Proteomic Analysis of Spatial Heterogeneity Identifies HMGB2 as Putative Biomarker of Tumor Progression in Adult-Type Diffuse Astrocytomas.

Although grading is defined by the highest histological grade observed in a glioma, most high-grade gliomas retain areas with histology reminiscent of their low-grade counterparts. We sought to achieve the following: (i) identify proteins and molecular pathways involved in glioma evolution; and (ii) validate the high mobility group protein B2 (HMGB2) as a key player in tumor progression and as a prognostic/predictive biomarker for diffuse astrocytomas. We performed liquid chromatography tandem mass spectrometry (LC-MS/MS) in multiple areas of adult-type astrocytomas and validated our finding in multiplatform-omics studies and high-throughput IHC analysis. LC-MS/MSdetected proteomic signatures characterizing glioma evolution towards higher grades associated with, but not completely dependent, on IDH status. Spatial heterogeneity of diffuse astrocytomas was associated with dysregulation of specific molecular pathways, and HMGB2 was identified as a putative driver of tumor progression, and an early marker of worse overall survival in grades 2 and 3 diffuse gliomas, at least in part regulated by DNA methylation. In grade 4 astrocytomas, HMGB2 expression was strongly associated with proliferative activity and microvascular proliferation. Grounded in proteomic findings, our results showed that HMGB2 expression assessed by IHC detected early signs of tumor progression in grades 2 and 3 astrocytomas, as well as identified GBMs that had a better response to the standard chemoradiation with temozolomide.

Origin and significance of leucine-rich glioma-inactivated 1 antibodies in cerebrospinal fluid.

BACKGROUND: Whether antibodies against leucine-rich glioma-inactivated 1 (LGI1-Abs) in cerebrospinal fluid (CSF) are partially transferred from serum and the impact of CSF-LGI1-Ab positivity on clinical features and prognosis are unclear. Therefore, we aim to investigate the differences in serum titers, clinical features, and outcomes between LGI1-Ab CSF-positive and LGI1-Ab CSF-negative patients. METHODS: Retrospective analysis of serum titers and clinical features according to CSF LGI1-Ab status. In addition, univariate and multivariate logistic regression were performed to identify predictors of worse outcomes. RESULTS: A total of 60 patients with anti-LGI1 encephalitis and positive serum LGI1-Abs were identified, of whom 8 (13.3%) patients were excluded due to the absence of CSF LGI1-Ab testing. Among the remaining 52 patients, 33 (63.5%) were positive for LGI1-Abs in CSF. CSF-positive patients were more likely to have high serum titers (≥ 1:100) than CSF-negative patients (p = 0.003), and Spearman's correlation analysis showed a positive correlation between CSF and serum titers in CSF-positive patients (r2 = 0.405, p = 0.019). Psychiatric symptoms and hyponatremia were more frequent in CSF-positive patients (p < 0.05). Both univariate and multivariate logistic regression analyses showed that CSF LGI1-Ab positivity and delayed immunotherapy are independent risk factors for incomplete recovery (modified Rankin Scale (mRS) > 0 at last follow-up). CONCLUSIONS: LGI1-Ab CSF-positive patients have higher serum titers, and their CSF titers are positively correlated with serum titers, indicating a possible peripheral origin of CSF LGI1-Abs. CSF-positive patients more often present with psychiatric symptoms, hyponatremia, and worse outcomes, suggesting more severe neuronal damage.

Predictive value of persistent antibodies at 6 months for relapse in neuronal surface antibody-associated autoimmune encephalitis.

BACKGROUND: For patients with neuronal surface antibody-associated autoimmune encephalitis (NSAE) whose clinical symptoms gradually improve, the recommended course of immunotherapy in China is about 6 months. We aim to explore the relationship between persistent antibody positivity when immunotherapy is discontinued at 6 months and subsequent relapse. METHODS: Prospective inclusion of NSAE patients with clinical remission after 6-month immunotherapy. Their antibody titers and other clinical data were collected at onset and 6 months later. Based on the antibody test results at 6 months, patients were divided into an antibody-persistent group and an antibody-negative conversion group, and then the rate of relapse between the two groups were compared. RESULTS: The study included 28 NSAE patients who were antibody-positive at diagnosis. After 6-month immunotherapy, there were 16 (57.1%) cases with persistent antibodies and 12 (42.9%) cases with antibody-negative conversion. In the acute phase of onset, seizures were more common in patients with persistent antibodies (87.5% vs. 50.0%, p = 0.044). During a mean follow-up period of 22 months, patients with persistent antibodies were more likely to experience relapse than those with antibody-negative conversion (37.5% vs. 0.0%, p = 0.024). There were no significant differences in antibody types, CSF findings, results of MRI and EEG, tumor combination, immunotherapy, and long-term outcome between the two groups (p > 0.05). CONCLUSIONS: For patients with persistent antibodies when immunotherapy is discontinued at 6 months, persistent antibody positivity was associated with a higher relapse rate.

