Position Of Label Research Articles

EXPRESS: Negative or positive left or right? The influence of attribute label position on IAT effects in picture-word IATs and word IATs.

The Implicit Association Test (IAT) is a widely used measure of implicit attitudes. Despite its application in various fields, the malleability of the IAT by different methodologial factors has been shown frequently. In the present paper, we focus on two factors that potentially influence the IAT effect, but which have received either inconsistent or no support so far: the IAT version (i.e., picture-word IAT vs. word IAT) and the position of the attribute labels on the screen (i.e., the positive or negative label on the left side). In two experiments, we used the original flower-insect IAT to systematically analyse the effects of the position of attribute labels (i.e., the assignment of the positive or the negative attribute label to the left screen position) and the block order of compatible (e.g., flower and positive) and incompatible blocks (e.g., flower and negative) as between-subjects factors.Reliable IAT effects were observed for the picture-word IAT and the word IAT when calculating the IAT effect as a difference in the response times as well as when computing the recommended D Score as IAT outcome. Smaller IAT effects occurred in the picture-word IAT than in the word IAT, supporting existing literature. Additionally, an effect of the position of the attribute labels on the screen was found in both experiments, resulting in larger IAT effects when the negative attribute label was positioned on the left. This effect also appeared when calculating the D score. The study highlights the importance of methodical factors for the IAT outcome.

An efficient EPR spin-labeling method enables insights into conformational changes in DNA

Electron paramagnetic resonance (EPR) is a powerful tool for elucidating both static and dynamic conformational alterations in macromolecules. However, to effectively utilize EPR for such investigations, the presence of paramagnetic centers, known as spin labels, is required. The process of spin labeling, particularly for nucleotides, typically demands intricate organic synthesis techniques. In this study, we introduce a unique addition-elimination reaction method with a simple spin-labeling process, facilitating the monitoring of structural changes within nucleotide sequences. Our investigation focuses on three distinct labeling positions with a DNA sequence, allowing the measurement of distance between two spin labels. The experimental mean distances obtained agreed with the calculated distances, underscoring the efficacy of this straightforward spin-labeling approach in studying complex biological processes such as transcription mechanism using EPR measurements.

The impacts of packaging on preferences for cannabis edibles: A discrete choice experiment

BackgroundsCannabis edibles recently gained considerable market share in the United States. The tobacco and food literatures consistently suggest that product packaging regulations are crucial to substance control, but little is known about how product packaging may impact cannabis edible use. This study aims to estimate the impacts of packaging on individual preferences for cannabis edibles and explore heterogeneities in preferences by cannabis use status and use purposes. Methods1578 adults were recruited, who lived in 18 states and Washington D.C. in the United States that legalized recreational cannabis by the time of data collection in August and September of 2022. An online discrete choice experiment was conducted to elicit individual choices between cannabis edibles with variations in five packaging attributes: package style, health claim, potency indicator, warning label position, and warning label text. Mixed logit regressions were used to assess associations between package attributes and package choices. Subsample analysis was conducted by cannabis use status (users vs. nonusers) and use purposes (medical-only, recreational-only, and dual-purpose) to detect heterogeneities. ResultsAlmost all subsamples prefer branded packages to plain packages, any health claim to no health claim, and any potency indicator to no potency indicator. Cannabis users, particularly recreational-only users and dual-purpose users, also prefer youth-appealing packages to branded packages. Warning label position and text have limited impacts on choices. Overall, package style is perceived to be the most important attribute among the five (relative importance 33.2–50.8%), followed by health claim (relative importance 22.6–30.5%). ConclusionIn the United States, adults’ preferences for cannabis edibles are associated with packaging features. Policies requiring plain package and prohibiting youth-appealing package and unsubstantiated health claims may be effective methods of cannabis control.

3D printable model of an entomological pinning block, designed for precise positioning of entomological glue boards and labels.

The entomological pinning block is a device widely used by entomologists to facilitate the mounting of glue boards and labels on entomological pins. The most commonly used entomological blocks are wooden blocks with steps of varying heights, allowing the placement of individual glue boards and labels at different levels. Models of entomological blocks ready for 3D printing are scarce on the Internet. The proposed model of an entomological block is ready for printing on a standard 3D printer. In addition to the usual positioning of glue boards and labels along the Z-axis, the model also offers targeting devices that enable precise positioning of the entomological pin along the X- and Y-axes. The proposed model can be easily modified for use with glue boards or labels of a different width than proposed or with label level steps of varying heights along the pin. The design of the new pinning block is simple, yet effective, making it an accessible and useful tool for entomologists, museum curators and amateur collectors.

