A portable europium complex-loaded fluorescent test paper combined with smartphone analysis for the on-site and visual detection of mancozeb in food samples.

The on-site detection of mancozeb in food samples holds immense value for food safety. A red-fluorescent europium complex (Eu-PYDC-Phen) has been prepared and employed as a fluorescence probe for mancozeb detection. The optimized probe suspension exhibits excellent detection performances, including a wide linear range (0-0.24 mM), low detection limit (65 nM), rapid response (2 mins) and high selectivity. Moreover, a portable detection platform was carefully designed, integrating the Eu-PYDC-Phen-based fluorescent test strips with smartphone color recognition software. This innovative platform enables visual and on-site detection of mancozeb in tomato, apple, and lettuce, achieving satisfactory recovery rates (90.34 to 106.50%). Furthermore, the integration of machine learning techniques based on hierarchical clustering algorithm has the potential to further improve the prediction and decision-making efficiency in mancozeb detection. This work provides an economical, convenient, and reliable strategy for on-site detection of pesticide in agricultural products, thereby making a meaningful contribution to food safety.

Self-assembly of cascade nanoenzyme glucose oxidase encapsulated in copper benzenedicarboxylate for wearable sweat-glucose colorimetric sensors with smartphone readout.

BACKGROUND: With the advent of personalized medical approaches, precise and tailored treatments are expected to become widely accepted for the prevention and treatment of diabetes. Paper-based colorimetric sensors that function in combination with smartphones have been rapidly developed in recent years because it does not require additional equipment and is inexpensive and easy to perform. In this study, we developed a portable, low-cost, and wearable sweat-glucose detection device for in situ detection. RESULTS: The sensor adopted an integrated biomimetic nanoenzyme of glucose oxidase (GOx) encapsulated in copper 1, 4-benzenedicarboxylate (CuBDC) (GOx@CuBDC) through a biomimetic mineralization process. CuBDC exhibited a peroxide-like effect, cascade catalytic effect with the encapsulated GOx, and increased the enzyme stability. GOx@CuBDC and 3,3,5,5-tetramethylbenzidine were combined to form a hybrid membrane that achieved single-step paper-based glucose detection. SIGNIFICANCE AND NOVELTY: This GOx@CuBDC-based colorimetric glucose sensor was used to quantitatively analyze the sweat-glucose concentration with smartphone readings. The sensor exhibited a good linear relationship over the concentration range of 40-900 µM and a limit of detection of 20.7 µM (S/N = 3). Moreover, the sensor performed well in situ monitoring and in evaluating variations based on the consumption of foods with different glycemic indices. Therefore, the fabricated wearable sweat-glucose sensors exhibited optimal practical application performance.

Effect of a Smartphone App (S-Check) on Actual and Intended Help-Seeking and Motivation to Change Methamphetamine Use Among Adult Consumers of Methamphetamine in Australia: Randomized Waitlist-Controlled Trial.

