Automatic offline-capable smartphone paper-based microfluidic device for efficient biomarker detection of Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a prevalent neurodegenerative disease with no effective treatment. Efficient and rapid detection plays a crucial role in mitigating and managing AD progression. Deep learning-assisted smartphone-based microfluidic paper analysis devices (μPADs) offer the advantages of low cost, good sensitivity, and rapid detection, providing a strategic pathway to address large-scale disease screening in resource-limited areas. However, existing smartphone-based detection platforms usually rely on large devices or cloud servers for data transfer and processing. Additionally, the implementation of automated colorimetric enzyme-linked immunoassay (c-ELISA) on μPADs can further facilitate the realization of smartphone μPADs platforms for efficient disease detection.

RESULTS

This paper introduces a new deep learning-assisted offline smartphone platform for early AD screening, offering rapid disease detection in low-resource areas. The proposed platform features a simple mechanical rotating structure controlled by a smartphone, enabling fully automated c-ELISA on μPADs. Our platform successfully applied sandwich c-ELISA for detecting the β-amyloid peptide 1-42 (Aβ 1-42, a crucial AD biomarker) and demonstrated its efficacy in 38 artificial plasma samples (healthy: 19, unhealthy: 19, N = 6). Moreover, we employed the YOLOv5 deep learning model and achieved an impressive 97 % accuracy on a dataset of 1824 images, which is 10.16 % higher than the traditional method of curve-fitting results. The trained YOLOv5 model was seamlessly integrated into the smartphone using the NCNN (Tencent's Neural Network Inference Framework), enabling deep learning-assisted offline detection. A user-friendly smartphone application was developed to control the entire process, realizing a streamlined "samples in, answers out" approach.

SIGNIFICANCE

This deep learning-assisted, low-cost, user-friendly, highly stable, and rapid-response automated offline smartphone-based detection platform represents a good advancement in point-of-care testing (POCT). Moreover, our platform provides a feasible approach for efficient AD detection by examining the level of Aβ 1-42, particularly in areas with low resources and limited communication infrastructure.

A fast gradient convolution kernel compensation method for surface electromyogram decomposition

Decomposition of EMG signals provides the decoding of motor unit (MU) discharge timings. In this study, we propose a fast gradient convolution kernel compensation (fgCKC) decomposition algorithm for high-density surface EMG decomposition and apply it to an offline and real-time estimation of MU spike trains. We modified the calculation of the cross-correlation vectors to improve the calculation efficiency of the gradient convolution kernel compensation (gCKC) algorithm. Specifically, the new fgCKC algorithm considers the past gradient in addition to the current gradient. Furthermore, the EMG signals are divided by sliding windows to simulate real-time decomposition, and the proposed algorithm was validated on simulated and experimental signals. In the offline decomposition, fgCKC has the same robustness as gCKC, with sensitivity differences of 2.6 ± 1.3 % averaged across all trials and subjects. Nevertheless, depending on the number of MUs and the signal-to-noise ratio of signals, fgCKC is approximately 3 times faster than gCKC. In the real-time part, the processing only needed 240 ms average per window of EMG signals on a regular personal computer (IIntel(R) Core(TM) i5-12490F 3 GHz, 16 GB memory). These results indicate that fgCKC achieves real-time decomposition by significantly reducing processing time, providing more possibilities for non-invasive neuronal behavior research.

Online and offline dating violence: same same, but different?

BACKGROUND

Violent behaviors in romantic relationships among adolescents and young people are pressing social matter as they have an effect on both victims and aggressors. Moreover, in the last decades, new forms of harassment, control, and abuse through social networks and mobile phones have arisen. Therefore, now forms of online and offline dating violence coexist.

OBJECTIVES

The aim was to analyze the prevalence rates by sex and age and the co-occurrence of online and offline dating violence. Moreover, the roles of online and offline dating violence aggressors and victims for their self-esteem, hostility, general psychological state, and emotional intelligence were investigated.

METHOD

Three hundred forty-one university students from the Basque Country, Spain, participated in the study. They completed six validated instruments related to the mentioned variables.

