forensic medicine and clinical organizations.

A portable smartphone-assisted ratiometric fluorescence sensor for intelligent and visual detection of malachite green

Developing intelligent, sensitive, and visual methods for rapidly detecting veterinary drug residues is essential for ensuring food quality and safety. A portable smartphone-assisted ratiometric fluorescent sensor was successfully designed using fluorescent Al-MOF nanosheet and rhodamine B (RhB) as fluorescent probes to adjust to the requirement of malachite green (MG) detection. The developed ratiometric fluorescent sensor allowed sensitive and selective detection of MG with good linear relationships in a wide range of 0.5-200 μg/mL. The Quantitative linearrange is 5.3 μg/mL to 200 μg/mL. The limit of detection (LOD) and limit of quantification (LOQ) were calculated to be 1.6 μg/mL and 5.3 μg/mL respectively. The practicability of the proposed method was verified using high performance liquid chromatography (HPLC) in spiked fish tissues with satisfying recoveries and RSD. Moreover, portable smartphone-assisted fluorescent test papers were fabricated for the intelligent detection of MG. This integration of smartphones and fluorescent test papers was economical and saved time, providing an alternative strategy for the qualitative discernment and semi-quantitative analysis of MG on-site.

Nitrogen, boron-doped Ti3C2 MXene quantum dot-based ratiometric fluorescence sensing platform for point-of-care testing of tetracycline using an enhanced antenna effect by Eu3

The Ti₃C₂ MXene quantum dots (Ti₃C₂ MQDs) derived from Ti₃C₂ MXene have received much attention because of their remarkable advantages in biosensing. Nevertheless, the functionalization of Ti₃C₂ MQDs to improve their properties is just in its infant stage. Herein, we firstly synthesized nitrogen and boron co-doped Ti₃C₂ MQDs (N, B-Ti₃C₂ MQDs) with good water solubility, strong stability, and high optical characteristics. The N, B-Ti₃C₂ MQDs exhibit excitation wavelength-dependent blue photoluminescence with optimal excitation/emission peaks at 335/439 nm. Nowadays, the development of fast and real-time detection of tetracycline (TC) in animal derived food is very essential. In this work, a novel point-of-care testing (POCT) platform was established based on ratiometric fluorescence method using N, B-Ti₃C₂ MQDs coupled with Eu³⁺. Upon addition of TC in the Eu³⁺/N, B-MQDs system, blue fluorescence emission of N, B-Ti₃C₂ MQDs was quenched and red fluorescence emission of Eu³⁺ was enhanced gradually, which was ascribed to the synergistic inner filter effect and antenna effect. Moreover, we prepared test papers with N, B-Ti₃C₂ MQDs and Eu³⁺ for TC detection based on the change of fluorescence color, which could be recognized by color recognizer app installed in the smartphone. Therefore, great promise for POCT of TC is given with the merits of simplicity and visible detection possibility. The proposed method demonstrated a low detection limit of 20 nM. Application of the platform for TC quantification in milk samples opened a novel means for the potential use of N, B-Ti₃C₂ MQDs in food safety.

ContextLabeler dataset: Physical and virtual sensors data collected from smartphone usage in-the-wild

This paper describes a data collection campaign and the resulting dataset derived from smartphone sensors characterizing the daily life activities of 3 volunteers in a period of two weeks. The dataset is released as a collection of CSV files containing more than 45K data samples, where each sample is composed by 1332 features related to a heterogeneous set of physical and virtual sensors, including motion sensors, running applications, devices in proximity, and weather conditions. Moreover, each data sample is associated with a ground truth label that describes the user activity and the situation in which she was involved during the sensing experiment (e.g., working, at restaurant, and doing sport activity). To avoid introducing any bias during the data collection, we performed the sensing experiment in-the-wild, that is, by using the volunteers' devices, and without defining any constraint related to the user's behavior. For this reason, the collected dataset represents a useful source of real data to both define and evaluate a broad set of novel context-aware solutions (both algorithms and protocols) that aim to adapt their behavior according to the changes in the user's situation in a mobile environment.