Less Is More: Label Recommendation for Weakly Supervised Point Cloud Semantic Segmentation

Weak supervision has proven to be an effective strategy for reducing the burden of annotating semantic segmentation tasks in 3D space. However, unconstrained or heuristic weakly supervised annotation forms may lead to suboptimal label efficiency. To address this issue, we propose a novel label recommendation framework for weakly supervised point cloud semantic segmentation. Distinct from pre-training and active learning, the label recommendation framework consists of three stages: inductive bias learning, recommendations for points to be labeled, and point cloud semantic segmentation learning. In practice, we first introduce the point cloud upsampling task to induct inductive bias from structural information. During the recommendation stage, we present a cross-scene clustering strategy to generate centers of clustering as recommended points. Then we introduce a recommended point positions attention module LabelAttention to model the long-range dependency under sparse annotations. Additionally, we employ position encoding to enhance the spatial awareness of semantic features. Throughout the framework, the useful information obtained from inductive bias learning is propagated to subsequent semantic segmentation networks in the form of label positions. Experimental results demonstrate that our framework outperforms weakly supervised point cloud semantic segmentation methods and other methods for labeling efficiency on S3DIS and ScanNetV2, even at an extremely low label rate.

Photoactivatable Xanthone (PaX) Dyes Enable Quantitative, Dual Color, and Live-Cell MINFLUX Nanoscopy.

The single-molecule localization concept MINFLUX has triggered a reevaluation of the features of fluorophores for attaining nanometer-scale resolution. MINFLUX nanoscopy benefits from temporally controlled fluorescence ("on"/"off") photoswitching. Combined with an irreversible switching behavior, the localization process is expected to turn highly efficient and quantitative data analysis simple. The potential in the recently reported photoactivable xanthone (PaX) dyes is recognized to extend the list of molecular switches used for MINFLUX with 561nm excitation beyond the fluorescent protein mMaple. The MINFLUX localization success rates of PaX560 , PaX+560, and mMaple are quantitatively compared by analyzing the effective labeling efficiency of endogenously tagged nuclear pore complexes. The PaX dyes prove to be superior to mMaple and on par with the best reversible molecular switches routinely used in single-molecule localization microscopy. Moreover, the rationally designed PaX595 is introduced for complementing PaX560 in dual color 561nm MINFLUX imaging based on spectral classification and the deterministic, irreversible, and additive-independent nature of PaX photoactivation is showcased in fast live-cell MINFLUX imaging. The PaX dyes meet the demands of MINFLUX for a robust readout of each label position and fill the void of reliable fluorophores dedicated to 561nm MINFLUX imaging.

Studies of DNA breathing in exciton-coupled (iCy3)2 dimer-labeled DNA constructs by polarization-sweep single-molecule fluorescence (PS-SMF) microscopy.

Local fluctuations of the sugar-phosphate backbones and bases of DNA (a form of DNA 'breathing') play a central role in the assembly of protein-DNA complexes. We present a single-molecule fluorescence method to sensitively measure the local conformational fluctuations of exciton-coupled cyanine [(iCy3)2] dimer-labeled DNA fork constructs in which the dimer probes are placed at varying positions relative to the DNA fork junction. These systems exhibit spectroscopic signals that are sensitive to the local conformations adopted by the sugar-phosphate backbones and bases immediately surrounding the dimer probe label positions. The (iCy3)2 dimer has one symmetric (+) and one anti-symmetric (-) exciton with respective transition dipole moments oriented perpendicular to one another. We excite single molecule samples using a continuous-wave, linearly polarized laser with its polarization direction rotated at a frequency of 1 MHz. The ensuing fluorescence signal is modulated as the laser polarization alternately excites the symmetric and anti-symmetric excitons of the (iCy3)2 dimer probe. Phase-sensitive detection of the signal at the photon-counting level provides information about the distribution of local conformations and conformational dynamics. We analyze our data using a kinetic network model, which we use to parametrize the free energy surface of the system. In addition to observing DNA breathing at and near ss-dsDNA junctions, the approach can be used to study the effects of proteins that bind and function at these sites.