RESULTS

Results highlight the high prevalence of online and offline dating violence in the sample and the co-occurrence of both types. No gender nor sex differences were found for online and offline dating violence perpetration and victimization. The correlation between online and offline dating violence was confirmed, and the reciprocity of violence is greater for offline violence. In relation to the role, both types of victims (online and offline) showed higher levels of hostility and psychological symptomatology than non-victims, but differences in self-esteem and emotional regulation were found in these modalities. Online and offline perpetrators shared hostility and some psychological symptoms as characteristics compared to non-victims, but differed in other symptoms and emotional intelligence.

CONCLUSION

There is a continuum between offline and online victimization perpetration albeit differences in the characteristics such as self-esteem, emotional intelligence, and general functioning exist.

Effect of nasal high-flow oxygen humidification on patients after cardiac surgery

Background

Although high-flow humidified oxygen therapy (HFNC) has emerged as an important treatment for respiratory failure, few studies have reported on whether HFNC is appropriate for patients with hypoxemia after cardiac surgery, and the clinical efficacy of HFNC in patients undergoing cardiac surgery is unclear.

Objective

To investigate the clinical effect of HFNC after cardiac surgery.

Methods

Convenience sampling was used to select 76 patients who underwent invasive mechanical ventilation and oxygen therapy after valve replacement or coronary artery bypass grafting from July 2019 to June 2021. The patients were divided into the routine group and the HFNC group according to the oxygen therapy provided after the operation. The patients in the routine group (N = 38) were treated with oxygen inhalation by face mask after the operation, while those in the HFNC group (N = 38) were treated with HFNC via nasal cavity. The arterial partial pressure of oxygen (PaO2), the arterial partial pressure of carbon dioxide (PaCO2) and the oxygenation index (OI) were observed and compared between the two groups at 6 h, 12 h and 24 h after treatment. The sputum viscosity, incidence of second intubation and the intensive care unit (ICU) stay time were evaluated.

Results

The difference in PaCO2 between the two groups was statistically significant at 24 h after treatment (p < 0.05). The PaO2 in the HFNC group was significantly higher than in the routine group at 24 h after treatment, and the OI of the routine group was lower than in the HFNC group at 6 h, 12 h and 24 h after treatment (p < 0.05). The sputum viscosity in the HFNC group was better than in the routine group at 12 h and 24 h after treatment. The second intubation rate and ICU stay time in the HFNC group were lower than in the routine group (p < 0.05).

Conclusion

Compared with conventional mask oxygen inhalation, HFNC can effectively reduce sputum viscosity, improve oxygenation, reduce the incidence of repeated intubation and meet patients' comfort needs. It is an advantageous respiratory support strategy for patients after cardiac surgery compared with invasive mechanical ventilation to oxygen therapy and is beneficial to the recovery of cardiopulmonary function.

Carbon tax policy analysis based on distribution channel strategy

This paper establishes a theoretical model to study the carbon tax policy based on a firm's different distribution channel strategy. First, we examine the firm's optimal distribution channel strategies in the absence of government policy intervention. Then, on the assumption that the firm is owned by the society as a whole and taking into account the environmental impact of the firm's decisions, we describe the product distribution strategy that optimizes social welfare. Through the comparison of the above two situations, we find that without the intervention of government policies, the firm's decision may deviate from the decision that optimizes social welfare. Finally, on the basis of the analysis, we propose a carbon tax policy for retailers in distribution channels under different firm distribution strategies. We hope that with the intervention of carbon tax policy, firm decisions can achieve optimal social welfare.

offline form meaningful? Empirical evidence from a large German speaking gamer sample

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Disordered gaming is distinguished by predominantly online, offline, and unspecific gaming.

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Online gamers showed the highest tendencies towards disordered gaming.

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Gaming via desktop computers was linked with the highest disordered gaming levels.