On the importance of working memory in the driving safety field: A systematic review.

In recent years, many studies have used poor cognitive functions to explain risk safety differences among drivers. Working memory is a cognitive function with information storage and attentional control that plays a crucial role in driver information processing. Furthermore, it is inextricably linked to parameters such as driving performance, driving eye movements and driving neurophysiology, which have a significant impact on drivers' risky behavior and crash risk. In particular, crash risk is a serious risk to social safety and economic development. For this reason, it is necessary to understand how risk-related working memory affects driving so that pre-driving safety pre-training programs and in-vehicle safety assistance systems for driving can be developed accordingly, contributing to the development of semi-autonomous vehicles and even autonomous vehicles. In this paper, a systematic search of the literature over the past 23 years resulted in 78 articles that met the eligibility criteria and quality assessment. The results show that higher working memory capacity, as measured neuropsychologically, is associated with more consistent and safer driving-related parameters for drivers (e.g., lane keeping) and may be related to pupil dilation during risk perception while driving, which is associated with driving outcomes (tickets, pull-overs, penalty points and fines,and driving accidents) is closely related to the perceived usefulness of the human-machine interface, reaction time, standard deviation of steering wheel corners, etc. when the autonomous driving takes over. In addition, higher working memory load interference was associated with more inconsistent and unsafe driving-related parameters (including but not limited to eye movements, electrophysiology, etc.), with higher working memory load being associated with easier driver concentration on the road, faster heart rate, lower heart rate variability, and lower oxyhemoglobin (OxyHb) and deoxyhemoglobin (DeoxyHb). Only a limited number of studies have simultaneously investigated the relationship between working memory capacity, working memory load and driving, showing an interaction between working memory capacity and working memory load on lane change initiation and lane change correctness, with working memory capacity acting as a covariate that mediated the effect of working memory load on braking reaction time. In addition, working memory-related cognitive training had a transfer effect on improving driving ability. Overall, working memory capacity determines the upper limit of the number of working memory attention resources, while working memory load occupies part of the working memory attention resources, thus influencing information perception, decision judgment, operational response, and collision avoidance in driving. Future effective interventions for safe driving can be combined with capacity training and load alerting. These findings contribute to our understanding of the role of working memory in driving and provide new insights into the design of driver safety training programs and automated driving personalized in-vehicle safety systems and roadside devices such as signage.

A study of safety acceptance and behavioral interventions for autonomous driving technologies.

Explaining the phenomenon of declining acceptance of automated driving technology (ADT) and predicting trends in acceptance has become an important area of research. To explore the reasons for the decline in acceptance of automated vehicles and how to improve user acceptance, we studied mechanisms of the influence process from the relationship between safety riskiness of ADT and user acceptance, and examined the mediating and moderating effects of the proposed intervention behaviors on the influence relationship between these two. First, an improved acceptance model incorporating safety risk factors was developed. Subsequently, the psychological change process of user acceptance was analyzed based on people's response to accident information. Ultimately, the results show that safety cognition risk regarding ADT has a significant negative impact on user acceptance. Next, the mediating model where user experience was introduced as a moderating variable was designed. From the test results of this model, it is found that the proposed behavioral intervention strategy is effective in attenuating the degree of impact of the safety riskiness of ADT on acceptance. The risk-based acceptance explanation model and intervention method designed in this study provide a scientific basis and practical approach to develop the market for automated vehicles.

An oversampling method for multi-class imbalanced data based on composite weights.

