Trajectory mapping of the early Drosophila germline reveals controls of zygotic activation and sex differentiation.

Germ cells in Drosophila melanogaster are specified maternally shortly after fertilization and are transcriptionally quiescent until their zygotic genome is activated to sustain further development. To understand the molecular basis of this process, we analyzed the progressing transcriptomes of early male and female germ cells at the single-cell level between germline specification and coalescence with somatic gonadal cells. Our data comprehensively cover zygotic activation in the germline genome, and analyses on genes that exhibit germline-restricted expression reveal that polymerase pausing and differential RNA stability are important mechanisms that establish gene expression differences between the germline and soma. In addition, we observe an immediate bifurcation between the male and female germ cells as zygotic transcription begins. The main difference between the two sexes is an elevation in X Chromosome expression in females relative to males, signifying incomplete dosage compensation, with a few select genes exhibiting even higher expression increases. These indicate that the male program is the default mode in the germline that is driven to female development with a second X Chromosome.

Targeting cathepsin S promotes activation of OLF1-BDNF/TrkB axis to enhance cognitive function.

BACKGROUND: Cathepsin S (CTSS) is a cysteine protease that played diverse roles in immunity, tumor metastasis, aging and other pathological alterations. At the cellular level, increased CTSS levels have been associated with the secretion of pro-inflammatory cytokines and disrupted the homeostasis of Ca2+ flux. Once CTSS was suppressed, elevated levels of anti-inflammatory cytokines and changes of Ca2+ influx were observed. These findings have inspired us to explore the potential role of CTSS on cognitive functions. METHODS: We conducted classic Y-maze and Barnes Maze tests to assess the spatial and working memory of Ctss-/- mice, Ctss+/+ mice and Ctss+/+ mice injected with the CTSS inhibitor (RJW-58). Ex vivo analyses including long-term potentiation (LTP), Golgi staining, immunofluorescence staining of sectioned whole brain tissues obtained from experimental animals were conducted. Furthermore, molecular studies were carried out using cultured HT-22 cell line and primary cortical neurons that treated with RJW-58 to comprehensively assess the gene and protein expressions. RESULTS: Our findings reported that targeting cathepsin S (CTSS) yields improvements in cognitive function, enhancing both working and spatial memory in behavior models. Ex vivo studies showed elevated levels of long-term potentiation levels and increased synaptic complexity. Microarray analysis demonstrated that brain-derived neurotrophic factor (BDNF) was upregulated when CTSS was knocked down by using siRNA. Moreover, the pharmacological blockade of the CTSS enzymatic activity promoted BDNF expression in a dose- and time-dependent manner. Notably, the inhibition of CTSS was associated with increased neurogenesis in the murine dentate gyrus. These results suggested a promising role of CTSS modulation in cognitive enhancement and neurogenesis. CONCLUSION: Our findings suggest a critical role of CTSS in the regulation of cognitive function by modulating the Ca2+ influx, leading to enhanced activation of the BDNF/TrkB axis. Our study may provide a novel strategy for improving cognitive function by targeting CTSS.

COVID-19 control measures unexpectedly increased the duration of stay at High Speed Rail stations during the first community outbreak in Taiwan.

During the COVID-19 pandemic, Taiwan has implemented strict border controls and community spread prevention measures. As part of these efforts, the government also implemented measures for public transportation. In Taiwan, there are two primary public transportation systems: Taiwan Railways (TR) is commonly utilized for local travel, while the Taiwan High-Speed Rail (THSR) is preferred for business trips and long-distance journeys due to its higher speed. In this study, we examined the impact of these disease prevention measures on the number of passengers and duration of stay in two major public transportation systems during the first community outbreak from April 29th to May 29th, 2021. Using data from a local telecommunications company, our study observed an expected decrease in the number of passengers after the cancellation of non-reserved seats at both TR and THSR stations across all 19 cities in the main island of Taiwan. Surprisingly, however, the duration of stay in some of the cities unexpectedly increased, especially at THSR stations. This unanticipated rise in the duration of stay has the potential to elevate contact probability among passengers and, consequently, the transmission rate. Our analysis shows that intervention policies may result in unforeseen outcomes, highlighting the crucial role of human mobility data as a real-time reference for policymakers. It enables them to monitor the impact of disease prevention measures and facilitates informed, data-driven decision-making.

The middle-aged and older Chinese adults' health using actigraphy in Taiwan (MOCHA-T): protocol for a multidimensional dataset of health and lifestyle.