In the eleventh revision of the International Classification of Diseases (ICD-11), Gaming Disorder (GD) is distinguished between disordered gaming occurring predominantly online, offline, and unspecified. Currently, no study has investigated whether such a distinction is meaningful in diagnosing disordered gaming. Therefore, a large group of gamers with varied tendencies towards disordered gaming was recruited to examine this issue. A large sample (N = 2,768) was recruited and data were collected on disordered gaming, along with information on their preferred gaming mode and device used to play. The present study shows that the distinction between online and offline gaming mode proposed by the WHO is meaningful because online gamers presented with the highest disordered gaming scores followed by mixed gamers (those stating to equally prefer online and offline gaming), and offline gamers. Finally, it was also observed that the type of device for gaming used associated with disordered gaming levels. Specifically, those reporting mostly to use their desktop computer for gaming showed the highest disordered gaming scores. The present study lends empirical support for the consideration of both gaming mode and gaming device in the study of disordered gaming.

Design and implementation of a mobile health electronic data capture platform that functions in fully-disconnected settings: a pilot study in rural Liberia

Background

Mobile phones and personal digital assistants have been used for data collection in developing world settings for over three decades, and have become increasingly common. However, the use of electronic data capture (EDC) through mobile phones is limited in many areas by inconsistent network connectivity and poor access to electricity, which thwart data transmission and device usage. This is the case in rural Liberia, where many health workers live and work in areas without any access to cellular connectivity or reliable power. Many existing EDC mobile software tools are built for occasionally-disconnected settings, allowing a user to collect data while out of range of a cell tower and transmit data to a central server when he/she regains a network connection. However, few tools exist that can be used indefinitely in fully-disconnected settings, where a user will never have access to the internet or a cell network. This led us to create and implement an EDC software tool that allows for completely offline data transfer and application updating.

Results

We designed, pilot-tested, and scaled an open-source fork of Open Data Kit Collect (an Android application that can be used to create EDC systems) that allows for offline Bluetooth-based bidirectional data transfer, enabling a system in which permanently-offline users can collect data and receive application updates. We implemented this platform among a cohort of 317 community health workers and 28 supervisors in a remote area of rural Liberia with incomplete cellular connectivity and low access to power sources.

Conclusions

Running a fully-offline EDC program that completely bypasses the cellular network was found to be feasible; the system is still running, over 4 years after the initial pilot program. The users of this program can theoretically collect data offline for months or years, assuming they receive hardware support when needed. Fully-offline EDC has applications in settings where cellular network coverage is poor, as well as in disaster relief settings in which portions of the communications infrastructure may be temporarily nonfunctional.

Impulsivity and cognitive distortions in different clinical phenotypes of gambling disorder: Profiles and longitudinal prediction of treatment outcomes

BACKGROUND

Impulsivity and cognitive distortions are hallmarks of gambling disorder (GD) but it remains unclear how they contribute to clinical phenotypes. This study aimed to (1) compare impulsive traits and gambling-related distortions in strategic versus non-strategic gamblers and online versus offline gamblers; (2) examine the longitudinal association between impulsivity/cognitive distortions and treatment retention and relapse.

METHODS

Participants seeking treatment for GD (n = 245) were assessed for gambling modality (clinical interview), impulsive traits (Urgency, Premeditation, Perseverance and Sensation Seeking [UPPS] scale) and cognitive distortions (Gambling Related Cognitions Scale) at treatment onset, and for retention and relapse (as indicated by the clinical team) at the end of treatment. Treatment consisted of 12-week standardized cognitive behavioral therapy, conducted in a public specialized clinic within a general public hospital.

RESULTS

Strategic gamblers had higher lack of perseverance and gambling-related expectancies and illusion of control than non-strategic gamblers, and online gamblers had generally higher distortions but similar impulsivity to offline gamblers. Lack of perseverance predicted treatment dropout, whereas negative urgency and distortions of inability to stop gambling and interpretative bias predicted number of relapses during treatment.

CONCLUSIONS

Individuals with online and strategic GD phenotypes have heightened gambling related biases associated with premature treatment cessation and relapse. Findings suggest that these GD phenotypes may need tailored treatment approaches to reduce specific distortions and impulsive facets.