BACKGROUND: Interventions are required that address delays in treatment-seeking and low treatment coverage among people consuming methamphetamine. OBJECTIVE: We aim to determine whether a self-administered smartphone-based intervention, the "S-Check app" can increase help-seeking and motivation to change methamphetamine use, and determine factors associated with app engagement. METHODS: This study is a randomized, 28-day waitlist-controlled trial. Consenting adults residing in Australia who reported using methamphetamine at least once in the last month were eligible to download the app for free from Android or iOS app stores. Those randomized to the intervention group had immediate access to the S-Check app, the control group was wait-listed for 28 days before gaining access, and then all had access until day 56. Actual help-seeking and intention to seek help were assessed by the modified Actual Help Seeking Questionnaire (mAHSQ), modified General Help Seeking Questionnaire, and motivation to change methamphetamine use by the modified readiness ruler. χ2 comparisons of the proportion of positive responses to the mAHSQ, modified General Help Seeking Questionnaire, and modified readiness ruler were conducted between the 2 groups. Logistic regression models compared the odds of actual help-seeking, intention to seek help, and motivation to change at day 28 between the 2 groups. Secondary outcomes were the most commonly accessed features of the app, methamphetamine use, feasibility and acceptability of the app, and associations between S-Check app engagement and participant demographic and methamphetamine use characteristics. RESULTS: In total, 560 participants downloaded the app; 259 (46.3%) completed eConsent and baseline; and 84 (32.4%) provided data on day 28. Participants in the immediate access group were more likely to seek professional help (mAHSQ) at day 28 than those in the control group (n=15, 45.5% vs n=12, 23.5%; χ21=4.42, P=.04). There was no significant difference in the odds of actual help-seeking, intention to seek help, or motivation to change methamphetamine use between the 2 groups on the primary logistic regression analyses, while in the ancillary analyses, the imputed data set showed a significant difference in the odds of seeking professional help between participants in the immediate access group compared to the waitlist control group (adjusted odds ratio 2.64, 95% CI 1.19-5.83, P=.02). For participants not seeking help at baseline, each minute in the app increased the likelihood of seeking professional help by day 28 by 8% (ratio 1.08, 95% CI 1.02-1.22, P=.04). Among the intervention group, a 10-minute increase in app engagement time was associated with a decrease in days of methamphetamine use by 0.4 days (regression coefficient [ß] -0.04, P=.02). CONCLUSIONS: The S-Check app is a feasible low-resource self-administered intervention for adults in Australia who consume methamphetamine. Study attrition was high and, while common in mobile health interventions, warrants larger studies of the S-Check app. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12619000534189; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377288&isReview=true.

A Deep Learning-Based Rotten Food Recognition App for Older Adults: Development and Usability Study.

BACKGROUND: Older adults are at greater risk of eating rotten fruits and of getting food poisoning because cognitive function declines as they age, making it difficult to distinguish rotten fruits. To address this problem, researchers have developed and evaluated various tools to detect rotten food items in various ways. Nevertheless, little is known about how to create an app to detect rotten food items to support older adults at a risk of health problems from eating rotten food items. OBJECTIVE: This study aimed to (1) create a smartphone app that enables older adults to take a picture of food items with a camera and classifies the fruit as rotten or not rotten for older adults and (2) evaluate the usability of the app and the perceptions of older adults about the app. METHODS: We developed a smartphone app that supports older adults in determining whether the 3 fruits selected for this study (apple, banana, and orange) were fresh enough to eat. We used several residual deep networks to check whether the fruit photos collected were of fresh fruit. We recruited healthy older adults aged over 65 years (n=15, 57.7%, males and n=11, 42.3%, females) as participants. We evaluated the usability of the app and the participants' perceptions about the app through surveys and interviews. We analyzed the survey responses, including an after-scenario questionnaire, as evaluation indicators of the usability of the app and collected qualitative data from the interviewees for in-depth analysis of the survey responses. RESULTS: The participants were satisfied with using an app to determine whether a fruit is fresh by taking a picture of the fruit but are reluctant to use the paid version of the app. The survey results revealed that the participants tended to use the app efficiently to take pictures of fruits and determine their freshness. The qualitative data analysis on app usability and participants' perceptions about the app revealed that they found the app simple and easy to use, they had no difficulty taking pictures, and they found the app interface visually satisfactory. CONCLUSIONS: This study suggests the possibility of developing an app that supports older adults in identifying rotten food items effectively and efficiently. Future work to make the app distinguish the freshness of various food items other than the 3 fruits selected still remains.

Phubbing and its impact on the individual's psychological well-being.

Increasingly, smartphones have become a part of people's everyday lives, and are now considered by many to be an indispensable social accessory. Since attachment to a smartphone could have negative psychological consequences, a burgeoning new area of research has emerged which examines the effects of smartphones on individuals' well-being. Hence, this study focuses on phubbing - one's engagement with the smartphone during a face-to-face conversation with another person or group of people - and its association with psychological well-being. For this investigation, a quantitative descriptive approach has been adopted involving a sample of 370 women and men from Spain between 25 and 60 years old. The survey was distributed during late 2019 and the first quarter of 2020. The Phubbing Behaviors Survey was conducted, comprising five dimensions (cultural, technological, social, communicational, and psychological), and a total of 33 items requiring responses on a 5-point Likert scale. This survey was used in conjunction with the General Health Questionnaire (GHQ-28), consisting of four categories (somatic symptoms, social dysfunction, anxiety and insomnia, and severe depression), and 7 items per category. The findings reveal a positive correlation between phubbing and severe depression and, young women under 25 years old show higher levels of somatic symptoms than men in the same age group. This study demonstrates the need to raise awareness via health education and to promote healthy use of the Internet to prevent psychological distress resulting from phubbing.

