BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets.

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

Approaches to vascularizing human brain organoids.

A major challenge in brain organoid technologies is the lack of vasculature. In recent years, innovative approaches have been taken to meet this challenge. A 2020 paper published in PLOS Biology exemplifies the approaches used in this booming field.

DSCAM gene triplication causes excessive GABAergic synapses in the neocortex in Down syndrome mouse models.

Down syndrome (DS) is caused by the trisomy of human chromosome 21 (HSA21). A major challenge in DS research is to identify the HSA21 genes that cause specific symptoms. Down syndrome cell adhesion molecule (DSCAM) is encoded by a HSA21 gene. Previous studies have shown that the protein level of the Drosophila homolog of DSCAM determines the size of presynaptic terminals. However, whether the triplication of DSCAM contributes to presynaptic development in DS remains unknown. Here, we show that DSCAM levels regulate GABAergic synapses formed on neocortical pyramidal neurons (PyNs). In the Ts65Dn mouse model for DS, where DSCAM is overexpressed due to DSCAM triplication, GABAergic innervation of PyNs by basket and chandelier interneurons is increased. Genetic normalization of DSCAM expression rescues the excessive GABAergic innervations and the increased inhibition of PyNs. Conversely, loss of DSCAM impairs GABAergic synapse development and function. These findings demonstrate excessive GABAergic innervation and synaptic transmission in the neocortex of DS mouse models and identify DSCAM overexpression as the cause. They also implicate dysregulated DSCAM levels as a potential pathogenic driver in related neurological disorders.

Sensitive genetically encoded sensors for population and subcellular imaging of cAMP in vivo.

Cyclic adenosine monophosphate (cAMP) signaling integrates information from diverse G-protein-coupled receptors, such as neuromodulator receptors, to regulate pivotal biological processes in a cellular-specific and subcellular-specific manner. However, in vivo cellular-resolution imaging of cAMP dynamics remains challenging. Here, we screen existing genetically encoded cAMP sensors and further develop the best performer to derive three improved variants, called cAMPFIREs. Compared with their parental sensor, these sensors exhibit up to 10-fold increased sensitivity to cAMP and a cytosolic distribution. cAMPFIREs are compatible with both ratiometric and fluorescence lifetime imaging and can detect cAMP dynamics elicited by norepinephrine at physiologically relevant, nanomolar concentrations. Imaging of cAMPFIREs in awake mice reveals tonic levels of cAMP in cortical neurons that are associated with wakefulness, modulated by opioids, and differentially regulated across subcellular compartments. Furthermore, enforced locomotion elicits neuron-specific, bidirectional cAMP dynamics. cAMPFIREs also function in Drosophila. Overall, cAMPFIREs may have broad applicability for studying intracellular signaling in vivo.

The relationship between innate/adaptive immunity and gastrointestinal cancer : a multi-omics Mendelian randomization study.

BACKGROUND: Innate/adaptive immunity is the key to anti-tumor therapy. However, its causal relationship to Gastrointestinal (GI) cancer remains unclear. METHODS: Immunity genes were extracted from the MSigDB database. The Genome-wide association studies (GWAS) summary data of GI cancer were integrated with expression quantitative trait loci (eQTL) and DNA methylation quantitative trait loci (mQTL) associated with genes. Summary-data-based Mendelian randomization (SMR) and co-localization analysis were used to reveal causal relationships between genes and GI cancer. Two-sample MR analysis was used for sensitivity analysis. Single cell analysis clarified the enrichment of genes. RESULTS: Three-step SMR analysis showed that a putative mechanism, cg17294865 CpG site regulating HLA-DRA expression was negatively associated with gastric cancer risk. HLA-DRA was significantly differentially expressed in monocyte/macrophage and myeloid cells in gastric cancer. CONCLUSION: This study provides evidence that upregulating the expression level of HLA-DRA can reduce the risk of gastric cancer.

Possible pathogenic mechanisms for doxorubicin-induced splenic atrophy in a human breast cancer xenograft mouse model.

