Miracle-dz/UniFAR-FTUs huggingface dataset:
Catch-up HPV Vaccination and Subsequent Uptake of Papanicolaou Testing in A State-mandated Health System

We found that catch-up HPV vaccination was associated with increased attention to long-term cervical screening attendance. Whereas, those who are not vaccinated and unprotected from HPV, are more likely to abstain from secondary prevention screening tests too and further increase their cervical cancer risk. The objective of this study was to evaluate the association between human papillomavirus (HPV) vaccination and uptake of initial Papanicolaou (Pap) testing in Israel among women not previously vaccinated through the national immunization program. In this retrospective cohort we used health provider records of vaccinations and cancer screening attendance among female members of a state-mandated health provider in Israel (Maccabi Healthcare Services, MHS). All eligible female members (N = 20,904) immunized with at least one dose of HPV vaccine from the date of its introduction in Israel (June 2007) until December 31, 2018 were individually matched with nonvaccinated MHS members on one to one ratio by year of birth, residential area socioeconomic level, and district of residence. Data on the uptake of Pap smears until December 2018 were extracted from MHS central datasets, and the number of Pap smears for each woman during the study period was counted. During the observed follow-up period (mean, 6.6 years; interquartile range, 3.9–8.7 year), the cumulative uptake rate of Pap testing in vaccinated women (26.8%) was significantly (P < 0.001) greater than among unvaccinated (22.4%) women. In a multivariable model, HPV vaccination was associated with an HR of 1.34 [95% confidence interval (CI), 1.29–1.41] to perform Pap testing. Our findings suggest that uptake of catch-up HPV vaccine was positively correlated to increased uptake of Pap testing. Prevention Relevance: We found that catch-up HPV vaccination was associated with increased attention to long-term cervical screening attendance. Whereas, those who are not vaccinated and unprotected from HPV, are more likely to abstain from secondary prevention screening tests too and further increase their cervical cancer risk.
Hormone receptor 4 is required in muscles and distinct ovarian cell types to regulate specific steps of Drosophila oogenesis

ABSTRACT The conserved nuclear receptor superfamily has crucial roles in many processes, including reproduction. Nuclear receptors with known roles in oogenesis have been studied mostly in the context of their ovary-intrinsic requirement. Recent studies in Drosophila, however, have begun to reveal new roles of nuclear receptor signaling in peripheral tissues in controlling reproduction. Here, we identified Hormone receptor 4 (Hr4) as an oogenesis regulator required in the ovary and muscles. Global Hr4 knockdown leads to increased germline stem cell (GSC) loss, reduced GSC proliferation, early germline cyst death, slowed follicle growth and vitellogenic follicle degeneration. Tissue-specific knockdown experiments uncovered ovary-intrinsic and peripheral tissue requirements for Hr4. In the ovary, Hr4 is required in the niche for GSC proliferation and in the germline for GSC maintenance. Hr4 functions in muscles to promote GSC maintenance and follicle growth. The specific tissues that require Hr4 for survival of early germline cysts and vitellogenic follicles remain unidentified. These results add to the few examples of muscles controlling gametogenesis and expand our understanding of the complexity of nuclear receptor regulation of various aspects of oogenesis. Highlighted Article: The nuclear receptor Hr4 is required in muscles and the ovary to control specific steps of oogenesis in adult Drosophila.
Picrosirius‐Polarization Method for Collagen Fiber Detection in Tendons: A Mini‐Review

Although the structure and composition of collagen have been studied by polarized light microscopy since the early 19th century, many studies and reviews have paid little or no attention to the morphological problems of histopathological diagnosis. The morphology of collagen fibers is critical in guiding mechanical and biological properties in both normal and pathological tendons. Highlighting the organization and spatial distribution of tendon‐containing collagen fibers can be very useful for visualizing a tendon's ultrastructure, biochemical and indirect mechanical properties, which benefits other researchers and clinicians. Picrosirius red (PSR) staining, relying on the birefringence of collagen fibers, is one of the best understood histochemical methods that can highly and specifically underline fibers better than other common staining techniques when combined with polarized light microscopy (PLM). Polarized light microscopy provides complementary information about collagen fibers, such as orientation, type and spatial distribution, which is important for a comprehensive assessment of collagen alteration in a tendon. Here, this brief review serves as a simplistic and important primer to research developments in which differential staining of collagen types by the Picrosirius‐polarization method is increasing in diverse studies of the medical field, mainly in the assessment of the morphology, spatial distribution, and content of collagen in tendons.
Response to “Comment on ‘A Quantile-Based g-Computation Approach to Addressing the Effects of Exposure Mixtures’”

