Translational regulation enhances distinction of cell types in the nervous system.

Multicellular organisms are composed of specialized cell types with distinct proteomes. While recent advances in single-cell transcriptome analyses have revealed differential expression of mRNAs, cellular diversity in translational profiles remains underinvestigated. By performing RNA-seq and Ribo-seq in genetically defined cells in the Drosophila brain, we here revealed substantial post-transcriptional regulations that augment the cell-type distinctions at the level of protein expression. Specifically, we found that translational efficiency of proteins fundamental to neuronal functions, such as ion channels and neurotransmitter receptors, was maintained low in glia, leading to their preferential translation in neurons. Notably, distribution of ribosome footprints on these mRNAs exhibited a remarkable bias toward the 5' leaders in glia. Using transgenic reporter strains, we provide evidence that the small upstream open-reading frames in the 5' leader confer selective translational suppression in glia. Overall, these findings underscore the profound impact of translational regulation in shaping the proteomics for cell-type distinction and provide new insights into the molecular mechanisms driving cell-type diversity.

Modified Radiological Union Score of Tibia (RUST) Scores in Diaphyseal Fractures Treated by the Ilizarov Frame: A Retrospective Analysis Evaluating Reliability.

Introduction The number of cases of tibia diaphyseal fractures treated by Ilizarov fixation is increasing. Fractures with infective etiology and altered bone biology due to the requirement of revision surgery or open wounds, which are often treated by the Ilizarov method, have challenges in ascertaining radiological signs of union. In this study, we aim to demonstrate the application of the modified Radiological Union Score of Tibia (m-RUST) scores in the assessment of fracture union in patients operated by the Ilizarov method. The secondary aim is to assess the interobserver and intraobserver variability of the m-RUST score validated by orthopaedicians and radiologists. Methodology A total of 119 patients who were treated with an Ilizarov fixator from February 2017 to December 2023 were included in the study. Four observers (two orthopaedicians and two radiologists) independently applied the m-RUST score for the included patients. Clinical data were not disclosed to the observers who worked independently of each other. Intraclass correlation coefficients (ICC) with 95% confidence intervals (CI) were used to measure the reliability of the m-RUST score. Interobserver reliability was measured by examining the scores of four observers from the second assessment, and intra-observer variability was assessed by a repeat evaluation after two weeks following the first assessment. Results The m-RUST score of the 119 X-rays analysed ranged from 8 to 16. The mean score in the first assessment was 11.36±3.51, and in the second assessment was 11.42±3.39. The reliability between all the observers was "substantial agreement" (ICC: 0.74, 95% CI). The ICC among the orthopaedicians was 0.77 and that among the radiologists was 0.72. Conclusion The m-RUST score has potential in other long bone fractures such as femur or humerus. Assessment of the m-RUST score in the healing of infective sequel and bone grafting conditions has been found effective. The m-RUST score is a dependable score in evaluating union in tibia fractures treated by the Ilizarov frame.

Nonlinear similarity characterisation and validation of dynamic response of ship stiffened plate structure under explosion load impacts.

The similarity test of ship stiffened plate structures under underwater explosions is a cost-effective and efficient method to evaluate the vitality of ships and guide the design of their shock resistance. This study focuses on the nonlinear impact response model tests of ship stiffened plate structures and their similarity laws with actual ships. The vertical motion of the ship stiffened plate structure is characterized by the Hurst index, and an equivalent relationship between the Hurst index of the model and the prototype is derived from classical similarity law. Based on the Hurst index, a similarity transformation relationship between the strain signals of the model and prototype is established. To verify the conclusions, similarity experiments of underwater explosions were conducted on both the model and the prototype. The original signals were grouped by the natural vibration period to determine the variation of the Hurst index over time. The model experiment strain signals for each natural vibration period were converted and compared with the prototype experiment results to verify the method's effectiveness. Simultaneously, the Hurst index of the stiffened plate structure under explosive shock load and its similarity transformation relationship with the prototype were simulated and analyzed. This provides theoretical and technical support for conducting analogous nonlinear response experiments for ship underwater explosions.