Doxorubicin-based chemotherapy is a widely used first-line treatment for breast cancer, yet it is associated with various side effects, including splenic atrophy. However, the pathogenic mechanisms underlying doxorubicin-induced atrophy of the spleen remain unclear. This study investigates that doxorubicin treatment leads to splenic atrophy through several interconnected pathways involving histological changes, an inflammatory response, and apoptosis. Immunohistochemical and western blot analyses revealed reduced size of white and red pulp, decreased cellularity, amyloidosis, and fibrotic remodeling in the spleen following doxorubicin treatment. Additionally, increased secretion of pro-inflammatory cytokines was detected using an antibody array and enzyme-linked immunosorbent assay (ELISA), which triggers inflammation through the regulation of signal transducer and activator of transcription 3 (STAT3) and nuclear factor-kappa B (NF-κB) signaling pathways. Further analysis revealed that the loss of regulators and effectors of the oxidative defense system, including sirtuin (Sirt)3, Sirt5, superoxide dismutase (SOD)1, and SOD2, was implicated in the upstream regulation of caspase-dependent cellular apoptosis. These findings provide insights on the pathogenic mechanisms underlying doxorubicin-induced splenic atrophy and suggest that further investigation may be warranted to explore strategies for managing potential side effects in breast cancer patients treated with doxorubicin.

Smartphone-Based Hand Function Assessment: Systematic Review.

BACKGROUND: Hand function assessment heavily relies on specific task scenarios, making it challenging to ensure validity and reliability. In addition, the wide range of assessment tools, limited and expensive data recording, and analysis systems further aggravate the issue. However, smartphones provide a promising opportunity to address these challenges. Thus, the built-in, high-efficiency sensors in smartphones can be used as effective tools for hand function assessment. OBJECTIVE: This review aims to evaluate existing studies on hand function evaluation using smartphones. METHODS: An information specialist searched 8 databases on June 8, 2023. The search criteria included two major concepts: (1) smartphone or mobile phone or mHealth and (2) hand function or function assessment. Searches were limited to human studies in the English language and excluded conference proceedings and trial register records. Two reviewers independently screened all studies, with a third reviewer involved in resolving discrepancies. The included studies were rated according to the Mixed Methods Appraisal Tool. One reviewer extracted data on publication, demographics, hand function types, sensors used for hand function assessment, and statistical or machine learning (ML) methods. Accuracy was checked by another reviewer. The data were synthesized and tabulated based on each of the research questions. RESULTS: In total, 46 studies were included. Overall, 11 types of hand dysfunction-related problems were identified, such as Parkinson disease, wrist injury, stroke, and hand injury, and 6 types of hand dysfunctions were found, namely an abnormal range of motion, tremors, bradykinesia, the decline of fine motor skills, hypokinesia, and nonspecific dysfunction related to hand arthritis. Among all built-in smartphone sensors, the accelerometer was the most used, followed by the smartphone camera. Most studies used statistical methods for data processing, whereas ML algorithms were applied for disease detection, disease severity evaluation, disease prediction, and feature aggregation. CONCLUSIONS: This systematic review highlights the potential of smartphone-based hand function assessment. The review suggests that a smartphone is a promising tool for hand function evaluation. ML is a conducive method to classify levels of hand dysfunction. Future research could (1) explore a gold standard for smartphone-based hand function assessment and (2) take advantage of smartphones' multiple built-in sensors to assess hand function comprehensively, focus on developing ML methods for processing collected smartphone data, and focus on real-time assessment during rehabilitation training. The limitations of the research are 2-fold. First, the nascent nature of smartphone-based hand function assessment led to limited relevant literature, affecting the evidence's completeness and comprehensiveness. This can hinder supporting viewpoints and drawing conclusions. Second, literature quality varies due to the exploratory nature of the topic, with potential inconsistencies and a lack of high-quality reference studies and meta-analyses.