To solve the oversampling problem of multi-class small samples and to improve their classification accuracy, we develop an oversampling method based on classification ranking and weight setting. The designed oversampling algorithm sorts the data within each class of dataset according to the distance from original data to the hyperplane. Furthermore, iterative sampling is performed within the class and inter-class sampling is adopted at the boundaries of adjacent classes according to the sampling weight composed of data density and data sorting. Finally, information assignment is performed on all newly generated sampling data. The training and testing experiments of the algorithm are conducted by using the UCI imbalanced datasets, and the established composite metrics are used to evaluate the performance of the proposed algorithm and other algorithms in comprehensive evaluation method. The results show that the proposed algorithm makes the multi-class imbalanced data balanced in terms of quantity, and the newly generated data maintain the distribution characteristics and information properties of the original samples. Moreover, compared with other algorithms such as SMOTE and SVMOM, the proposed algorithm has reached a higher classification accuracy of about 90%. It is concluded that this algorithm has high practicability and general characteristics for imbalanced multi-class samples.

Analysis of Pedestrian Street-Crossing Decision-Making Based on Vehicle Deceleration-Safety Gap.

Numerous traffic crashes occur every year on zebra crossings in China. Pedestrians are vulnerable road users who are usually injured severely or fatally during human-vehicle collisions. The development of an effective pedestrian street-crossing decision-making model is essential to improving pedestrian street-crossing safety. For this purpose, this paper carried out a naturalistic field experiment to collect a large number of vehicle and pedestrian motion data. Through interviewed with many pedestrians, it is found that they pay more attention to whether the driver can safely brake the vehicle before reaching the zebra crossing. Therefore, this work established a novel decision-making model based on the vehicle deceleration-safety gap (VD-SGM). The deceleration threshold of VD-SGM was determined based on signal detection theory (SDT). To verify the performance of VD-SGM proposed in this work, the model was compared with the Raff model. The results show that the VD-SGM performs better and the false alarm rate is lower. The VD-SGM proposed in this work is of great significance to improve pedestrians' safety. Meanwhile, the model can also increase the efficiency of autonomous vehicles.

Linking executive functions to distracted driving, does it differ between young and mature drivers?

Distracted driving is a leading cause of traffic accidents. Certain executive functions significantly affect the willingness of distracted driving; however, little research has compared the effects of executive functions on distracted driving behaviors in different aged populations. This study explores and compares the behavioral and cognitive processes underlying distracted driving behaviors in young and mature drivers. A total of 138 participants aged 18-65 years old completed a self-report questionnaire for measuring executive function index and distracted driving behaviors. Independent sample t-tests were conducted for executive functions (motivational drive, organization, strategic planning, impulse control, and empathy) and driving variables to examine any differences between young and mature groups. Partial correlation coefficients and z-score of these comparisons were calculated to compare the differences between age groups. Furthermore, multiple hierarchical regression models were constructed to determine the relative contributions of age, gender, and executive functions on distracted driving behaviors. Results demonstrated the following: (1) Mature drivers performed better for impulse control, the executive function index as well as the measure of distracted driving behavior than young drivers; (2) the relationships between executive functions and distracted driving behaviors did not significantly differ between young and mature drivers; (3) for both young and mature drivers, motivational drive and impulse control were found to significantly improve the prediction of distracted driving behavior in regression models. The findings emphasize that similar behavioral and cognitive processes are involved in distracted driving behavior of young and mature drivers, and can promote a single strategy for driver education and accident prevention interventions for both age groups.

Research on a Cognitive Distraction Recognition Model for Intelligent Driving Systems Based on Real Vehicle Experiments.

The accurate and prompt recognition of a driver's cognitive distraction state is of great significance to intelligent driving systems (IDSs) and human-autonomous collaboration systems (HACSs). Once the driver's distraction status has been accurately identified, the IDS or HACS can actively intervene or take control of the vehicle, thereby avoiding the safety hazards caused by distracted driving. However, few studies have considered the time-frequency characteristics of the driving behavior and vehicle status during distracted driving for the establishment of a recognition model. This study seeks to exploit a recognition model of cognitive distraction driving according to the time-frequency analysis of the characteristic parameters. Therefore, an on-road experiment was implemented to measure the relative parameters under both normal and distracted driving via a test vehicle equipped with multiple sensors. Wavelet packet analysis was used to extract the time-frequency characteristics, and 21 pivotal features were determined as the input of the training model. Finally, a bidirectional long short-term memory network (Bi-LSTM) combined with an attention mechanism (Atten-BiLSTM) was proposed and trained. The results indicate that, compared with the support vector machine (SVM) model and the long short-term memory network (LSTM) model, the proposed model achieved the highest recognition accuracy (90.64%) for cognitive distraction under the time window setting of 5 s. The determination of time-frequency characteristic parameters and the more accurate recognition of cognitive distraction driving achieved in this work provide a foundation for human-centered intelligent vehicles.