BACKGROUND AND OBJECTIVES: Older adults keep transforming with Baby Boomers and Gen Xers being the leading older population. Their lifestyle, however, is not well understood. The middle-aged and older Chinese adults' health using actigraphy in Taiwan (MOCHA-T) collected both objective and subjective data to depict the health and lifestyle of this population. The objectives, design, and measures of the MOCHA-T study are introduced, and the caveats and future directions related to the use of the data are presented. METHODS: People aged 50 and over were recruited from the community, with a subset of women aged 45-49 invited to supplement data on menopause and aging. Four instruments (i.e., self-reported questionnaires, diary, wrist actigraphy recorder, and GPS) were used to collect measures of sociodemographic, health, psychosocial, behavioral, temporal, and spatial data. RESULTS: A total of 242 participants who returned the informed consent and questionnaires were recruited in the MOCHA-T study. Among them, 94.6%, 95.0%, and 25.2% also completed the diary, actigraphy, and GPS data, respectively. There was almost no difference in sociodemographic characteristics between those with and without a completed diary, actigraphy, and GPS data, except for age group and educational level for those who returned completed actigraphy data. CONCLUSION: The MOCHA-T study is a multidimensional dataset that allows researchers to describe the health, behaviors, and lifestyle patterns, and their interactions with the environment of the newer generation of middle-aged and older adults in Taiwan. It can be compared with other countries with actigraphy and GPS-based lifestyle data of middle-aged and older adults in the future.

Distinguishing gene flow between malaria parasite populations.

Measuring gene flow between malaria parasite populations in different geographic locations can provide strategic information for malaria control interventions. Multiple important questions pertaining to the design of such studies remain unanswered, limiting efforts to operationalize genomic surveillance tools for routine public health use. This report examines the use of population-level summaries of genetic divergence (FST) and relatedness (identity-by-descent) to distinguish levels of gene flow between malaria populations, focused on field-relevant questions about data size, sampling, and interpretability of observations from genomic surveillance studies. To do this, we use P. falciparum whole genome sequence data and simulated sequence data approximating malaria populations evolving under different current and historical epidemiological conditions. We employ mobile-phone associated mobility data to estimate parasite migration rates over different spatial scales and use this to inform our analysis. This analysis underscores the complementary nature of divergence- and relatedness-based metrics for distinguishing gene flow over different temporal and spatial scales and characterizes the data requirements for using these metrics in different contexts. Our results have implications for the design and implementation of malaria genomic surveillance studies.

Effects of a Taiwanese Adaptation of the Group Cognitive Stimulation Therapy Program on Mild-To-Moderate Dementia: A Quasi-Experimental Trial.

Cognitive stimulation therapy (CST) was found to significantly improve cognitive function and quality of life (QOL) in patients with mild-to-moderate dementia in the UK. However, indigenous research on older adults with dementia in Taiwan is scarce. Therefore, this study developed and investigated the effects of a Taiwan version of group CST (CST-T) through a quasi-experimental trial. Excluding the dropouts, there were 13 experimental participants (M = 78.9 ± 9.0) and 13 control participants (77.9 ± 5.6). The results indicated significant improvements in cognitive function, QOL, and daily life functioning in the experimental group compared with the control group, and these effects remained evident at a 3-month follow-up.

Real-time forecasting of COVID-19 spread according to protective behavior and vaccination: autoregressive integrated moving average models.

BACKGROUND: Mathematical and statistical models are used to predict trends in epidemic spread and determine the effectiveness of control measures. Automatic regressive integrated moving average (ARIMA) models are used for time-series forecasting, but only few models of the 2019 coronavirus disease (COVID-19) pandemic have incorporated protective behaviors or vaccination, known to be effective for pandemic control. METHODS: To improve the accuracy of prediction, we applied newly developed ARIMA models with predictors (mask wearing, avoiding going out, and vaccination) to forecast weekly COVID-19 case growth rates in Canada, France, Italy, and Israel between January 2021 and March 2022. The open-source data was sourced from the YouGov survey and Our World in Data. Prediction performance was evaluated using the root mean square error (RMSE) and the corrected Akaike information criterion (AICc). RESULTS: A model with mask wearing and vaccination variables performed best for the pandemic period in which the Alpha and Delta viral variants were predominant (before November 2021). A model using only past case growth rates as autoregressive predictors performed best for the Omicron period (after December 2021). The models suggested that protective behaviors and vaccination are associated with the reduction of COVID-19 case growth rates, with booster vaccine coverage playing a particularly vital role during the Omicron period. For example, each unit increase in mask wearing and avoiding going out significantly reduced the case growth rate during the Alpha/Delta period in Canada (-0.81 and -0.54, respectively; both p < 0.05). In the Omicron period, each unit increase in the number of booster doses resulted in a significant reduction of the case growth rate in Canada (-0.03), Israel (-0.12), Italy (-0.02), and France (-0.03); all p < 0.05. CONCLUSIONS: The key findings of this study are incorporating behavior and vaccination as predictors led to accurate predictions and highlighted their significant role in controlling the pandemic. These models are easily interpretable and can be embedded in a "real-time" schedule with weekly data updates. They can support timely decision making about policies to control dynamically changing epidemics.