Dual Leucine Zipper Kinase Regulates Dscam Expression through a Noncanonical Function of the Cytoplasmic Poly(A)-Binding Protein.

Dual leucine zipper kinase (DLK) plays a pivotal role in the development, degeneration, and regeneration of neurons. DLK can regulate gene expression post-transcriptionally, but the underlying mechanism remains poorly understood. The Drosophila DLK, Wallenda (Wnd), regulates the expression of Down syndrome cell adhesion molecule (Dscam) to control presynaptic arbor growth. This regulation is mediated by the 3' untranslated region (3'UTR) of Dscam mRNA, which suggests that RNA binding proteins (RBPs) mediate DLK function. We performed a genome-wide cell-based RNAi screen of RBPs and identified the cytoplasmic poly(A)-binding protein, pAbp, as an RBP that mediates Wnd-induced increase in Dscam expression. Genetic analysis shows that Wnd requires pAbp for promoting presynaptic arbor growth and for enhancing Dscam expression. Our analysis revealed that Dscam mRNAs harbor short poly(A) tails. We identified a region in Dscam 3'UTR that specifically interacts with pAbp. Removing this region significantly reduced Wnd-induced increase in Dscam expression. These suggest that a noncanonical interaction of PABP with the 3'UTR of target transcripts is essential for DLK functions.SIGNIFICANCE STATEMENT The kinase DLK plays key roles in a multitude of neuronal responses, including axon development, neurodegeneration, and nerve injury. Previous studies show that DLK acts via mRNAs to regulate protein synthesis, but how DLK does so is poorly understood. This study demonstrates that DLK regulates the synthesis of Dscam through the poly(A)-binding protein PABP-C. Whereas PABP-C is known as a general translational activator, our study shows that DLK-mediated Dscam expression involves a noncanonical interaction between PABP-C and the Dscam mRNA, which leads to a selective regulation of Dscam translation by PABP-C. Thus, our study provides novel insights into the mechanisms that underlie the function of DLK and regulation of gene expression of PABP-C.

Migrating pyramidal neurons require DSCAM to bypass the border of the developing cortical plate.

During mammalian neocortex development, nascent pyramidal neurons migrate along radial glial cells and overtake earlier-born neurons to terminate at the front of the developing cortical plate (CP), leading to the outward expansion of the CP border. While much has been learned about the cellular and molecular mechanisms that underlie the migration of pyramidal neurons, how migrating neurons bypass the preceding neurons at the end of migration to reach their final positions remains poorly understood. Here, we report that Down syndrome cell adhesion molecule (DSCAM) is required for migrating neurons to bypass their post-migratory predecessors during the expansion of the upper cortical layers. DSCAM is a type I transmembrane cell adhesion molecule. It has been linked to Down syndrome through its location in the Down syndrome critical region of Chromosome 21 trisomy and to autism spectrum disorders through loss-of-function mutations. Ex vivo time-lapse imaging demonstrates that DSCAM is required for migrating neurons to bypass their post-migratory predecessors, crossing the CP border to expand the upper cortical layers. In DSCAM-deficient cortices, migrating neurons stop prematurely under the CP border, leading to thinner and denser upper cortical layers. We further show that DSCAM weakens cell adhesion mediated by N-cadherin in the upper cortical plate, allowing migrating neurons to traverse the CP border and expand the CP. These findings suggest that DSCAM is required for proper migratory termination and final positioning of nascent pyramidal neurons, which may provide insight into brain disorders that exhibit thinner upper layers of the cerebral cortex without neuronal loss.SIGNIFICANCE STATEMENTNewly born neurons in the developing mammalian neocortex migrate outward towards the cortical surface, bypassing earlier born neurons to expand the developing cortex. How migrating neurons bypass the preceding neurons and terminate at the front of the expanding cortex remains poorly understood. We demonstrate that Down syndrome cell adhesion molecule (DSCAM), linked to Down syndrome and autism spectrum disorder, is required by migrating neurons to bypass their post-migratory predecessors and terminate migration in the outwardly expanding cortical layer. Migrating neurons deficient in DSCAM stop prematurely, failing to expand the cortex. We further show that DSCAM likely mediates migratory termination by weakening cell-adhesion mediated by N-cadherin.