Surface defect detection of ceramic disc based on improved YOLOv5s.

Addressing the challenges in detecting surface defects on ceramic disks, such as difficulty in detecting small defects, variations in defect sizes, and inaccurate defect localization, we propose an enhanced YOLOv5s algorithm. Firstly, we improve the anchor frame structure of the YOLOv5s model to enhance its generalization ability, enabling robust defect detection for objects of varying sizes. Secondly, we introduce the ECA attention mechanism to improve the model's accuracy in detecting small targets. Under identical experimental conditions, our enhanced YOLOv5s algorithm demonstrates significant improvements, with precision, F1 scores, and mAP values increasing by 3.1 %, 3 %, and 4.5 % respectively. Moreover, the accuracy in detecting crack, damage, slag, and spot defects increases by 0.2 %, 4.7 %, 5.4 %, and 1.9 % respectively. Notably, the detection speed improves from 232 frames/s to 256 frames/s. Comparative analysis with other algorithms reveals superior performance over YOLOv3 and YOLOv4 models, showcasing enhanced capability in identifying small target defects and achieving real-time detection.

Evolution of natural myocardial shear wave behavior in young hearts: determinant factors and reproducibility analysis.

BACKGROUND: Myocardial diastolic function assessment in children by conventional echocardiography is challenging. Recent high frame rate (HFR) echocardiography facilitates the assessment of myocardial stiffness (MS) -a key factor of diastolic function- by measuring the propagation velocities of myocardial shear waves (SWs). However, normal values of natural SWs in children are currently lacking. OBJECTIVES: To explore the behavior of natural SW among children and adolescents, their reproducibility, and the factors affecting SW velocities from childhood into adulthood. METHODS: 106 healthy children (2-18 years) and 62 adults (19-80 years) were recruited. HFR images were acquired using a modified commercial scanner. An anatomical M-mode was drawn along the ventricular septum, and propagation velocities of natural SWs after mitral valve closure (MVC) were measured in the tissue acceleration coded M-mode display. RESULTS: Throughout life, SW velocities after MVC exhibited pronounced age dependency (r= 0.73; P<0.001). Among the pediatric population, SW velocities correlated significantly with measures of cardiac geometry (septal thickness and left ventricular end-diastolic dimension), local hemodynamics (systolic blood pressure), as well as with echocardiographic parameters of systolic and diastolic function (global longitudinal strain (GLS), mitral E/e', isovolumetric relaxation time and mitral deceleration time) (P <0.001). In a multivariate analysis including all these factors, the predictors of SW velocities were age, mitral E/e', and GLS (r= 0.81). CONCLUSIONS: Natural myocardial SW velocities in children can be detected and measured. SW velocities showed significant dependence on age and diastolic function. Natural SWs could be a promising additive tool for assessment of diastolic function among children.

Cellular function of the GndA small open reading frame-encoded polypeptide during heat shock.

Over the past 15 years, hundreds of previously undiscovered bacterial small open reading frame (sORF)-encoded polypeptides (SEPs) of fewer than fifty amino acids have been identified, and biological functions have been ascribed to an increasing number of SEPs from intergenic regions and small RNAs. However, despite numbering in the dozens in Escherichia coli, and hundreds to thousands in humans, same-strand nested sORFs that overlap protein coding genes in alternative reading frames remain understudied. In order to provide insight into this enigmatic class of unannotated genes, we characterized GndA, a 36-amino acid, heat shock-regulated SEP encoded within the +2 reading frame of the gnd gene in E. coli K-12 MG1655. We show that GndA pulls down components of respiratory complex I (RCI) and is required for proper localization of a RCI subunit during heat shock. At high temperature GndA deletion (ΔGndA) cells exhibit perturbations in cell growth, NADH+/NAD ratio, and expression of a number of genes including several associated with oxidative stress. These findings suggest that GndA may function in maintenance of homeostasis during heat shock. Characterization of GndA therefore supports the nascent but growing consensus that functional, overlapping genes occur in genomes from viruses to humans.