Alexander P. Keil,1,2 Jessie P. Buckley,3,4 Katie M. O’Brien,2 Kelly K. Ferguson,2 Shanshan Zhao,5 and Alexandra J. White2 Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA Epidemiology Branch, National Institute of Environmental Health Sciences (NIEHS), National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Research Triangle Park, North Carolina, USA Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, Maryland, USA Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland, USA Biostatistics Branch, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, USA
Investigating the effects of driving environment and driver characteristics on drivers’ compliance with speed limits

Abstract Objective Speed compliance of drivers plays a significant role in influencing crash risks, and remains a major road safety issue. Majority of the speed compliance behavioral studies have been conducted in the western world; relatively little knowledge is available about the speed compliance of the drivers of developing nations. The present study aims to investigate the speed compliance behavior of Indian drivers in changing driving environment, and to identify the significant predictors influencing their speed compliance. Method The driving scenario (consisting of rural and urban driving environments) representing heterogenous Indian driving conditions was designed on a driving simulator where eighty-two licensed drivers completed the driving task. Driver attributes (demographics and driving characteristics) were recorded with the help of a self-reported questionnaire. Speed compliance of drivers was estimated as an indication of the difference of driving speed from the posted speed limit of a particular driving environment, averaged over the duration of driving. The low speed difference indicated better speed compliance of drivers and vice-versa. A Generalized Linear Model (GLM) was developed using speed difference as the dependent variable along with driving environments and driver attributes as predictor variables. Results Speed compliance of drivers was found to be better in urban driving environment compared to rural driving environment, indicating that drivers were less able to adapt to the corresponding speed limits in rural environment. Drivers’ age was positively associated with the speed compliance. For male drivers, speed compliance was found to be lower than the female drivers. Compared to the drivers who studied till their secondary education, speed compliances of post-graduate and graduate drivers were found to be better. Moreover, driving experience was observed as a negative predictor of speed compliance. Drivers who had prior crash history were found to have better speed compliance compared to the other drivers. Other predictors such as vehicle type and preferred time of driving did not show any significant influence on the speed compliance of drivers. Conclusion This is the first exploratory study which investigated the speed compliance behavior of Indian drivers. Findings of the present study may assist the road safety strategies and policy interventions in reducing the speed-related crashes.
Part-Level Car Parsing and Reconstruction in Single Street View Images

Part information has been proven to be resistant to occlusions and viewpoint changes, which are main difficulties in car parsing and reconstruction. However, in the absence of datasets and approaches incorporating car parts, there are limited works that benefit from it. In this paper, we propose the first part-aware approach for joint part-level car parsing and reconstruction in single street view images. Without labor-intensive part annotations on real images, our approach simultaneously estimates pose, shape, and semantic parts of cars. There are two contributions in this paper. First, our network introduces dense part information to facilitate pose and shape estimation, which is further optimized with a novel 3D loss. To obtain part information in real images, a class-consistent method is introduced to implicitly transfer part knowledge from synthesized images. Second, we construct the first high-quality dataset containing 348 car models with physical dimensions and part annotations. Given these models, 60K synthesized images with randomized configurations are generated. Experimental results demonstrate that part knowledge can be effectively transferred with our class-consistent method, which significantly improves part segmentation performance on real street views. By fusing dense part information, our pose and shape estimation results achieve the state-of-the-art performance on the ApolloCar3D and outperform previous approaches by large margins in terms of both A3DP-Abs and A3DP-Rel.
Cell-Associated HIV-1 Unspliced-to-Multiply-Spliced RNA Ratio at 12 Weeks of ART Predicts Immune Reconstitution on Therapy