An MPI-based parallel genetic algorithm for multiple geographical feature label placement based on the hybrid of fixed-sliding models

ABSTRACT Multiple Geographical Feature Label Placement (MGFLP) has been a fundamental problem in geographic information visualization for decades. Moreover, the nature of label positioning has proven to be an Nondeterministic polynomial-time hard (NP-hard) problem. Although advances in computer technology and robust approaches have addressed the problem of label positioning, the lengthy running time of MGFLP has not been a major focus of recent studies. Based on a hybrid of the fixed-position and sliding models, a Message Passing Interface (MPI) parallel genetic algorithm is proposed in the present study for MGFLP to label mixed types of geographical features. To evaluate the quality of label placement, a quality function is defined based on four quality metrics: label-feature conflict; label-label conflict; label association with the corresponding feature; label position priority for all three types of features. The experimental results show that the proposed algorithm outperforms the DDEGA, DDEGA-NM, and Parallel-MS in both label placement quality and computation time efficiency. Across three datasets, compared to Parallel-MS, running times decreased from 118.45 to 8.34, 45.98 to 3.51, and 20.01 to 0.43 min, with further reductions in label-label and label-feature conflicts.

Systematic Literature Review on Halal Label Studies of Halal Tourism

The halal tourism sector is developing in a positive direction every year. Muslim-friendly vacations are a subset of the halal market which has an essential influence on Islamic economic development. This study aims to determine the extent of research developments related to a systematic literature review of halal certification targets in halal tourism. This research reveals the development of halal label studies on halal tourism, the target of halal certification in halal tourism, and discussions on future research development. This qualitative research uses a systematic literature review method, adopting the PRISMA system to screen articles that become research material. From 23 halal label research articles on halal tourism indexed by the Scopus database, this study selects all articles and leaves 18 as the main research material. The findings of this study show the dominance of authors from Indonesia and the development trend of publication of halal label studies on tourism in 2022. The results showed that Muslim tourists, in determining tourist destinations, pay attention to the availability of halal attributes such as halal food and hotels. This study has implications for the position of the halal label in halal tourism, which is increasingly important and has become a reference for the development of the halal industry.

Exploring the dynamics and structure of PpiB in living Escherichiacoli cells using electron paramagnetic resonance spectroscopy.

The combined effects of the cellular environment on proteins led to the definition of a fifth level of protein structural organization termed quinary structure. To explore the implication of potential quinary structure for globular proteins, we studied the dynamics and conformations of Escherichia coli (E. coli) peptidyl-prolyl cis/trans isomerase B (PpiB) in E. coli cells. PpiB plays a major role in maturation and regulation of folded proteins by catalyzing the cis/trans isomerization of the proline imidic peptide bond. We applied electron paramagnetic resonance (EPR) techniques, utilizing both Gadolinium (Gd(III)) and nitroxide spin labels. In addition to using standard spin labeling approaches with genetically engineered cysteines, we incorporated an unnatural amino acid to achieve Gd(III)-nitroxide orthogonal labeling. We probed PpiB's residue-specific dynamics by X-band continuous wave EPR at ambient temperatures and its structure by double electron-electron resonance (DEER) on frozen samples. PpiB was delivered to E. coli cells by electroporation. We report a significant decrease in the dynamics induced by the cellular environment for two chosen labeling positions. These changes could not be reproduced by adding crowding agents and cell extracts. Concomitantly, we report a broadening of the distance distribution in E. coli, determined by Gd(III)-Gd(III) DEER measurements, as compared with solution and human HeLa cells. This suggests an increase in the number of PpiB conformations present in E. coli cells, possibly due to interactions with other cell components, which also contributes to the reduction in mobility and suggests the presence of a quinary structure.

Understanding the pharmacokinetic journey of Fc-fusion protein, rhIL-7-hyFc using complementary approach of two analytical methods, accelerator mass spectrometry and ELISA.

Antibody-based therapeutics (ABTs), including monoclonal/polyclonal antibodies and fragment crystallizable region (Fc)-fusion proteins, are increasingly used in disease treatment, driving the global market growth. Understanding the pharmacokinetic (PK) properties of ABTs is crucial for their clinical effectiveness. This study investigated the PK profile and tissue distribution of efineptakin alfa, a long-acting recombinant human interleukin-7 (rhIL-7-hyFc), using enzyme-linked immunosorbent assay (ELISA) and accelerator mass spectrometry (AMS). Totally, four rats were injected intramuscularly with 1mg/kg of rhIL-7-hyFc containing 14C-rhIL-7-hyFc, which was prepared via reductive methylation. Serum total radioactivity (TRA) and serum rhIL-7-hyFc concentrations were quantified using AMS and ELISA, respectively. The TRA concentrations in organs were determined by AMS. Serum TRA peaked at 10hours with a terminal half-life of 40hours. The rhIL-7-hyFc exhibited a mean peak concentration at around 17hours and a rapid elimination with a half-life of 12.3hours. Peak concentration and area under the curve of TRA were higher than those of rhIL-7-hyFc. Tissue distribution analysis showed an elevated TRA concentrations in lymph nodes, kidneys, and spleen, indicating rhIL-7-hyFc's affinity for these organs. The study also simulated the positions of 14C labeling in rhIL-7-hyFc, identifying specific residues in the fragment of rhIL-7 portion, and provided the explanation of distinct analytes targeted by each method. Combining ELISA and AMS provided advantages by offering sensitivity and specificity for quantification as well as enabling the identification of analyte forms. The integrated use of ELISA and AMS offers valuable insights for the development and optimization of ABT.