Wearable, Biocompatible, and Dual-Emission Ocular Multisensor Patch for Continuous Profiling of Fluoroquinolone Antibiotics in Tears.

The abuse or misuse of antibiotics in clinical and agricultural settings severely endangers human health and ecosystems, which has raised profound concerns for public health worldwide. Trace detection and reliable discrimination of commonly used fluoroquinolone (FQ) antibiotics and their analogues have consequently become urgent to guide the rational use of antibiotic medicines and deliver efficient treatments for associated diseases. Herein, we report a wearable eye patch integrated with a quadruplex nanosensor chip for noninvasive detection and discrimination of primary FQ antibiotics in tears during routine eyedrop treatment. A set of dual-mode fluorescent nanoprobes of red- or green-emitting CdTe quantum dots integrated with lanthanide ions and a sensitizer, adenosine monophosphate, were constructed to provide an enhanced fluorescence up to 45-fold and nanomolar sensitivity toward major FQs owing to the aggregation-regulated antenna effect. The aggregation-driven, CdTe-Ln(III)-based microfluidic sensor chip is highly specific to FQ antibiotics against other non-FQ counterparts or biomolecular interfering species and is able to accurately discriminate nine types of FQ or non-FQ eyedrop suspensions using linear discriminant analysis. The prototyped wearable sensing detector has proven to be biocompatible and nontoxic to human tissues, which integrates the entire optical imaging modules into a miniaturized, smartphone-based platform for field use and reduces the overall assay time to ∼5 min. The practicability of the wearable eye patch was demonstrated through accurate quantification of antibiotics in a bactericidal event and the continuous profiling of FQ residues in tears after using a typical prescription antibiotic eyedrop. This technology provides a useful supplement to the toolbox for on-site and real-time examination and regulation of inappropriate daily drug use that might potentially lead to long-term antibiotic abuse and has great implications in advancing personal healthcare techniques for the regulation of daily medication therapy.

Ultrasound-electrochemistry assisted liquid-phase co-exfoliation of phosphorene decorated by Au-Ag bimetallic nanoparticles as nanozyme for smartphone-based portable sensing of 4-nitrophenol.

The stability of black phosphorene (BP) and its preparation and modification for developing and applying devices have become a hot topic in the interdisciplinary field. We propose ultrasound-electrochemistry co-assisted liquid-phase exfoliation as an eco-friendly one-step method to prepare gold-silver bimetallic nanoparticles (Au-AgNPs)-decorated BP nanozyme for smartphone-based portable sensing of 4-nitrophenol (4-NP) in different water sources. The structure, morphology, composition, and properties of Au-AgNPs-BP nanozyme are characterized by multiple instrumental analyses. Bimetallic salts are induced to efficiently occupy oxidative sites of BP to form highly stable Au-AgNPs-BP nanozyme and guarantee the integrity of the lamellar BP. The electrochemistry shortens the exfoliation time of the BP nanosheet and contributes to the loading efficiency of bimetallic nanoparticles on the BP nanosheet. Au-AgNPs-BP-modified screen-printed carbon electrode coupled with palm-sized smartphone-controlled wireless electrochemical analyzer as a portable wireless intelligent sensing platform was applied to the determination of 4-NP in a linear range of 0.6-10 µM with a limit of detection of 63 nM. It enables on-site determination of 4-NP content in lake water, river water, and irrigation ditch water. This work will provide a reference for an eco-friendly one-step preparation of bimetallic nanoparticle-decorated graphene-like materials as nanozymes and their smartphone-based portable sensing application outdoors.