Examining Human-Smartphone Interaction as a Proxy for Circadian Rhythm in Patients With Insomnia: Cross-Sectional Study.

BACKGROUND: The sleep and circadian rhythm patterns associated with smartphone use, which are influenced by mental activities, might be closely linked to sleep quality and depressive symptoms, similar to the conventional actigraphy-based assessments of physical activity. OBJECTIVE: The primary objective of this study was to develop app-defined circadian rhythm and sleep indicators and compare them with actigraphy-derived measures. Additionally, we aimed to explore the clinical correlations of these indicators in individuals with insomnia and healthy controls. METHODS: The mobile app "Rhythm" was developed to record smartphone use time stamps and calculate circadian rhythms in 33 patients with insomnia and 33 age- and gender-matched healthy controls, totaling 2097 person-days. Simultaneously, we used standard actigraphy to quantify participants' sleep-wake cycles. Sleep indicators included sleep onset, wake time (WT), wake after sleep onset (WASO), and the number of awakenings (NAWK). Circadian rhythm metrics quantified the relative amplitude, interdaily stability, and intradaily variability based on either smartphone use or physical activity data. RESULTS: Comparisons between app-defined and actigraphy-defined sleep onsets, WTs, total sleep times, and NAWK did not reveal any significant differences (all P>.05). Both app-defined and actigraphy-defined sleep indicators successfully captured clinical features of insomnia, indicating prolonged WASO, increased NAWK, and delayed sleep onset and WT in patients with insomnia compared with healthy controls. The Pittsburgh Sleep Quality Index scores were positively correlated with WASO and NAWK, regardless of whether they were measured by the app or actigraphy. Depressive symptom scores were positively correlated with app-defined intradaily variability (ß=9.786, SD 3.756; P=.01) and negatively correlated with actigraphy-based relative amplitude (ß=-21.693, SD 8.214; P=.01), indicating disrupted circadian rhythmicity in individuals with depression. However, depressive symptom scores were negatively correlated with actigraphy-based intradaily variability (ß=-7.877, SD 3.110; P=.01) and not significantly correlated with app-defined relative amplitude (ß=-3.859, SD 12.352; P=.76). CONCLUSIONS: This study highlights the potential of smartphone-derived sleep and circadian rhythms as digital biomarkers, complementing standard actigraphy indicators. Although significant correlations with clinical manifestations of insomnia were observed, limitations in the evidence and the need for further research on predictive utility should be considered. Nonetheless, smartphone data hold promise for enhancing sleep monitoring and mental health assessments in digital health research.

A tale of two lineages: how the strains of the earliest divergent symbiotic Frankia clade spread over the world.

It is currently assumed that around 100 million years ago, the common ancestor to the Fabales, Fagales, Rosales and Cucurbitales in Gondwana, developed a root nodule symbiosis with a nitrogen-fixing bacterium. The symbiotic trait evolved first in Frankia cluster-2; thus, strains belonging to this cluster are the best extant representatives of this original symbiont. Most cluster-2 strains could not be cultured to date, except for Frankia coriariae, and therefore many aspects of the symbiosis are still elusive. Based on phylogenetics of cluster-2 metagenome-assembled genomes (MAGs), it has been shown that the genomes of strains originating in Eurasia are highly conserved. These MAGs are more closely related to Frankia cluster-2 in North America than to the single genome available thus far from the southern hemisphere, i.e., from Papua New Guinea.To unravel more biodiversity within Frankia cluster-2 and predict routes of dispersal from Gondwana, we sequenced and analysed the MAGs of Frankia cluster-2 from Coriaria japonica and Coriaria intermedia growing in Japan, Taiwan and the Philippines. Phylogenetic analyses indicate there is a clear split within Frankia cluster-2, separating a continental from an island lineage. Presumably, these lineages already diverged in Gondwana.Based on fossil data on the host plants, we propose that these two lineages dispersed via at least two routes. While the continental lineage reached Eurasia together with their host plants via the Indian subcontinent, the island lineage spread towards Japan with an unknown host plant.