Human-Like Obstacle Avoidance Trajectory Planning and Tracking Model for Autonomous Vehicles That Considers the River's Operation Characteristics.

Developing a human-like autonomous driving system has gained increasing amounts of attention from both technology companies and academic institutions, as it can improve the interpretability and acceptance of the autonomous system. Planning a safe and human-like obstacle avoidance trajectory is one of the critical issues for the development of autonomous vehicles (AVs). However, when designing automatic obstacle avoidance systems, few studies have focused on the obstacle avoidance characteristics of human drivers. This paper aims to develop an obstacle avoidance trajectory planning and trajectory tracking model for AVs that is consistent with the characteristics of human drivers' obstacle avoidance trajectory. Therefore, a modified artificial potential field (APF) model was established by adding a road boundary repulsive potential field and ameliorating the obstacle repulsive potential field based on the traditional APF model. The model predictive control (MPC) algorithm was combined with the APF model to make the planning model satisfy the kinematic constraints of the vehicle. In addition, a human driver's obstacle avoidance experiment was implemented based on a six-degree-of-freedom driving simulator equipped with multiple sensors to obtain the drivers' operation characteristics and provide a basis for parameter confirmation of the planning model. Then, a linear time-varying MPC algorithm was employed to construct the trajectory tracking model. Finally, a co-simulation model based on CarSim/Simulink was established for off-line simulation testing, and the results indicated that the proposed trajectory planning controller and the trajectory tracking controller were more human-like under the premise of ensuring the safety and comfort of the obstacle avoidance operation, providing a foundation for the development of AVs.

Research on the Influence of Vehicle Speed on Safety Warning Algorithm: A Lane Change Warning System Case Study.

Speed has an important impact on driving safety, however, this factor is not included in existing safety warning algorithms. This study uses lane change systems to study the influence of vehicle speed on safety warning algorithms, aiming to determine lane change warning rules for different speeds (DS-LCW). Thirty-five drivers are recruited to carry out an extreme trial and naturalistic driving experiment. The vehicle speed, relative speed, relative distance, and minimum safety deceleration (MSD) related to lane change characteristics are then analyzed and calculated as warning rule characterization parameters. Lane change warning rules for a rear vehicle in the target lane under four-speed levels of 60 ≤ v < 70 km/h, 70 ≤ v < 80 km/h, 80 ≤ v < 90 km/h, and v ≥ 90 km/h are established. The accuracy of lane change warning rules not considering speed level (NDS-LCW) and ISO 17387 are found to be 87.5% and 79.8%, respectively. Comparatively, the accuracy rate of DS-LCW under four-speed levels is 94.6%, 93.8%, 90.0%, and 92.6%, respectively, which is significantly superior. The algorithm proposed in this paper provides warning in the lane change process with a smaller relative distance, and the accuracy rate of DS-LCW is significantly superior to NDS-LCW and ISO 17387.

What is the difference in driver's lateral control ability during naturalistic distracted driving and normal driving? A case study on a real highway.

Driver distraction is widely recognized as a major contributor to traffic crashes. Although the effect of distraction on simulated driving performance has been studied extensively, comparatively little research based on field tests has been performed on the effects of high driving speeds on lateral driving performance during naturalistic distraction (the driver was unaware of the research topic). In this study, an instrumented vehicle is used to examine the impact of speed and naturalistic visual distraction (rear vehicle's velocity and relative distance estimation) on a driver's ability to keep in the lane. Similar to results from previous studies, visual distraction resulted in an impaired ability to keep in a lane compared to normal driving. Further investigation of steering control parameters showed an increase in steering wheel reversal rates (SRRs at 1.3° and 2.5° levels) and the standard deviation of steering wheel acceleration (SDSWA). The results of this study indicated that the standard deviation of lane positioning (SDLP) and trajectory offset (TO) increased as speed increased. As speed increased, the growth rates of SDLP and TO in the visual distraction task were the same as that in normal driving. Moreover, the SRRs and steering wheel acceleration (SWA) decreased with increased speed. As speed increased, the growth rates of SRRs and SWA during a visual distraction task were the same as that during normal driving. These results suggest that driving speed has a similar effect on driving performance during both distracted driving and normal driving.