SNR-enhanced signal delivery scheme with delta-sigma modulation in a four-mode fiber system.

This Letter proposes a scheme for optimizing the signal-to-noise ratio (SNR) of signal to improve the system performance by a 1 bit delta-sigma modulation (DSM) in a four-mode MDM system for mobile fronthaul. A 1 bit digitalized signal with an SNR of 60 dB from transmitter digital signal processing (Tx DSP) can be achieved. Based on this system, an experimental demonstration of the ultrahigh-order 1048576-QAM signal transmission over a 50 km strong-coupling few-mode fiber (FMF) is successfully realized. With DSP, the bit error rate (BER) of the received 1048576-QAM signals over four modes transmission is below the 20% soft-decision forward error correction (20% SD-FEC) threshold of 2.4 × 10-2. To the best of our knowledge, this is the first time that the combination of DSM technology and strong-coupling MDM system is achieved and that the highest-modulation order with DSM reported in MDM system is reached. This experimental demonstration of the proposed novel scheme in MDM system can provide an effective solution for ultra-large-capacity mobile fronthaul in the future.

Epstein-Barr virus immediate-early protein Zta mediates the proliferation and migration of HER2-overexpressing cancer cells.

Epstein-Barr virus immediate-early protein Zta plays an active role in altering cellular gene expression, which may be fundamentally linked to the viral life cycle, cell cycle, cell growth, and differentiation. HER2 is associated with a wide variety of human cancers, and its knockdown significantly reverses the malignant features of HER2-positive cancers. The aim of this study was to investigate the potential role of Zta in regulating HER2 expression and phenotype changes of MDA-MB-453 cells. Our results indicate that ectopic expression of Zta resulted in downregulation of the HER2 protein in cancer cells (MDA-MB-453, SKBR-3, BT474, and SKOV-3). The Zta protein significantly decreased HER2 mRNA and protein expression in MDA-MB-453 cells in a dose-dependent manner. Mechanistically, Zta recognized and targeted the promoter of HER2 gene, reducing the transcriptional activity of the HER2 gene. Zta induced G0/G1 arrest of MDA-MB-453 cells, inhibiting their proliferation and migration activity. These data suggest that Zta may act as a transforming suppressor of the HER2 gene.

Privacy-protecting behaviours of risk detection in people with dementia using videos.

BACKGROUND: People living with dementia often exhibit behavioural and psychological symptoms of dementia that can put their and others' safety at risk. Existing video surveillance systems in long-term care facilities can be used to monitor such behaviours of risk to alert the staff to prevent potential injuries or death in some cases. However, these behaviours of risk events are heterogeneous and infrequent in comparison to normal events. Moreover, analysing raw videos can also raise privacy concerns. PURPOSE: In this paper, we present two novel privacy-protecting video-based anomaly detection approaches to detect behaviours of risks in people with dementia. METHODS: We either extracted body pose information as skeletons or used semantic segmentation masks to replace multiple humans in the scene with their semantic boundaries. Our work differs from most existing approaches for video anomaly detection that focus on appearance-based features, which can put the privacy of a person at risk and is also susceptible to pixel-based noise, including illumination and viewing direction. We used anonymized videos of normal activities to train customized spatio-temporal convolutional autoencoders and identify behaviours of risk as anomalies. RESULTS: We showed our results on a real-world study conducted in a dementia care unit with patients with dementia, containing approximately 21 h of normal activities data for training and 9 h of data containing normal and behaviours of risk events for testing. We compared our approaches with the original RGB videos and obtained a similar area under the receiver operating characteristic curve performance of 0.807 for the skeleton-based approach and 0.823 for the segmentation mask-based approach. CONCLUSIONS: This is one of the first studies to incorporate privacy for the detection of behaviours of risks in people with dementia. Our research opens up new avenues to reduce injuries in long-term care homes, improve the quality of life of residents, and design privacy-aware approaches for people living in the community.