Evaluating the Performance of Malaria Genetics for Inferring Changes in Transmission Intensity Using Transmission Modeling.

Substantial progress has been made globally to control malaria, however there is a growing need for innovative new tools to ensure continued progress. One approach is to harness genetic sequencing and accompanying methodological approaches as have been used in the control of other infectious diseases. However, to utilize these methodologies for malaria, we first need to extend the methods to capture the complex interactions between parasites, human and vector hosts, and environment, which all impact the level of genetic diversity and relatedness of malaria parasites. We develop an individual-based transmission model to simulate malaria parasite genetics parameterized using estimated relationships between complexity of infection and age from five regions in Uganda and Kenya. We predict that cotransmission and superinfection contribute equally to within-host parasite genetic diversity at 11.5% PCR prevalence, above which superinfections dominate. Finally, we characterize the predictive power of six metrics of parasite genetics for detecting changes in transmission intensity, before grouping them in an ensemble statistical model. The model predicted malaria prevalence with a mean absolute error of 0.055. Different assumptions about the availability of sample metadata were considered, with the most accurate predictions of malaria prevalence made when the clinical status and age of sampled individuals is known. Parasite genetics may provide a novel surveillance tool for estimating the prevalence of malaria in areas in which prevalence surveys are not feasible. However, the findings presented here reinforce the need for patient metadata to be recorded and made available within all future attempts to use parasite genetics for surveillance.

Ten-year trends in depression care in Taiwan.

BACKGROUND/PURPOSE: The number of psychiatrists working in community clinics in Taiwan has increased dramatically in the recent decade. This study aimed to investigate the trend of prevalence and incidence of depressive disorders and assess the quality of depression care between 2007 and 2016 in Taiwan. METHODS: We used the claims database derived from Taiwan's National Health Insurance (NHI) program, in which approximately 23.0 million individuals were enrolled, translating to a coverage rate of 99%. Patients with depressive disorders were identified based on International Classification of Diseases codes. The process indicators of depression care quality included visit, duration, and dose adequacy. The outcome indicators included the rate of psychiatric hospitalisation, emergency visit, self-harm hospitalisation, and suicide. RESULTS: The prevalence of treated depressive disorders increased from 1.61% in 2007 to 1.92% in 2016, i.e., a 25% increase, whereas the incidence of first-ever or recurrent depressive disorder did not change significantly. The number of patients treated by psychiatrists and in community clinics also increased. The quality of depression care improved, the proportion of patients receiving minimum psychiatric clinic follow-up and adequate medication increased, and the rate of emergency visits, psychiatric hospitalisation, and self-harm hospitalisation declined. CONCLUSION: The community-based psychiatric services increased and the quality indicators of depression care in Taiwan improved during 2007-2016. The causality warrants further investigations.

Serum Homocysteine, Folate, and Vitamin B12 Levels in Patients with Systemic Lupus Erythematosus: A Meta-Analysis and Meta-Regression.

BACKGROUND: Patients with systemic lupus erythematosus (SLE) have elevated cardiovascular risk. Hyperhomocysteinemia may be one of the contributing factors to this phenomenon. This study therefore aimed to compare the serum homocysteine levels and the levels of folate and vitamin B12, cofactors for homocysteine metabolism, between individuals with and without SLE. METHODS: A literature search was performed in PubMed, Embase, and the Cochrane library (from inception to March 31, 2019). Studies comparing serum homocysteine, folate or vitamin B12 levels between individuals with and without SLE were selected. Of the 1040 screened studies, 50 studies met the inclusion criteria. RESULTS: A total of 50 studies involving 4396 patients with SLE were included. Patients with SLE had a significantly higher serum level of homocysteine (standardized mean difference [SMD], 1.134; 95% CI, 0.795-1.474) and lower level of vitamin B12 (SMD, -0.359; 95% CI, -0.638 to -0.080) than controls. The folate level didn't differ markedly between SLE patients and the control group (SMD, -0.276; 95% CI, -0.674-0.123). Subgroup analysis showed consistent results in adult SLE patients. A random effects meta-regression analysis revealed a significantly inverse correlation between the SMD of homocysteine levels and C3 levels (coefficient, -0.0356, 95% CI, -0.054 to -0.0171; P < .001) and C4 levels (coefficient, -0.0876, 95% CI, -0.1407 to -0.0345; P = .0012). CONCLUSIONS: Serum homocysteine levels were higher and vitamin B12 levels were lower among individuals with SLE than those without SLE. Physicians are encouraged to monitor these parameters and offer timely interventions for patients with SLE.