The roles of symmetry and elongation in developing reference frames.

Previous studies showed that elongation and symmetry (two ubiquitous aspects of natural stimuli) are important attributes in object perception and recognition, which in turn suggests that these geometrical factors may contribute to the selection of perceptual reference-frames. However, whether and how these attributes guide the selection of reference-frames is still poorly understood. The goal of this study was to examine systematically the roles of elongation and symmetry, as well as their combination, in the selection of reference axis and how these axes are developed for unfamiliar objects. We designed our experiments to eliminate two potential confounding factors: (i) extraneous environmental cues, such as edges of the screen, etc. (by using VR) and (ii) pre-learned cues for familiar objects and shapes (by using reinforcement learning of novel shapes). We used algorithmically generated textures with different orientations having specified levels of symmetry and elongation as the stimuli. In each trial, we presented only one stimulus and asked observers to report if the stimulus was in its original form or a flipped (mirror-image) one. Feedback was provided at the end of each trial. Based on previous studies on mental rotation, we hypothesized that the selection of a reference-frame defined by symmetry and/or elongation would be revealed by a linear relationship between reaction-times and the angular-deviation from either the most symmetrical or the most elongated orientation. Our results are consistent with this hypothesis. We found that subjects performed mental rotation to transform images to their reference axes and used the most symmetrical or elongated orientation as the reference axis when only one factor was presented, and they used a "winner-take-all" strategy when both factors were presented, with elongation being more dominant than symmetry. We discuss theoretical implications of these findings, in particular in the context of "canonical sensorimotor theory."

Sign language images dataset from Mexican sign language.

Sign language is a complete language with its own grammatical rules, akin to any spoken language used worldwide. It comprises two main components: static words and ideograms. Ideograms involve hand movements and contact with various parts of the body to convey meaning. Variations in sign language are evident across different countries, necessitating comprehensive documentation of each country's sign language. In Mexico, there is a lack of formal datasets for Mexican Sign Language (MSL), to solve this issue we structure a dataset of 249 words of the MSL divided into 17 sub-sets, we use background and clothes of black color to enhance the areas of interest (hands and face), for each word we use an average of 11 individuals, from every video sequence we obtain an average of 15 frames from each individual, obtaining 31442 jpg images.

Prediction of frequency response of sub-frame bushing and study of high-order fractional derivative viscoelastic model.

This paper presents experimental and dynamic modeling research on the rubber bushings of the rear sub-frame. The Particle Swarm Optimization algorithm was utilized to optimize a Backpropagation (BP) neural network, which was separately trained and tested across two frequency ranges: 1-40 Hz and 41-50 Hz, using wideband frequency sweep dynamic stiffness test data. The testing errors at amplitudes of 0.2 mm, 0.3 mm, and 0.5 mm were found to be 1.03%, 3.05%, and 1.96%, respectively. Subsequently, the trained neural network was employed to predict data within the frequency range of 51-70 Hz. To incorporate the predicted data into simulation software, a dynamic model of the rubber bushing was established, encompassing elastic, friction, and viscoelastic elements. Additionally, a novel model, integrating high-order fractional derivatives, was proposed based on the frequency-dependent model for the viscoelastic element. An enhanced Particle Swarm Optimization algorithm was introduced to identify the model's parameters using the predicted data. In comparison to the frequency-dependent model, the new model exhibited lower fitting errors at various amplitudes, with reductions of 3.84%, 3.61%, and 5.49%, respectively. This research establishes a solid foundation for subsequent vehicle dynamic modeling and simulation.

Using FRAME to characterize provider-identified adaptations to a stepped care intervention for adolescents and youth living with HIV in Kenya: a mixed methods approach.