The association of medication use with clearance or persistence of oral HPV infection.

PURPOSE: Persistent oral human papillomavirus (HPV) infection increases risk for oropharyngeal carcinoma, and people living with HIV have higher rates of oral HPV infection and related cancers. Some prescription medications have immunomodulatory effects, but the impact of medication use on oral HPV natural history is unknown. METHODS: Scope® oral rinse-and-gargle samples were collected semi-annually from 1,666 participants and tested for 37 types of oral HPV DNA using PCR; 594 HPV-infected participants with 1,358 type-specific oral HPV infections were identified. Data were collected on recent (past 6 months) use of medications. The relationship between medication use and oral HPV clearance was evaluated using Wei-Lin-Weissfeld regression, adjusting for biologic sex, prevalent versus incident infection, age, HIV status and CD4+ T cell count. RESULTS: Out of 11 medications examined, oral HPV clearance was significantly reduced in participants reporting recent use of antipsychotics (HR 0.75, 95% CI 0.57-0.99), anxiolytics/sedatives (HR 0.78, 95% CI 0.63-0.96) and antidepressants (HR 0.82, 95% CI 0.67-0.999). Among antipsychotics users, effect modification by HIV status was observed, with reduced clearance in HIV-infected (HR 0.67, 95% CI 0.49-0.91), but not HIV-uninfected participants (p-interaction = 0.009). After adjusted analysis, antipsychotic use remained significantly associated with reduced oral HPV clearance overall (aHR 0.75, 95% CI 0.57-0.99), and when restricted to only HIV-infected participants (aHR 0.66, 95% CI 0.48-0.90). After adjustment, anxiolytic/sedative use and antidepressant use were no longer significantly associated with reduced oral HPV clearance. CONCLUSIONS: Some medications were associated with decreased oral HPV clearance, most notably antipsychotic medications. These medications are prescribed for conditions that may have immunomodulating effects, so characteristics of underlying illness may have partially contributed to reduced oral HPV clearance.

Association of serum cytokines with oral HPV clearance.

BACKGROUND: Initial studies suggest higher serum levels of some pro-inflammatory cytokines may be associated with decreased cervical human papillomavirus (HPV) clearance. However, the relationship of cytokines with oral HPV clearance has not been explored. METHODS: From 2010 to 2014, oral rinse and serum samples were collected semi-annually from 1601 adults. Oral rinse samples were tested for HPV DNA using PCR. Based on oral HPV results, 931 serum samples were selected for cytokine evaluation to include a roughly equal number of prevalent (n=307), incident (n=313), and no oral HPV infections (n=311). Electrochemiluminescence multiplex assays were used to determine the concentrations of IL-6, IL-8, TNF-α, IFN-γ, IL-1ß, IL-2, IL-4, IL-10, IL-12 and IL-13. The relationship between serum cytokine concentrations (categorized into quartiles) and oral HPV clearance was evaluated with Wei-Lin-Weissfeld regression models, adjusting for HPV infection type (prevalent vs. incident), age, HIV status, and CD4 T cell count. RESULTS: Higher TNF-α concentration was associated with decreased clearance in men (highest vs. lowest quartile, adjusted hazard ratio [aHR]=0.52, 95% CI=0.34-0.79) and women (aHR=0.76, 95% confidence interval [CI]=0.55-1.04), with stronger associations in men than women (p-interaction=0.049). Higher IL-2 concentration was associated with reduced clearance in men (aHR=0.69, 95% CI=0.50-0.95), but not women (p-interaction=0.058). Results were similar within CD4 T cell strata (CD4⩾500 or CD4<500 cells/µl) among HIV-infected participants. No other cytokines were associated with clearance. CONCLUSION: High serum TNF-α is associated with reduced clearance of oral HPV infection.

Sex Differences in Risk Factors and Natural History of Oral Human Papillomavirus Infection.