Application of a long short-term memory neural network algorithm fused with Kalman filter in UWB indoor positioning

Ultra-wideband technology has good anti-interference capabilities and development prospects in indoor positioning. Since ultra-wideband will be affected by random errors in indoor positioning, to exploit the advantages of the Kalman filter (KF) and the long short-term memory (LSTM) network, this paper proposes a long short-term memory neural network algorithm fused with the Kalman filter (KF–LSTM) to improve UWB positioning. First, the ultra-wideband data is processed through KF to weaken the noise in the data, and then the data is fed into the LSTM network for training, and the capability of the LSTM network to process time series features is employed to obtain more accurate label positions. Finally, simulation and measurement results show that the KF–LSTM algorithm achieves 71.31%, 37.28%, and 49.31% higher average positioning accuracy than the back propagation (BP) network, (back propagation network fused with the Kalman filter (KF-BP), and LSTM network algorithms, respectively, and the KF–LSTM algorithm performs more stably. Meanwhile, the more noise the data contains, the more obvious the stability contrast between the four algorithms.

“Like Seeking out a Lost Friend”: Reconsidering “Pioneer” Arab Feminists and Their Networks as Part of a/the First Wave

AbstractContemporary Arab feminist writers such as Margot Badran and Mona Eltahawy describe their personal discovery of Arab “pioneers.” This label positions “pioneers” as exceptional figures, which untethers their legacy from contemporary Arab feminists, and from one another. Drawing on the Warwick Research Collective's concept of “combined and uneven development,” this essay rethinks how we understand the first wave to account for the feminist histories in al-mashreq, and therefore reimagines the feminist wave model to account for waves of transmission, of emotion such as inspiration drawn from solidarity with other women. Through analysis of Anglophone scholarship and biographies, translated autobiographical writings of “pioneers,” and analysis of L'Egyptienne magazine, this article offers a new way of framing the work of “pioneer” feminists as part of a wide network of collaborators, and a wave of feminist activism that is locally and globally imbricated. This paper examines women's journals and salons which contribute to a period of “invisible feminism” from 1860 to the early 1920s. The endeavors of three “pioneer” figures, Huda Sha'rawi (Egypt, 1879–1947), Anbara Salam Khalidi (Lebanon, 1897–1986), and May Ziadeh (Palestine/Lebanon, 1886–1941) are then discussed through the lens of their influential friendships with other women.

Graph Transformer for Label Placement.

Placing text labels is a common way to explain key elements in a given scene. Given a graphic input and original label information, how to place labels to meet both geometric and aesthetic requirements is an open challenging problem. Geometry-wise, traditional rule-driven solutions struggle to capture the complex interactions between labels, let alone consider graphical/appearance content. In terms of aesthetics, training/evaluation data ideally require nontrivial effort and expertise in design, thus resulting in a lack of decent datasets for learning-based methods. To address the above challenges, we formulate the task with a graph representation, where nodes correspond to labels and edges to interactions between labels, and treat label placement as a node position prediction problem. With this novel representation, we design a Label Placement Graph Transformer (LPGT) to predict label positions. Specifically, edge-level attention, conditioned on node representations, is introduced to reveal potential relationships between labels. To integrate graphic/image information, we design a feature aligning strategy that extracts deep features for nodes and edges efficiently. Next, to address the dataset issue, we collect commercial illustrations with professionally designed label layouts from household appliance manuals, and annotate them with useful information to create a novel dataset named the Appliance Manual Illustration Labels (AMIL) dataset. In the thorough evaluation on AMIL, our LPGT solution achieves promising label placement performance compared with popular baselines. Our algorithm and dataset are available at https://github.com/JingweiQu/LPGT.

Probing and perturbing riboswitch folding using a fluorescent base analogue.