INTRODUCTION: The Data-informed Stepped Care (DiSC) study is a cluster-randomized trial implemented in 24 HIV care clinics in Kenya, aimed at improving retention in care for adolescents and youth living with HIV (AYLHIV). DiSC is a multi-component intervention that assigns AYLHIV to different intensity (steps) of services according to risk. We used the Framework for Reporting Adaptations and Modifications-Expanded (FRAME) to characterize provider-identified adaptations to the implementation of DiSC to optimize uptake and delivery, and determine the influence on implementation outcomes. METHODS: Between May and December 2022, we conducted continuous quality improvement (CQI) meetings with providers to optimize DiSC implementation at 12 intervention sites. The meetings were guided by plan-do-study-act processes to identify challenges during early phase implementation and propose targeted adaptations. Meetings were audio-recorded and analysed using FRAME to categorize the level, context and content of planned adaptations and determine if adaptations were fidelity consistent. Providers completed surveys to quantify perceptions of DiSC acceptability, appropriateness and feasibility. Mixed effects linear regression models were used to evaluate these implementation outcomes over time. RESULTS: Providers participated in eight CQI meetings per facility over a 6-month period. A total of 65 adaptations were included in the analysis. The majority focused on optimizing the integration of DiSC within the clinic (83%, n = 54), and consisted of improving documentation, addressing scheduling challenges and improving clinic workflow. Primary reasons for adaptation were to align delivery with AYLHIV needs and preferences and to increase reach among AYLHIV: with reminder calls to AYLHIV, collaborating with schools to ensure AYLHIV attended clinic appointments and addressing transportation challenges. All adaptations to optimize DiSC implementation were fidelity-consistent. Provider perceptions of implementation were consistently high throughout the process, and on average, slightly improved each month for intervention acceptability (ß = 0.011, 95% CI: 0.002, 0.020, p = 0.016), appropriateness (ß = 0.012, 95% CI: 0.007, 0.027, p<0.001) and feasibility (ß = 0.013, 95% CI: 0.004, 0.022, p = 0.005). CONCLUSIONS: Provider-identified adaptations targeted improved integration into routine clinic practices and aimed to reduce barriers to service access unique to AYLHIV. Characterizing types of adaptations and adaptation rationale may enrich our understanding of the implementation context and improve abilities to tailor implementation strategies when scaling to new settings.

Multimodality assessment of the coronary microvasculature with TIMI frame count versus perfusion PET highlights coronary changes characteristic of coronary microvascular disease.

Background: The diagnosis of coronary microvascular disease (CMVD) remains challenging. Perfusion PET-derived myocardial blood flow (MBF) reserve (MBFR) can quantify CMVD but is not widely available. Thrombolysis in Myocardial Infarction (TIMI) frame count (TFC) is an angiography-based method that has been proposed as a measure of CMVD. Here, we compare TFC and PET-derived MBF measurements to establish the role of TFC in assessing for CMVD. We use coronary modeling to elucidate the relationship between MBFR and TFC and propose TFC thresholds for identifying CMVD. Methods: In a cohort of 123 individuals (age 58 ± 12.1, 63% women, 41% Caucasian) without obstructive coronary artery disease who had undergone perfusion PET and coronary angiography for clinical indications, we compared TFC and perfusion PET parameters using Pearson correlation (PCC) and linear regression modeling. We used mathematical modeling of the coronary circulation to understand the relationship between these parameters and performed Receiver Operating Curve (ROC) analysis. Results: We found a significant negative correlation between TFC and MBFR. Sex, race and ethnicity, and nitroglycerin administration impact this relationship. Coronary modeling showed an uncoupling between TFC and flow in epicardial vessels. In ROC analysis, TFC performed well in women (AUC 0.84-0.89) and a moderately in men (AUC 0.68-0.78). Conclusions: We established an inverse relationship between TFC and PET-derived MBFR, which is affected by patient selection and procedural factors. TFC represents a measure of the volume of the epicardial coronary compartment, which is increased in patients with CMVD, and performs well in identifying women with CMVD.

An allocentric human odometer for perceiving distances on the ground plane.