Ultrasensitive and visual detection of tetracycline based on dual-recognition units constructed multicolor fluorescent nano-probe

Ultrasensitive and visual detection of tetracycline antibiotic (TC) residues is of great significance to public health and environmental safety. A novel dual-response ratiometric fluorescent nano-probe (SiQDs-Cit-Eu) has been elaborately tailored for the determination and on-site visual assay of tetracycline, by grafting citric acid and europium (Eu³⁺) ions onto the surface of silicon quantum dots (SiQDs). The blue-emissive SiQDs (λ_em = 455 nm) fabricated by a one-step facile method act as both scaffold for coordination with Eu³⁺ ions and recognition unit for TC owing to the inner filter effect (IFE). The coordinate unsaturated red-fluorescent Eu³⁺ ions (λ_em = 617 nm) bond to the surface of SiQDs, serving as the specific recognition element for TC due to the antenna effect. In the presence of TC, the as-synthesized nano-probe exhibits double (λ_em = 455 and 617 nm) and reverse response signals which are accompanied by a marked color change from blue to purple, and then red, thus achieving ultra-high sensitivity with a detection limit of 7.1 nM and instant visual detection of TC in real samples (milk, honey, lake and river water). Furthermore, smartphone-assisted point-of-care testing platform is also constructed based on nano-probe-immobilized test paper by using the color scanning APP.

Best practices for Electronically Activated Recorder (EAR) research: A practical guide to coding and processing EAR data

Since its introduction in 2001, the Electronically Activated Recorder (EAR) method has become an established and broadly used tool for the naturalistic observation of daily social behavior in clinical, health, personality, and social science research. Previous treatments of the method have focused primarily on its measurement approach (relative to other ecological assessment methods), research design considerations (e.g., sampling schemes, privacy considerations), and the properties of its data (i.e., reliability, validity, and added measurement value). However, the evolved procedures and practices related to arguably one of the most critical parts of EAR research-the coding process that converts the sampled raw ambient sounds into quantitative behavioral data for statistical analysis-so far have largely been communicated informally between EAR researchers. This article documents "best practices" for processing EAR data, which have been tested and refined in our research over the years. Our aim is to provide practical information on important topics such as the development of a coding system, the training and supervision of EAR coders, EAR data preparation and database optimization, the troubleshooting of common coding challenges, and coding considerations specific to diverse populations.

Digital phenotyping: towards replicable findings with comprehensive assessments and integrative models in bipolar disorders

Background

Digital phenotyping promises to unobtrusively obtaining a continuous and objective input of symptomatology from patients’ daily lives. The prime example are bipolar disorders, as smartphone parameters directly reflect bipolar symptomatology. Empirical studies, however, have yielded inconsistent findings. We believe that three main shortcomings have to be addressed to fully leverage the potential of digital phenotyping: short assessment periods, rare outcome assessments, and an extreme fragmentation of parameters without an integrative analytical strategy.

Methods

To demonstrate how to overcome these shortcomings, we conducted frequent (biweekly) dimensional and categorical expert ratings and daily self-ratings over an extensive assessment period (12 months) in 29 patients with bipolar disorder. Digital phenotypes were monitored continuously. As an integrative analytical strategy, we used structural equation modelling to build latent psychopathological outcomes (mania, depression) and latent digital phenotype predictors (sleep, activity, communicativeness).

Outcomes

Combining gold-standard categorical expert ratings with dimensional self and expert ratings resulted in two latent outcomes (mania and depression) with statistically meaningful factor loadings that dynamically varied over 299 days. Latent digital phenotypes of sleep and activity were associated with same-day latent manic psychopathology, suggesting that psychopathological alterations in bipolar disorders relate to domains (latent variables of sleep and activity) and not only to specific behaviors (such as the number of declined incoming calls). The identification of latent psychopathological outcomes that dimensionally vary on a daily basis will enable to empirically determine which combination of digital phenotypes at which days prior to an upcoming episode are viable as digital prodromal predictors.