Researched Apps Used in Dementia Care for People Living With Dementia and Their Informal Caregivers: Systematic Review on App Features, Security, and Usability.

BACKGROUND: Studies have shown that mobile apps have the potential to serve as nonpharmacological interventions for dementia care, improving the quality of life of people living with dementia and their informal caregivers. However, little is known about the needs for and privacy aspects of these mobile apps in dementia care. OBJECTIVE: This review seeks to understand the landscape of existing mobile apps in dementia care for people living with dementia and their caregivers with respect to app features, usability testing, privacy, and security. METHODS: ACM Digital Library, Cochrane Central Register of Controlled Trials, Compendex, Embase, Inspec, Ovid MEDLINE, PsycINFO, and Scopus were searched. Studies were included if they included people with dementia living in the community, their informal caregivers, or both; focused on apps in dementia care using smartphones or tablet computers; and covered usability evaluation of the app. Records were independently screened, and 2 reviewers extracted the data. The Centre for Evidence-Based Medicine critical appraisal tool and Mixed Methods Appraisal Tool were used to assess the risk of bias in the included studies. Thematic synthesis was used, and the findings were summarized and tabulated based on each research aim. RESULTS: Overall, 44 studies were included in this review, with 39 (89%) published after 2015. In total, 50 apps were included in the study, with more apps developed for people living with dementia as end users compared with caregivers. Most studies (27/44, 61%) used tablet computers. The most common app feature was cognitive stimulation. This review presented 9 app usability themes: user interface, physical considerations, screen size, interaction challenges, meeting user needs, lack of self-awareness of app needs, stigma, technological inexperience, and technical support. In total, 5 methods (questionnaires, interviews, observations, logging, and focus groups) were used to evaluate usability. There was little focus on the privacy and security aspects, including data transfer and protection, of mobile apps for people living with dementia. CONCLUSIONS: The limitations of this review include 1 reviewer conducting the full-text screening, its restriction to studies published in English, and the exclusion of apps that lacked empirical usability testing. As a result, there may be an incomplete representation of the available apps in the field of dementia care. However, this review highlights significant concerns related to the usability, privacy, and security of existing mobile apps for people living with dementia and their caregivers. The findings of this review provide a valuable framework to guide app developers and researchers in the areas of privacy policy development, app development strategies, and the importance of conducting thorough usability testing for their apps. By considering these factors, future work in this field can be advanced to enhance the quality and effectiveness of dementia care apps. TRIAL REGISTRATION: PROSPERO CRD42020216141; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=216141. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1159/000514838.

Development of a quadruple PCR-based gene microarray for detection of vaccine and wild-type classical swine fever virus, African swine fever virus and atypical porcine pestivirus.

BACKGROUND: Classical swine fever (CSF), African swine fever (ASF), and atypical porcine pestivirus (APPV) are acute, virulent, and contagious viral diseases currently hampering the pig industry in China, which result in mummification or stillbirths in piglets and mortality in pigs. Diagnostic assays for the differentiation of infection and vaccination of CSFV, in addition to the detection of ASFV and APPV, are urgently required for better prevention, control, and elimination of these viral diseases in China. METHODS: A quadruple PCR-based gene microarray assay was developed in this study to simultaneously detect wild-type and vaccine CSFV strains, ASFV and APPV according to their conserved regions. Forty-two laboratory-confirmed samples, including positive samples of 10 other swine viral diseases, were tested using this assay to confirm its high specificity. RESULTS: This assay's limit of detections (LODs) for the wild-type and vaccine CSFV were 6.98 and 6.92 copies/µL. LODs for ASFV and APPV were 2.56 × 10 and 1.80 × 10 copies/µL, respectively. When compared with standard RT-PCR or qPCR for CSFV (GB/T 26875-2018), ASFV (MARR issue No.172), or APPV (CN108611442A) using 219 clinical samples, the coincidence was 100%. The results showed that this assay with high sensitivity could specifically distinguish ASFV, APPV, and CSFV, including CSFV infection and immunization. CONCLUSION: This assay provides a practical, simple, economic, and reliable test for the rapid detection and accurate diagnosis of the three viruses and may have good prospects for application in an epidemiological investigation, prevention, and control and elimination of these three diseases.