Relationships between experiences of humiliation on social networks, problematic phone use, and aggressive and altruistic behaviors in young adults.

The purpose of this study was to analyze the relationships between cybervictimization in social networks, problematic smartphone use, aggressive behaviors, and prosocial altruistic tendencies in young adults. The sample consisted of 601 young adults (mean age = 19.96 years; SD = 2.27; 69.1% female) who were administered online assessments of experiences of humiliation on networks, problematic smartphone use, prosocial altruistic tendencies, and aggressiveness. Results indicated significant indirect effects of cyber victimization on aggressiveness and prosocial altruistic tendencies through problematic smartphone use. Problematic cell phone use explained the relationships between online humiliation and aggressive and prosocial altruistic behaviors. The results confirmed the positive relationship between cybervictimization and problematic cell phone use, consistent with previous research. However, the negative relationship between cybervictimization and altruistic prosocial tendencies was not corroborated. The findings emphasize the need to promote actions that foster social connectedness and interdependence among young individuals to develop their identity within the community.

Mobile Health Assessment of Traumatic Dental Injuries Using Smartphone-Acquired Photographs: A Multicenter Diagnostic Accuracy Study.

Background: Mobile health (mHealth) has an emerging potential for remote assessment of traumatic dental injuries (TDI) and support of emergency care. This study aimed to determine the diagnostic accuracy of TDI detection from smartphone-acquired photographs. Methods: The upper and lower anterior teeth of 153 individuals aged ≥ 6 years were photographed using a smartphone camera app. The photos of 148 eligible participants were reviewed independently by a dental specialist, two general dentists, and two dental therapists, using predetermined TDI classification and criteria. The sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and inter-rater reliability were estimated to evaluate the diagnostic performance of the photographic method relative to the reference standard established by the dental specialist. Results: Of the 1,870 teeth screened, one-third showed TDI; and one-seventh of the participants had primary or mixed dentitions. Compared between the specialist's reference standard and four dental professionals' reviews, the diagnostic sensitivity and specificity for TDI versus non-TDI were 59-95% and 47-93%, respectively, with better performance for urgent types of TDI (78-89% and 99-100%, separately). The diagnostic consistency was also better for the primary/mixed dentitions than the permanent dentition. Conclusion: This study suggested a valid mHealth practice for remote assessment of TDI. A better diagnostic performance in the detection of urgent types of TDI and examination of the primary/mixed dentition was also reported. Future directions include professional development activities involving dental photography and photographic assessment, incorporation of a machine learning technology to aid photographic reviews, and randomized controlled trials in multiple clinical settings.

An integrated magnetic separation enzyme-linked colorimetric sensing platform for field detection of Escherichia coli O157: H7 in food.

An intelligent colorimetric sensing platform integrated with in situ immunomagnetic separation function was developed for ultrasensitive detection of Escherichia coli O157: H7 (E. coli O157: H7) in food. Captured antibody modified magnetic nanoparticles (cMNPs) and detection antibody/horseradish peroxidase (HRP) co-functionalized AuNPs (dHAuNPs) were firstly synthesized for targeted enrichment and colorimetric assay of E. coli O157: H7, in which remarkable signal amplification was realized by loading large amounts of HRP on the surface of AuNPs. Coupling with the optical collimation attachments and embedded magnetic separation module, a highly integrated optical device was constructed, by which in situ magnetic separation and high-quality imaging of 96-well microplates containing E. coli O157: H7 was achieved with a smartphone. The concentration of E. coli O157: H7 could be achieved in one-step by performing digital image colorimetric analysis of the obtained image with a custom-designed app. This biosensor possesses high sensitivity (1.63 CFU/mL), short detecting time (3 h), and good anti-interference performance even in real-sample testing. Overall, the developed method is expected to be a novel field detection platform for foodborne pathogens in water and food as well as for the diagnosis of infections due to its portability, ease of operation, and high feasibility.