UNLABELLED: Oral human papillomavirus genotype 16 (HPV16) infection causes oropharyngeal squamous cell carcinoma (SCC), and the prevalence of oropharyngeal SCC is higher among men than women in the United States. In a cohort study of oral HPV infection among 409 individuals aged 18-25 years, the risk among men but not among women significantly increased as the number of recent (ie, within the prior 3 months) oral sex partners increased (Pinteraction = .05). In contrast, the risk among women but not among men significantly decreased as the lifetime number of vaginal sex partners increased (Pinteraction = .037). Men were also significantly less likely than women to clear oral HPV infection. Our data contribute to understanding sex differences in risk for HPV-positive oropharyngeal SCC. CLINICAL TRIALS REGISTRATION: NCT00994019.

Prevalence of and Risk Factors for Oral Human Papillomavirus Infection among HIV-Positive and HIV-Negative People Who Inject Drugs.

BACKGROUND: Human papillomavirus (HPV) causes most oropharyngeal cancers in the United States. Oral HPV prevalence is associated with immunosuppression, and drug use can be immunosuppressive, but the epidemiology of oral HPV among people who use drugs is not well described. METHODS: We enrolled men and women with a current or prior history of injection drug use in this cross-sectional sub-study within the AIDS Linked to the Intravenous Experience (ALIVE) cohort. We tested oral rinse samples for 37 types of HPV DNA and collected self-reported risk factor information. We compared oral HPV prevalence across categories using chi-squared statistics and multivariable logistic regression. RESULTS: Among 199 subjects, 32% were HIV-positive (median CD4 count 384 cells/µL), 90% were Black, 56% had less than a high school education, 17% had recently used injection drugs, and the median age was 54 years. Most had performed oral sex (82%) but had fewer than 5 lifetime partners (58%). The prevalence of any oral HPV was 29%, and of any oncogenic oral HPV was 13%. Oral HPV prevalence was high among both heterosexual men (30%) and women (20%). After adjustment, odds of oral HPV were increased among HIV-positive individuals with a low CD4 count (<350 cells/µl, aOR = 2.7, 95%CI = 1.2-6.4, vs. HIV-negative individuals), but not among HIV-positive individuals with a higher CD4 cell count. Odds were also elevated for those who had recently performed oral sex on a woman (aOR = 2.2, 95%CI = 1.01-4.6) and, even after this adjustment, among bisexual/lesbian females (aOR = 5.6, 95%CI = 1.4-23, vs. heterosexual females). Oral HPV prevalence was not associated with vaginal sex, performing oral sex on a man, or recent drug use. CONCLUSIONS: Recent drug use was not associated with oral HPV prevalence in our study. However, despite modest numbers of sexual partners, the prevalence of oral HPV among this largely Black population with lower socioeconomic status was high.

Prognostic Implication of Persistent Human Papillomavirus Type 16 DNA Detection in Oral Rinses for Human Papillomavirus-Related Oropharyngeal Carcinoma.

IMPORTANCE: Human papillomavirus-related oropharyngeal carcinoma (HPV-OPC) is increasing in incidence in the United States. Although HPV-OPC has favorable prognosis, 10% to 25% of HPV-OPCs recur. Detection of human papillomavirus (HPV) DNA in oral rinses is associated with HPV-OPC, but its potential as a prognostic biomarker is unclear. OBJECTIVE: To determine whether HPV DNA detection in oral rinses after treatment for HPV-OPC is associated with recurrence and survival. DESIGN, SETTING, AND PARTICIPANTS: Prospective cohort study of patients with incident HPV-OPC diagnosed from 2009 to 2013 at 4 academic tertiary referral cancer centers in the United States. Oral rinse samples were collected at diagnosis and after treatment (9, 12, 18, and 24 months after diagnosis), and evaluated for HPV DNA. Among an initial cohort of 157 participants with incident HPV-OPC treated with curative intent, 124 had 1 or more posttreatment oral rinses available and were included in this study. MAIN OUTCOMES AND MEASURES: Disease-free survival (DFS) and overall survival (OS) were estimated by the Kaplan-Meier method, and the association of HPV DNA detection in oral rinses with survival was evaluated using Cox regression analysis. RESULTS: Oral HPV type 16 (HPV16) DNA was common at diagnosis (67 of 124 participants [54%]). In contrast, oral HPV16 DNA was detected in only 6 participants after treatment (5%), including 5 with HPV16 DNA also detected at diagnosis (persistent oral HPV16 DNA). Two-year DFS and OS were 92% (95% CI, 94%-100%) and 98% (95% CI, 93%-99%). Persistent oral HPV16 DNA was associated with worse DFS (hazard ratio, 29.7 [95% CI, 9.0-98.2]) and OS (hazard ratio, 23.5 [95% CI, 4.7-116.9]). All 5 participants with persistent oral HPV16 DNA developed recurrent disease, 3 with local disease involvement. In contrast, just 9 of 119 participants (8%) without persistent oral HPV16 DNA developed recurrent disease, only 1 (11%) with local disease involvement. Median (range) time from earliest posttreatment oral HPV16 DNA detection to recurrence was 7.0 (3.7-10.9) months. CONCLUSIONS AND RELEVANCE: Human papillomavirus type 16 DNA in oral rinses is common at diagnosis but rare after treatment for HPV-OPC. Our data suggest that, although infrequent, persistent HPV16 DNA in posttreatment oral rinses is associated with poor prognosis and is a potential tool for long-term tumor surveillance, perhaps more so for local recurrence.