Treating toxic epidermal necrolysis with systemic immunomodulating therapies: A systematic review and network meta-analysis.

BACKGROUND: Various systemic immunomodulating therapies have been used to treat toxic epidermal necrolysis (TEN), but their efficacy remains unclear. OBJECTIVE: To perform a systematic review and network meta-analysis (NMA) evaluating the effects of systemic immunomodulating therapies on mortality for Stevens-Johnson syndrome (SJS)/TEN overlap and TEN. METHODS: A literature search was performed in online databases (from inception to October 31, 2019). Outcomes were mortality rates and Score of Toxic Epidermal Necrolysis (SCORTEN)-based standardized mortality ratio (SMR). A frequentist random-effects model was adopted. RESULTS: Sixty-seven studies involving 2079 patients were included. An NMA of 10 treatments showed that none was superior to supportive care in reducing mortality rates and that thalidomide was associated with a significantly higher mortality rate (odds ratio, 11.67; 95% confidence interval [CI], 1.42-95.96). For SMR, an NMA of 11 treatment arms showed that corticosteroids and intravenous immunoglobulin combination therapy was the only treatment with significant survival benefits (SMR, 0.53; 95% CI, 0.31-0.93). LIMITATIONS: Heterogeneity and a paucity of eligible randomized controlled trials. CONCLUSIONS: Combination therapy with corticosteroids and IVIg may reduce mortality risks in patients with SJS/TEN overlap and TEN. Cyclosporine and etanercept are promising therapies, but more studies are required to provide clearer evidence.

Transmission of SARS-CoV-2 before and after symptom onset: impact of nonpharmaceutical interventions in China.

Nonpharmaceutical interventions, such as contact tracing and quarantine, have been the primary means of controlling the spread of SARS-CoV-2; however, it remains uncertain which interventions are most effective at reducing transmission at the population level. Using serial interval data from before and after the rollout of nonpharmaceutical interventions in China, we estimate that the relative frequency of presymptomatic transmission increased from 34% before the rollout to 71% afterward. The shift toward earlier transmission indicates a disproportionate reduction in transmission post-symptom onset. We estimate that, following the rollout of nonpharmaceutical interventions, transmission post-symptom onset was reduced by 82% whereas presymptomatic transmission decreased by only 16%. The observation that only one-third of transmission was presymptomatic at baseline, combined with the finding that NPIs reduced presymptomatic transmission by less than 20%, suggests that the overall impact of NPIs was driven in large part by reductions in transmission following symptom onset. This implies that interventions which limit opportunities for transmission in the later stages of infection, such as contact tracing and isolation, are particularly important for control of SARS-CoV-2. Interventions which specifically reduce opportunities for presymptomatic transmission, such as quarantine of asymptomatic contacts, are likely to have smaller, but non-negligible, effects on overall transmission.

Effects of backhand stroke styles on bone mineral content and density in postmenopausal recreational tennis players: a cross-sectional pilot investigation.

BACKGROUND: One-handed backhand (OB) and two-handed backhand (TB) styles are commonly used in tennis, but only TB generates loadings on the non-dominant arm and a greater extension torque on the rear leg, leading to a greater axial torque involving rotation of the hip and trunk. The current study investigated whether those effects can further affect bone area (BA), bone mineral content (BMC) and density (BMD) in postmenopausal recreational tennis players. METHODS: BA, BMC and BMD of the lumbar spine, hip and distal radius were assessed using dual-energy X-ray absorptiometry in TB, OB, and swimmers' group as a control (SG) (all participants self-reported for at least 5 years of exercise history, n = 14 per group). Muscular strength was assessed with a hand dynamometer. Among these three groups, the BA, BMC and BMD of distal radius and muscle strength were assessed using one-way ANOVA, and those of the lumbar region and the hip joint were tested by one-way ANCOVA. RESULTS: TB showed higher BMC and BMD for both lumbar spine and femoral neck than SG (all, p < 0.05). Both OB and TB showed greater BMD inter-trochanter than SG (both, p < 0.05). OB demonstrated greater inter-arm differences in the distal radius, which involved 1/3 distal for BMC and mid-distal radius for BMD compared to the TB and SG (all, p < 0.05). In addition, greater inter-arm asymmetry of grip strength was found in OB compared to TB and SG (both, p < 0.05). CONCLUSION: For postmenopausal women, performing two-handed backhand strokes, leads to higher BMC and BMD in the non-dominant arm, the lumbar region, and hips, indicating potential benefit to maintain bone health and strength. Whether this result leads to reducing the risk of osteoporosis needs to be investigated in further research.

Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan.

BACKGROUND: As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. METHODS: In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. RESULTS: We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. CONCLUSIONS: To prepare for the potential spread within Taiwan, we utilized Facebook's aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions.

COVID-19 in Individuals Treated With Long-Term Hydroxychloroquine: A Propensity Score-Matched Analysis of Cicatricial Alopecia Patients.

Early in the COVID-19 pandemic, anti-malarial agent hydroxychloroquine (HCQ) was touted as a potentially effective COVID-19 treatment due to its purported antiinflammatory and antiviral effects.

Assessing Physicians' Recall Bias of Work Hours With a Mobile App: Interview and App-Recorded Data Comparison.

BACKGROUND: Previous studies have shown inconsistencies in the accuracy of self-reported work hours. However, accurate documentation of work hours is fundamental for the formation of labor policies. Strict work-hour policies decrease medical errors, improve patient safety, and promote physicians' well-being. OBJECTIVE: The aim of this study was to estimate physicians' recall bias of work hours with a mobile app, and to examine the association between the recall bias and physicians' work hours. METHODS: We quantified recall bias by calculating the differences between the app-recorded and self-reported work hours of the previous week and the penultimate week. We recruited 18 physicians to install the "Staff Hours" app, which automatically recorded GPS-defined work hours for 2 months, contributing 1068 person-days. We examined the association between work hours and two recall bias indicators: (1) the difference between self-reported and app-recorded work hours and (2) the percentage of days for which work hours were not precisely recalled during interviews. RESULTS: App-recorded work hours highly correlated with self-reported counterparts (r=0.86-0.88, P<.001). Self-reported work hours were consistently significantly lower than app-recorded hours by -8.97 (SD 8.60) hours and -6.48 (SD 8.29) hours for the previous week and the penultimate week, respectively (both P<.001). The difference for the previous week was significantly correlated with work hours in the previous week (r=-0.410, P=.01), whereas the correlation of the difference with the hours in the penultimate week was not significant (r=-0.119, P=.48). The percentage of hours not recalled (38.6%) was significantly higher for the penultimate week (38.6%) than for the first week (16.0%), and the former was significantly correlated with work hours of the penultimate week (r=0.489, P=.002). CONCLUSIONS: Our study identified the existence of recall bias of work hours, the extent to which the recall was biased, and the influence of work hours on recall bias.

Correction: Artificial Intelligence-Based Prediction of Lung Cancer Risk Using Nonimaging Electronic Medical Records: Deep Learning Approach.

[This corrects the article DOI: 10.2196/26256.].

Artificial Intelligence-Based Prediction of Lung Cancer Risk Using Nonimaging Electronic Medical Records: Deep Learning Approach.

BACKGROUND: Artificial intelligence approaches can integrate complex features and can be used to predict a patient's risk of developing lung cancer, thereby decreasing the need for unnecessary and expensive diagnostic interventions. OBJECTIVE: The aim of this study was to use electronic medical records to prescreen patients who are at risk of developing lung cancer. METHODS: We randomly selected 2 million participants from the Taiwan National Health Insurance Research Database who received care between 1999 and 2013. We built a predictive lung cancer screening model with neural networks that were trained and validated using pre-2012 data, and we tested the model prospectively on post-2012 data. An age- and gender-matched subgroup that was 10 times larger than the original lung cancer group was used to assess the predictive power of the electronic medical record. Discrimination (area under the receiver operating characteristic curve [AUC]) and calibration analyses were performed. RESULTS: The analysis included 11,617 patients with lung cancer and 1,423,154 control patients. The model achieved AUCs of 0.90 for the overall population and 0.87 in patients ≥55 years of age. The AUC in the matched subgroup was 0.82. The positive predictive value was highest (14.3%) among people aged ≥55 years with a pre-existing history of lung disease. CONCLUSIONS: Our model achieved excellent performance in predicting lung cancer within 1 year and has potential to be deployed for digital patient screening. Convolution neural networks facilitate the effective use of EMRs to identify individuals at high risk for developing lung cancer.