Trends and Influencing Factors in Problematic Smartphone Use Prevalence (2012-2022): A Systematic Review and Meta-Analysis.

Given that problematic smartphone use (PSU) has been researched for a long time, it becomes necessary to assess how the trends of PSU prevalence have evolved over time. In total, 106 articles from 2012 to 2022 with 109 studies covering 97,748 individuals were included in this systematic review and meta-analysis. The estimation of the global pooled PSU prevalence was 37.1% (95% confidence interval, 33.5 - 40.8%) and the PSU prevalence is growing over time in total. Although the PSU prevalence exhibited wide variation between regions and measurement scales, the increasing trend remained. In addition, the regression slope of the PSU prevalence trend in males was higher than that in females. Males initially had a lower prevalence of PSU than females, but this steadily changed over time until it was greater in males than in females. Moreover, the prevalence of PSU showed an increasing trend across all age groups, with a faster growth rate in the older age group. Considering the aforementioned results, it's necessary to implement proper interventions to do with this phenomenon. In addition, considering the differences in prevalence brought by regions, and measurement scales, in practice and research, we should not only take into account the disparities of PSU between countries or cultures, but also to concern about establishing unified standard and measurement tools to confirm it.

Real-time non-invasive hemoglobin prediction using deep learning-enabled smartphone imaging.

BACKGROUND: Accurate measurement of hemoglobin concentration is essential for various medical scenarios, including preoperative evaluations and determining blood loss. Traditional invasive methods are inconvenient and not suitable for rapid, point-of-care testing. Moreover, current models, due to their complex parameters, are not well-suited for mobile medical settings, which limits the ability to conduct frequent and rapid testing. This study aims to introduce a novel, compact, and efficient system that leverages deep learning and smartphone technology to accurately estimate hemoglobin levels, thereby facilitating rapid and accessible medical assessments. METHODS: The study employed a smartphone application to capture images of the eye, which were subsequently analyzed by a deep neural network trained on data from invasive blood test data. Specifically, the EGE-Unet model was utilized for eyelid segmentation, while the DHA(C3AE) model was employed for hemoglobin level prediction. The performance of the EGE-Unet was evaluated using statistical metrics including mean intersection over union (MIOU), F1 Score, accuracy, specificity, and sensitivity. The DHA(C3AE) model's performance was assessed using mean absolute error (MAE), mean-square error (MSE), root mean square error (RMSE), and R^2. RESULTS: The EGE-Unet model demonstrated robust performance in eyelid segmentation, achieving an MIOU of 0.78, an F1 Score of 0.87, an accuracy of 0.97, a specificity of 0.98, and a sensitivity of 0.86. The DHA(C3AE) model for hemoglobin level prediction yielded promising outcomes with an MAE of 1.34, an MSE of 2.85, an RMSE of 1.69, and an R^2 of 0.34. The overall size of the model is modest at 1.08 M, with a computational complexity of 0.12 FLOPs (G). CONCLUSIONS: This system presents a groundbreaking approach that eliminates the need for supplementary devices, providing a cost-effective, swift, and accurate method for healthcare professionals to enhance treatment planning and improve patient care in perioperative environments. The proposed system has the potential to enable frequent and rapid testing of hemoglobin levels, which can be particularly beneficial in mobile medical settings. TRIAL REGISTRATION: The clinical trial was registered on the Chinese Clinical Trial Registry (No. ChiCTR2100044138) on 20/02/2021.

Alleviating premenstrual symptoms with smartphone-based heart rate variability biofeedback training: a pilot study.