High Oral Human Papillomavirus Type 16 Load Predicts Long-term Persistence in Individuals With or at Risk for HIV Infection.

The association between oral human papillomavirus 16 (HPV16) DNA load and infection clearance was evaluated among 88 individuals with oral HPV16 infection who were identified within a prospective cohort of 1470 HIV-infected and uninfected individuals. Oral rinse specimens were collected semiannually for up to 5 years. The oral HPV16 load at the time of the first positive test result was significantly associated with the time to clearance of infection (continuous P trends <.01). Notably, clearance rates by 24 months were 41% and 94% in the highest and lowest HPV16 load tertiles (P = .03), respectively. High oral HPV16 load warrants consideration as a biomarker for infection persistence, the presumed precursor of HPV16-associated oropharyngeal cancer.

Multi-parameter prediction of drivers' lane-changing behaviour with neural network model.

Accurate prediction of driving behaviour is essential for an active safety system to ensure driver safety. A model for predicting lane-changing behaviour is developed from the results of naturalistic on-road experiment for use in a lane-changing assistance system. Lane changing intent time window is determined via visual characteristics extraction of rearview mirrors. A prediction index system for left lane changes was constructed by considering drivers' visual search behaviours, vehicle operation behaviours, vehicle motion states, and driving conditions. A back-propagation neural network model was developed to predict lane-changing behaviour. The lane-change-intent time window is approximately 5 s long, depending on the subjects. The proposed model can accurately predict drivers' lane changing behaviour for at least 1.5 s in advance. The accuracy and time series characteristics of the model are superior to the use of turn signals in predicting lane-changing behaviour.

Risk factors for acquisition and clearance of oral human papillomavirus infection among HIV-infected and HIV-uninfected adults.

Human papillomavirus (HPV) causes the majority of oropharyngeal cancers in the United States, yet the risk factors for and natural history of oral HPV infection are largely unknown. In 2010-2011, a US-based longitudinal cohort study of 761 human immunodeficiency virus (HIV)-infected and 469 at-risk HIV-uninfected participants from the Multicenter AIDS Cohort Study and the Women's Interagency HIV Study was initiated. Semiannually collected oral rinses were evaluated for 37 HPV genotypes using the Roche LINEAR ARRAY HPV Genotyping Test (Roche Molecular Systems, Pleasanton, California), and factors associated with oral HPV incidence and clearance were explored using adjusted Wei-Lin-Weissfeld modeling. Through 2013, the 2-year cumulative incidence of any type of oral HPV infection was 34% in HIV-infected persons and 19% in HIV-uninfected persons. However, many of these infections cleared. Seven percent of incident infections and 35% of prevalent infections persisted for at least 2 years. After adjustment for other risk factors, HIV infection (adjusted hazard ratio = 2.3, 95% confidence interval: 1.7, 3.2), reduced current CD4 cell count, and increased numbers of oral sex and "rimming" partners increased the risk of incident oral HPV infection, whereas male sex, older age, and current smoking increased the risk of oral HPV persistence (each P < 0.05). This helps explain the consistent associations observed between these factors and prevalent oral HPV infection in previous cross-sectional studies.