Fresh hetero-metallic compound as luminescent sensor for detection of CS2 and inhibitory activity on children diabetes.

The combination of the dicarboxylate ligand of 2-aminoterephthalic acid (H2L), Cd(NO3)2·4H2O, and KNO3 under hydrothermal condition formed a fresh hetero-metallic coordination polymer, namely, [CdK2(L)2(H2O)4]n (1). The compound exhibited a high luminescence intensity at normal environment as well as high sensitivity and selectivity in the measurement of CS2. The effect of the fresh compound on childhood diabetes was investigated. A blood glucose monitor was utilized to assess the blood glucose level of the body after the addition of the compound. Moreover, the relative expression level of the insulin recipient on hepatocytes was assessed by real time RT-PCR.

Technology-Based Compensation Assessment and Detection of Upper Extremity Activities of Stroke Survivors: Systematic Review.

BACKGROUND: Upper extremity (UE) impairment affects up to 80% of stroke survivors and accounts for most of the rehabilitation after discharge from the hospital release. Compensation, commonly used by stroke survivors during UE rehabilitation, is applied to adapt to the loss of motor function and may impede the rehabilitation process in the long term and lead to new orthopedic problems. Intensive monitoring of compensatory movements is critical for improving the functional outcomes during rehabilitation. OBJECTIVE: This review analyzes how technology-based methods have been applied to assess and detect compensation during stroke UE rehabilitation. METHODS: We conducted a wide database search. All studies were independently screened by 2 reviewers (XW and YF), with a third reviewer (BY) involved in resolving discrepancies. The final included studies were rated according to their level of clinical evidence based on their correlation with clinical scales (with the same tasks or the same evaluation criteria). One reviewer (XW) extracted data on publication, demographic information, compensation types, sensors used for compensation assessment, compensation measurements, and statistical or artificial intelligence methods. Accuracy was checked by another reviewer (YF). Four research questions were presented. For each question, the data were synthesized and tabulated, and a descriptive summary of the findings was provided. The data were synthesized and tabulated based on each research question. RESULTS: A total of 72 studies were included in this review. In all, 2 types of compensation were identified: disuse of the affected upper limb and awkward use of the affected upper limb to adjust for limited strength, mobility, and motor control. Various models and quantitative measurements have been proposed to characterize compensation. Body-worn technology (25/72, 35% studies) was the most used sensor technology to assess compensation, followed by marker-based motion capture system (24/72, 33% studies) and marker-free vision sensor technology (16/72, 22% studies). Most studies (56/72, 78% studies) used statistical methods for compensation assessment, whereas heterogeneous machine learning algorithms (15/72, 21% studies) were also applied for automatic detection of compensatory movements and postures. CONCLUSIONS: This systematic review provides insights for future research on technology-based compensation assessment and detection in stroke UE rehabilitation. Technology-based compensation assessment and detection have the capacity to augment rehabilitation independent of the constant care of therapists. The drawbacks of each sensor in compensation assessment and detection are discussed, and future research could focus on methods to overcome these disadvantages. It is advised that open data together with multilabel classification algorithms or deep learning algorithms could benefit from automatic real time compensation detection. It is also recommended that technology-based compensation predictions be explored.

The Development and Concurrent Validity of a Multi-Sensor-Based Frailty Toolkit for In-Home Frailty Assessment.