Introduction: Heart rate variability biofeedback (HRVB) is a well-studied intervention known for its positive effects on emotional, cognitive, and physiological well-being, including relief from depressive symptoms. However, its practical use is hampered by high costs and a lack of trained professionals. Smartphone-based HRVB, which eliminates the need for external devices, offers a promising alternative, albeit with limited research. Additionally, premenstrual symptoms are highly prevalent among menstruating individuals, and there is a need for low-cost, accessible interventions with minimal side effects. With this pilot study, we aim to test, for the first time, the influence of smartphone-based HRVB on depressive and premenstrual symptoms, as well as anxiety/stress symptoms and attentional control. Methods: Twenty-seven participants with above-average premenstrual or depressive symptoms underwent a 4-week photoplethysmography smartphone-based HRVB intervention using a waitlist-control design. Laboratory sessions were conducted before and after the intervention, spaced exactly 4 weeks apart. Assessments included resting vagally mediated heart rate variability (vmHRV), attentional control via the revised attention network test (ANT-R), depressive symptoms assessed with the BDI-II questionnaire, and stress/anxiety symptoms measured using the DASS questionnaire. Premenstrual symptomatology was recorded through the PAF questionnaire if applicable. Data analysis employed linear mixed models. Results: We observed improvements in premenstrual, depressive, and anxiety/stress symptoms, as well as the Executive Functioning Score of the ANT-R during the intervention period but not during the waitlist phase. However, we did not find significant changes in vmHRV or the Orienting Score of the ANT-R. Discussion: These findings are promising, both in terms of the effectiveness of smartphone-based HRVB and its potential to alleviate premenstrual symptoms. Nevertheless, to provide a solid recommendation regarding the use of HRVB for improving premenstrual symptoms, further research with a larger sample size is needed to replicate these effects.

Effectiveness of a mobile application for independent computerized cognitive training in patients with mild cognitive impairment: study protocol for the NeNaE Study, a randomized controlled trial.

BACKGROUND: Mild cognitive impairment (MCI) involves cognitive decline beyond typical age-related changes, but without significant daily activity disruption. It can encompass various cognitive domains as the causes of MCI are diverse. MCI as well as frequent comorbid neuropsychiatric conditions like depression and anxiety affect individuals' quality of life. Early interventions are essential, and computerized cognitive training (cCT) is an established treatment method. This paper presents the protocol for the NeuroNation MED Effectiveness Study, evaluating the self-administered mobile cCT intervention ("NeuroNation MED") in individuals with MCI to assess training effects on cognitive domains, health competence, neuropsychiatric symptoms, psychological well-being, and the general application usability. METHODS: This study protocol presents a single-blinded multicenter randomized controlled trial that will be carried out in six study centers in Germany and Luxembourg. We included adults with MCI (existing F06.7 ICD-10-GM diagnosis and TICS ≥ 21 and ≤ 32). The intervention group will use a mobile, multi-domain cCT ("NeuroNation MED") for 12 weeks. Meanwhile, the wait list control group will receive standard medical care or no care. The eligibility of volunteers will be determined through a telephone screening. After completion of the baseline examination, patients will be randomly assigned to one of the experimental conditions in a 2:1 ratio. In total, 286 participants will be included in this study. The primary outcome is the change of cognitive performance measured by the index score of the screening module of the Neuropsychological Assessment Battery. Secondary outcomes are changes in the Cognitive Failures Questionnaire, Hospital Anxiety and Depression Scale, Health-49, Health Literacy Questionnaire, among others. All of the primary and secondary outcomes will be assessed at baseline and after the 12-week post-allocation period. Furthermore, the intervention group will undergo an assessment of the System Usability Scale, and the training data of the NeuroNation MED application will be analyzed. DISCUSSION: This study aims to assess the effectiveness of a mobile self-administered cCT in enhancing cognitive abilities among individuals diagnosed with MCI. Should the findings confirm the effectiveness of the NeuroNation MED app, it may confer possible benefits for the care management of patients with MCI, owing to the accessibility, cost-effectiveness, and home-based setting it provides. Specifically, the cCT program could provide patients with personalized cognitive training, educational resources, and relaxation techniques, enabling participants to independently engage in cognitive training sessions at home without further supervision. TRIAL REGISTRATION: German Clinical Trials Register DRKS00025133. Registered on November 5, 2021.

Analysis of the performance of the CorneAI for iOS in the classification of corneal diseases and cataracts based on journal photographs.