We reliably judge locations of static objects when we walk despite the retinal images of these objects moving with every step we take. Here, we showed our brains solve this optical illusion by adopting an allocentric spatial reference frame. We measured perceived target location after the observer walked a short distance from the home base. Supporting the allocentric coding scheme, we found the intrinsic bias , which acts as a spatial reference frame for perceiving location of a dimly lit target in the dark, remained grounded at the home base rather than traveled along with the observer. The path-integration mechanism responsible for this can utilize both active and passive (vestibular) translational motion signals, but only along the horizontal direction. This asymmetric path-integration finding in human visual space perception is reminiscent of the asymmetric spatial memory finding in desert ants, pointing to nature's wondrous and logically simple design for terrestrial creatures.

Validation of Inertial-Measurement-Unit-Based Ex Vivo Knee Kinematics during a Loaded Squat before and after Reference-Frame-Orientation Optimisation.

Recently, inertial measurement units have been gaining popularity as a potential alternative to optical motion capture systems in the analysis of joint kinematics. In a previous study, the accuracy of knee joint angles calculated from inertial data and an extended Kalman filter and smoother algorithm was tested using ground truth data originating from a joint simulator guided by fluoroscopy-based signals. Although high levels of accuracy were achieved, the experimental setup leveraged multiple iterations of the same movement pattern and an absence of soft tissue artefacts. Here, the algorithm is tested against an optical marker-based system in a more challenging setting, with single iterations of a loaded squat cycle simulated on seven cadaveric specimens on a force-controlled knee rig. Prior to the optimisation of local coordinate systems using the REference FRame Alignment MEthod (REFRAME) to account for the effect of differences in local reference frame orientation, root-mean-square errors between the kinematic signals of the inertial and optical systems were as high as 3.8° ± 3.5° for flexion/extension, 20.4° ± 10.0° for abduction/adduction and 8.6° ± 5.7° for external/internal rotation. After REFRAME implementation, however, average root-mean-square errors decreased to 0.9° ± 0.4° and to 1.5° ± 0.7° for abduction/adduction and for external/internal rotation, respectively, with a slight increase to 4.2° ± 3.6° for flexion/extension. While these results demonstrate promising potential in the approach's ability to estimate knee joint angles during a single loaded squat cycle, they highlight the limiting effects that a reduced number of iterations and the lack of a reliable consistent reference pose inflicts on the sensor fusion algorithm's performance. They similarly stress the importance of adapting underlying assumptions and correctly tuning filter parameters to ensure satisfactory performance. More importantly, our findings emphasise the notable impact that properly aligning reference-frame orientations before comparing joint kinematics can have on results and the conclusions derived from them.

Early Warning for Continuous Rigid Frame Bridges Based on Nonlinear Modeling for Temperature-Induced Deflection.

Bridge early warning based on structural health monitoring (SHM) system is of significant importance for ensuring bridge safe operation. The temperature-induced deflection (TID) is a sensitive indicator for performance degradation of continuous rigid frame bridges, but the time-lag effect makes it challenging to predict the TID accurately. A bridge early warning method based on nonlinear modeling for the TID is proposed in this article. Firstly, the SHM data of temperature and deflection of a continuous rigid frame bridge are analyzed to examine the temperature gradient variation patterns. Kernel principal component analysis (KPCA) is used to extract principal temperature components. Then, the TID is extracted through wavelet transform, and a nonlinear modeling method for the TID considering the temperature gradient is proposed using the support vector machine (SVM). Finally, the prediction errors of the KPCA-SVM algorithm are analyzed, and the early warning thresholds are determined based on the statistical patterns of the errors. The results show that the KPCA-SVM algorithm achieves high-precision nonlinear modeling for the TID while significantly reducing the computational load. The prediction results have coefficients of determination above 0.98 and fluctuate within a small range with clear statistical patterns. Setting the early warning thresholds based on the statistical patterns of errors enables dynamic and multi-level warnings for bridge structures.

Motion-Aware Video Frame Interpolation.