Human immunodeficiency virus (HIV) infection is currently managed by antiretroviral drugs, which block virus replication and promote immune restoration. However, the latter effect is not universal, with a proportion of infected individuals failing to sufficiently reconstitute their immune function despite a successful virological response to antiretroviral therapy (ART). ABSTRACT Incomplete restoration of CD4+ T-cell counts on antiretroviral therapy (ART) is a major predictor of HIV-related morbidity and mortality. To understand the possible mechanisms behind this poor immunological response despite viral suppression, we longitudinally measured more than 50 virological and immunological biomarkers in a cohort of HIV-infected individuals at several time points during the first 96 weeks of virologically suppressive ART. No baseline virological or immunological marker was predictive of the degree of immune reconstitution. However, the cell-associated HIV-1 unspliced-to-multiply-spliced (US/MS) RNA ratio at 12 weeks of ART positively correlated with markers of CD4+ T-cell activation and apoptosis and negatively predicted both the absolute and relative CD4+ T-cell counts at 48 and 96 weeks. A higher US/MS RNA ratio may reflect the higher frequency of productively infected cells that could exert pressure on the immune system, contributing to persistent immune activation and apoptosis and subsequently to a poor immunological response to ART. IMPORTANCE Human immunodeficiency virus (HIV) infection is currently managed by antiretroviral drugs, which block virus replication and promote immune restoration. However, the latter effect is not universal, with a proportion of infected individuals failing to sufficiently reconstitute their immune function despite a successful virological response to antiretroviral therapy (ART). No reliable predictive markers of immunological failure have been identified, and there is still no efficient therapeutic strategy, apart from ART itself, to facilitate immune reconstitution. Here, we measured more than 50 viral and host biomarkers at five time points during the first 2 years of ART and identified the cell-associated HIV-1 unspliced-to-multiply-spliced RNA ratio at 12 weeks of ART as a predictive factor for the immunological response to therapy. Moreover, the same marker positively correlated with markers of CD4+ T-cell activation and apoptosis. The fact that a virological biomarker performed better than any immunological biomarker in predicting an immunological outcome highlights the importance of considering the residual HIV activity on ART as a correlate and a possible cause of the residual immune dysfunction that frequently occurs despite virologically suppressive ART.
Image‐guided robots for low dose rate prostate brachytherapy: Perspectives on safety in design and use

Image‐guided brachytherapy (BT) robots can be used to assist urologists during seed implantation, thereby improving therapeutic effects. However, safety issues must be considered in the design of such robots, including their structure, mechanical movements, function, materials and actuators. Previous reviews focused on image‐guided prostate BT robot technology (e.g., imaging and robot navigation technology and robot system introduction); however, this review is the first time that safety issues have been investigated as part of a study on low‐dose‐rate (LDR) prostate BT robots.
Population Coding of Natural Electrosensory Stimuli by Midbrain Neurons

Natural stimuli display spatiotemporal characteristics that typically vary over orders of magnitude, and their encoding by sensory neurons remains poorly understood. We investigated population coding of highly heterogeneous natural electrocommunication stimuli in Apteronotus leptorhynchus of either sex. Neuronal activities were positively correlated with one another in the absence of stimulation, and correlation magnitude decayed with increasing distance between recording sites. Under stimulation, we found that correlations between trial-averaged neuronal responses (i.e., signal correlations) were positive and higher in magnitude for neurons located close to another, but that correlations between the trial-to-trial variability (i.e., noise correlations) were independent of physical distance. Overall, signal and noise correlations were independent of stimulus waveform as well as of one another. To investigate how neuronal populations encoded natural electrocommunication stimuli, we considered a nonlinear decoder for which the activities were combined. Decoding performance was best for a timescale of 6 ms, indicating that midbrain neurons transmit information via precise spike timing. A simple summation of neuronal activities (equally weighted sum) revealed that noise correlations limited decoding performance by introducing redundancy. Using an evolution algorithm to optimize performance when considering instead unequally weighted sums of neuronal activities revealed much greater performance values, indicating that midbrain neuron populations transmit information that reliably enable discrimination between different stimulus waveforms. Interestingly, we found that different weight combinations gave rise to similar discriminability, suggesting robustness. Our results have important implications for understanding how natural stimuli are integrated by downstream brain areas to give rise to behavioral responses. SIGNIFICANCE STATEMENT We show that midbrain electrosensory neurons display correlations between their activities and that these can significantly impact performance of decoders. While noise correlations limited discrimination performance by introducing redundancy, considering unequally weighted sums of neuronal activities gave rise to much improved performance and mitigated the deleterious effects of noise correlations. Further analysis revealed that increased discriminability was achieved by making trial-averaged responses more separable, as well as by reducing trial-to-trial variability by eliminating noise correlations. We further found that multiple combinations of weights could give rise to similar discrimination performances, which suggests that such combinatorial codes could be achieved in the brain. We conclude that the activities of midbrain neuronal populations can be used to reliably discriminate between highly heterogeneous stimulus waveforms.
Engineered SARS-CoV-2 receptor binding domain improves immunogenicity in mice and elicits protective immunity in hamsters