Early identification of frailty is crucial to prevent or reverse its progression but faces challenges due to frailty's insidious onset. Monitoring behavioral changes in real life may offer opportunities for the early identification of frailty before clinical visits. This study presented a sensor-based system that used heterogeneous sensors and cloud technologies to monitor behavioral and physical signs of frailty from home settings. We aimed to validate the concurrent validity of the sensor measurements. The sensor system consisted of multiple types of ambient sensors, a smart speaker, and a smart weight scale. The selection of these sensors was based on behavioral and physical signs associated with frailty. Older adults' perspectives were also included in the system design. The sensor system prototype was tested in a simulated home lab environment with nine young, healthy participants. Cohen's Kappa and Bland−Altman Plot were used to evaluate the agreements between the sensor and ground truth measurements. Excellent concurrent validity was achieved for all sensors except for the smart weight scale. The bivariate correlation between the smart and traditional weight scales showed a strong, positive correlation between the two measurements (r = 0.942, n = 24, p < 0.001). Overall, this work showed that the Frailty Toolkit (FT) is reliable for monitoring physical and behavioral signs of frailty in home settings.

Doubly Modulated Optical Lattice Clock: Interference and Topology.

The quantum system under periodical modulation is the simplest path to understand the quantum nonequilibrium system because it can be well described by the effective static Floquet Hamiltonian. Under the stroboscopic measurement, the initial phase is usually irrelevant. However, if two uncorrelated parameters are modulated, their relative phase cannot be gauged out so that the physics can be dramatically changed. Here, we simultaneously modulate the frequency of the lattice laser and the Rabi frequency in an optical lattice clock (OLC) system. Thanks to the ultrahigh precision and ultrastability of the OLC, the relative phase could be fine-tuned. As a smoking gun, we observed the interference between two Floquet channels. Finally, by experimentally detecting the eigenenergies, we demonstrate the relation between the effective Floquet Hamiltonian and the one-dimensional topological insulator with a high winding number. Our experiment not only provides a direction for detecting the phase effect but also paves a way in simulating the quantum topological phase in the OLC platform.

Dementia Care Apps for People with Dementia and Informal Caregivers: A Systematic Review Protocol.

Dementia drastically impacts the quality of life (QOL) of both people living with dementia (PLwD) and their family caregivers. As dementia progresses and care needs escalate, the likelihood of institutionalization is increased, which is counter to the wishes of the majority of older adults and their family members. Dementia care apps can provide critical support and have the potential to improve the QOL of both PLwD and their family caregivers and reduce perceived caregivers' burden. However, there is a lack of understanding of the needs of both PLwD and their family caregivers related to dementia care apps. There is also a gap in understanding the privacy concerns in relation to the apps among older adults with dementia and their caregivers. As such, the main aims of this systematic review are to understand the landscape of dementia mobile apps targeting PLwD and their caregivers with respect to the features of the apps, usability testing, and the privacy and security aspects of the app from the perspective of both app developers/researchers and the end users (PLwD and family caregivers who provide care of PLwD). Extensive databases, including ACM Digital Library, Cochrane Central Register of Controlled Trials, Compendex, Embase, Inspec, Ovid MEDLINE(R) Daily, Proquest Dissertations and These Global, PsycINFO, and Scopus, have been searched. All searches are from the inception of the databases. All peer-reviewed studies and articles written in the English language are included. Two reviewers will independently screen and select the studies with the involvement of a third reviewer for disagreements. Data will be abstracted using a custom data extraction form that is made based on the research questions. Critical Appraisal Skills Programme (CASP) checklists will be used to assess the study quality. As the first review of its kind, the findings from this review will provide valuable insights related to the needs of the dementia care apps for both PLwD and their family caregivers. The review will be relevant to health providers who are interested in using technologies to promote the independence of PLwD and reduce the stress experienced from caregivers of PLwD. The review will also serve as a guide to app developers and researchers to design usable and acceptable apps. In addition, the review will provide critical knowledge of the privacy and security features of the app to reveal the valid concerns from the end users and thus help with the uptake and adoption of the dementia care apps.