Video frame interpolation methodologies endeavor to create novel frames betwixt extant ones, with the intent of augmenting the video's frame frequency. However, current methods are prone to image blurring and spurious artifacts in challenging scenarios involving occlusions and discontinuous motion. Moreover, they typically rely on optical flow estimation, which adds complexity to modeling and computational costs. To address these issues, we introduce a Motion-Aware Video Frame Interpolation (MA-VFI) network, which directly estimates intermediate optical flow from consecutive frames by introducing a novel hierarchical pyramid module. It not only extracts global semantic relationships and spatial details from input frames with different receptive fields, enabling the model to capture intricate motion patterns, but also effectively reduces the required computational cost and complexity. Subsequently, a cross-scale motion structure is presented to estimate and refine intermediate flow maps by the extracted features. This approach facilitates the interplay between input frame features and flow maps during the frame interpolation process and markedly heightens the precision of the intervening flow delineations. Finally, a discerningly fashioned loss centered around an intermediate flow is meticulously contrived, serving as a deft rudder to skillfully guide the prognostication of said intermediate flow, thereby substantially refining the precision of the intervening flow mappings. Experiments illustrate that MA-VFI surpasses several representative VFI methods across various datasets, and can enhance efficiency while maintaining commendable efficacy.

DNA-based nanostructures for RNA delivery.

RNA-based therapeutics have emerged as a promising approach for the treatment of various diseases, including cancer, genetic disorders, and infectious diseases. However, the delivery of RNA molecules into target cells has been a major challenge due to their susceptibility to degradation and inefficient cellular uptake. To overcome these hurdles, DNA-based nano technology offers an unprecedented opportunity as a potential delivery platform for RNA therapeutics. Due to its excellent characteristics such as programmability and biocompatibility, these DNA-based nanostructures, composed of DNA molecules assembled into precise and programmable structures, have garnered significant attention as ideal building materials for protecting and delivering RNA payloads to the desired cellular destinations. In this review, we highlight the current progress in the design and application of three DNA-based nanostructures: DNA origami, lipid-nanoparticle (LNP) technology related to frame guided assembly (FGA), and DNA hydrogel for the delivery of RNA molecules. Their biomedical applications are briefly discussed and the challenges and future perspectives in this field are also highlighted.

Advancements and Challenges in the Application of Metal-Organic Framework (MOF) Nanocomposites for Tumor Diagnosis and Treatment.

Nanoscale metal-organic frameworks (MOFs) offer high biocompatibility, nanomaterial permeability, substantial specific surface area, and well-defined pores. These properties make MOFs valuable in biomedical applications, including biological targeting and drug delivery. They also play a critical role in tumor diagnosis and treatment, including tumor cell targeting, identification, imaging, and therapeutic methods such as drug delivery, photothermal effects, photodynamic therapy, and immunogenic cell death. The diversity of MOFs with different metal centers, organics, and surface modifications underscores their multifaceted contributions to tumor research and treatment. This review is a summary of these roles and mechanisms. The final section of this review summarizes the current state of the field and discusses prospects that may bring MOFs closer to pharmaceutical applications.

Beyond Translation: Exploring the Stigmatization of Rainbow Works Translation Under Frame Theory.

Drawing on Goffman's frame theory, this study examines the attitudes of nine Chinese university teacher translators in translating rainbow works, ranging from hesitancy to resistance. The primary objective is to uncover the frames of stigmatization inherent in their negative attitudes toward rainbow works translation. The research clarifies the identities of perpetrators and victims in these frames leading to stigmatization. Findings indicate that various stigmatization events in rainbow works translation share a common feature-an unfavorable depiction of rainbow culture and related elements, encompassing the rainbow community, works, and translators. Perpetrators and victims vary across events, demonstrating diversity. The research interprets stigmatization in rainbow works translation at individual, institutional, and sociocultural levels. Providing a unique Chinese perspective, the study contributes to international understanding of stigmatization in a heteronormative society. It challenges traditional Chinese norms, advocates reevaluating identity labels for the rainbow community, and underscores the importance of addressing translators' circumstances in translating rainbow works within specific societal contexts.