CorneAI for iOS is an artificial intelligence (AI) application to classify the condition of the cornea and cataract into nine categories: normal, infectious keratitis, non-infection keratitis, scar, tumor, deposit, acute primary angle closure, lens opacity, and bullous keratopathy. We evaluated its performance to classify multiple conditions of the cornea and cataract of various races in images published in the Cornea journal. The positive predictive value (PPV) of the top classification with the highest predictive score was 0.75, and the PPV for the top three classifications exceeded 0.80. For individual diseases, the highest PPVs were 0.91, 0.73, 0.42, 0.72, 0.77, and 0.55 for infectious keratitis, normal, non-infection keratitis, scar, tumor, and deposit, respectively. CorneAI for iOS achieved an area under the receiver operating characteristic curve of 0.78 (95% confidence interval [CI] 0.5-1.0) for normal, 0.76 (95% CI 0.67-0.85) for infectious keratitis, 0.81 (95% CI 0.64-0.97) for non-infection keratitis, 0.55 (95% CI 0.41-0.69) for scar, 0.62 (95% CI 0.27-0.97) for tumor, and 0.71 (95% CI 0.53-0.89) for deposit. CorneAI performed well in classifying various conditions of the cornea and cataract when used to diagnose journal images, including those with variable imaging conditions, ethnicities, and rare cases.

Two-dimensional ß-MnOOH nanosheets with high oxidase-mimetic activity for smartphone-based colorimetric sensing.

Manganese (Mn) is a versatile transition element with diverse oxidation states and significant biological importance. Mn-based nanozymes have emerged as promising catalysts in various applications. However, the direct use of manganese oxides as oxidase mimics remains limited and requires further improvement. In this study, we focus on hydroxylated manganese (MnOOH), specifically the layered form ß-MnOOH which exhibits unique electronic and structural characteristics. The two-dimensional ß-MnOOH nanosheets were synthesized through a hydrothermal approach and showed remarkable oxidase-like activity. These nanosheets effectively converted the oxidase substrate, 3,3',5,5'-tetramethylbenzidine (TMB), into its oxidized form by initiating the conversion of dissolved oxygen into ·O2-, 1O2 and ·OH. However, in the presence of L-cysteine (L-Cys), the catalytic activity of ß-MnOOH was significantly inhibited, enabling highly sensitive detection of L-Cys. This sensing strategy was successfully applied for smartphone-based L-Cys assay, offering potential utility in the diagnosis of Cys-related diseases. The exploration of layered ß-MnOOH nanosheets as highly active oxidase mimics opens up new possibilities for catalytic and biomedical applications.

Requirements for the Acceptance of an App for Voice Therapy-A Usability Report Based on the "Oldenburger Logopädie App" (OLA).

OBJECTIVE: The prototype "Oldenburger Logopädie App" (OLA) was designed to support voice therapy for patients with recurrent paresis, such as to accompany homework or as a short-term substitute for regular therapy due to dropouts, such as during the COVID-19 pandemic. The treating speech and language pathologists (SLPs) unlocks videos individually applicable to the respective patients, in which the SLPs instruct the individual exercises. The app can be used without information technology knowledge or detailed instructions. MATERIALS AND METHODS: The prototype's usability was evaluated through a usability test battery (AttrakDiff questionnaire, System Usability Scale, Visual Aesthetics of Websites Inventory questionnaire) and informal interviews from the perspective of patients and SLPs. RESULTS: The acceptance, usability, user experience, self-descriptiveness, and user behavior of OLA were consistently given and mostly rated as positive. Both user groups rated OLA as practical and easy to use (eg, System Usability Scale: "practical" (agree: ∅ 49.5%), "cumbersome to use" (total: strongly disagree: ∅ 60.0%). However, the monotonous layout of the app and the instructional and exercise videos should be modified in the next editing step. An overview of relevant criteria for a voice therapy app, regarding design and functions, was derived from the results. CONCLUSION: This user-oriented feedback on the usability of the voice app provides the proof of concept and the basis for the further development of the Artificial intelligence-based innovative follow-up app LAOLA. In the future, it should be possible to support the treatment of all voice disorders with such an app. For the further development of the voice app, the therapeutic content and the effectiveness of the training should also be investigated.