Global containment of COVID-19 still requires accessible and affordable vaccines for low- and middle-income countries (LMICs). 1 Recently approved vaccines provide needed interventions, albeit at prices that may limit their global access.2 Subunit vaccines based on recombinant proteins are suited for large-volume microbial manufacturing to yield billions of doses annually, minimizing their manufacturing costs.3 These types of vaccines are well-established, proven interventions with multiple safe and efficacious commercial examples.4–6 Many vaccine candidates of this type for SARS-CoV-2 rely on sequences containing the receptor-binding domain (RBD), which mediates viral entry to cells via ACE2.7,8 Here we report an engineered sequence variant of RBD that exhibits high-yield manufacturability, high-affinity binding to ACE2, and enhanced immunogenicity after a single dose in mice compared to the Wuhan-Hu-1 variant used in current vaccines. Antibodies raised against the engineered protein exhibited heterotypic binding to the RBD from two recently reported SARS-CoV-2 variants of concern (501Y.V1/V2). Presentation of the engineered RBD on a designed virus-like particle (VLP) also reduced weight loss in hamsters upon viral challenge.
Online Mindfulness-Based Cognitive Behavioral Therapy Intervention for Youth With Major Depressive Disorders: Randomized Controlled Trial

Background Approximately 70% of mental health disorders appear prior to 25 years of age and can become chronic when ineffectively treated. Individuals between 18 and 25 years old are significantly more likely to experience mental health disorders, substance dependencies, and suicidality. Treatment progress, capitalizing on the tendencies of youth to communicate online, can strategically address depressive disorders. Objective We performed a randomized controlled trial (RCT) that compared online mindfulness-based cognitive behavioral therapy (CBT-M) combined with standard psychiatric care to standard psychiatric care alone in youth (18-30 years old) diagnosed with major depressive disorder. Methods Forty-five participants were randomly assigned to CBT-M and standard care (n=22) or to standard psychiatric care alone (n=23). All participants were provided standard psychiatric care (ie, 1 session per month), while participants in the experimental group received an additional intervention consisting of the CBT-M online software program. Interaction with online workbooks was combined with navigation coaching delivered by phone and secure text messaging. Results In a two-level linear mixed-effects model intention-to-treat analysis, significant between-group differences were found for the Beck Depression Inventory-II score (difference –8.54, P=.01), Quick Inventory of Depressive Symptoms score (difference –4.94, P=.001), Beck Anxiety Inventory score (difference –11.29, P<.001), and Brief Pain Inventory score (difference –1.99, P=.03), while marginal differences were found for the Five Facet Mindfulness Questionnaire–Nonjudging subscale (difference –2.68, P=.05). Conclusions These results confirm that youth depression can be effectively treated with online CBT-M that can be delivered with less geographic restriction. Trial Registration Clinical Trials.gov NCT03406052; https://www.clinicaltrials. gov/ct2/show/NCT03406052
DTexFusion: Dynamic Texture Fusion Using a Consumer RGBD Sensor

In addition to 3D geometry, accurate representation of texture is important when digitizing real objects in virtual worlds. Based on a single consumer RGBD sensor, accurate texture representation for static objects can be realized by fusing multi-frame information; however, extending the process to dynamic objects, which typically have time-varying textures, is difficult. Thus, to address this problem, we propose a compact keyframe-based representation that decouples a dynamic texture into a basic static texture and a set of multiplicative changing maps. With this representation, the proposed method first aligns textures recorded from multiple keyframes with the reconstructed dynamic geometry of the object. Errors in the alignment and geometry are then compensated in an innovative iterative linear optimization framework. With the reconstructed texture, we then employ a scheme to synthesize the dynamic object from arbitrary viewpoints. By considering temporal and local pose similarities jointly, dynamic textures in all keyframes are fused to guarantee high-quality image generation. Experimental results demonstrate that the proposed method handles various dynamic objects, including faces, bodies, cloth, and toys. In addition, qualitative and quantitative comparisons demonstrate that the proposed method outperforms state-of-the-art solutions.