Riboswitches are mRNA segments that regulate gene expression in response to ligand binding. The Class I preQ1 riboswitch consists of a stem-loop and an adenine-rich single-stranded tail ("L3"), which adopt a pseudoknot structure upon binding of the ligand preQ1 . We inserted 2-aminopurine (2-AP), a fluorescent analogue of adenine (A), into the riboswitch at six different positions within L3. Here, 2-AP functions both as a spectroscopic probe and as a "mutation" that reveals how alteration of specific A residues impacts the riboswitch. Using fluorescence and circular dichroism spectroscopy, we found that 2-AP decreases the affinity of the riboswitch for preQ1 at all labeling positions tested, although modified and unmodified variants undergo the same global conformational changes at sufficiently high preQ1 concentration. 2-AP substitution is most detrimental to ligand binding at sites proximal to the ligand-binding pocket, while distal labeling sites exhibit the largest impacts on the stability of the L3 domain in the absence of ligand. Insertion of multiple 2-AP residues does not induce significant additional disruptions. Our results show that interactions involving the A residues in L3 play a critical role in ligand recognition by the preQ1 riboswitch and that 2-AP substitution exerts complex and varied impacts on this riboswitch.

U-net based vortex detection in Bose–Einstein condensates with automatic correction for manually mislabeled data

Quantum vortices in Bose–Einstein condensates (BECs) are essential phenomena in condensed matter physics, and precisely locating their positions, especially the vortex core, is a precondition for studying their properties. With the rise of machine learning, there is a possibility to expedite the localization process and provide accurate predictions. However, traditional machine learning requires particular considerable amount of manual data annotation, leading to uncontrollable accuracy. In this paper, we utilize the U-Net method to detect vortex positions accurately at the pixel level and propose an Automatic Correction Labeling (ACL) approach to optimize the acquisition of data sets for vortex localization in BECs. This approach addresses inaccuracies in the labeled vortex positions and improves the accuracy of vortex localization, especially the vortex core positions, while enhancing the tolerance for human mislabeling. The main process involves Rough Labeling →\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\rightarrow $$\\end{document} Machine Learning →\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\rightarrow $$\\end{document} Probability Region Search →\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\rightarrow $$\\end{document} Data Relabeling →\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\rightarrow $$\\end{document} Machine Learning again. The objective of ACL is to secure more accurate labeled data for model retraining. Through vortex localization experiments conducted in a two-dimensional Bose-Einstein condensate, our results establish the following: 1. Even under conditions of biased and missing manual annotations, U-Net can still accurately locate vortex positions; 2. Vortices exhibit certain regularities, and training U-Net with a small number of samples yields excellent predictive consequences; 3. The machine learning vortex locator based on the ACL method effectively corrects errors in manually annotated data, significantly improving the model’s performance metrics, thus enhancing the precision and metrics of vortex localization. This substantial advancement in the application of machine learning in vortex localization provides an effective way for vortex dynamics localization. Furthermore, this method of obtaining more accurate positions of approximate human labels through machine learning offers new insights for machine learning in other types of image recognition problems.

A non-contact interactive system for multimodal surgical robots based on LeapMotion and visual tags.

In recent years, the integration of robots in minimally invasive surgery has gained significant traction in clinical practice. However, conventional contact-based human-computer interaction poses the risk of bacterial infection, significantly limiting the role of robots in surgery. To address this limitation, we propose an innovative interaction method rooted in gestures and visual tags, allowing surgeons to control and fine-tune surgical robots without physical contact with the environment. By encoding the six gestures collected using LeapMotion, we can effectively control the surgical robot in a non-contact manner. Moreover, utilizing Aruco technology, we have accurately identified the 3D spatial position of the visual label, and developed 12 fine-tuning operations to refine surgical instruments. To evaluate the applicability of our proposed system in surgery, we designed a relevant experimental setup. In the experiment, we achieved enough precision. These results demonstrate that our system meets the clinical standard, providing doctors with a non-contact and flexible means of interacting with robots during surgery.

A Hybrid Discrete Artificial Bee Colony Algorithm Based on Label Similarity for Solving Point-Feature Label Placement Problem

The artificial bee colony algorithm (ABC) is a promising metaheuristic algorithm for continuous optimization problems, but it performs poorly in solving discrete problems. To address this issue, this paper proposes a hybrid discrete artificial bee colony (HDABC) algorithm based on label similarity for the point-feature label placement (PFLP) problem. Firstly, to better adapt to PFLP, we have modified the update mechanism for employed bees and onlooker bees. Employed bees learn the label position of the better individuals, while onlooker bees perform dynamic probability searches using two neighborhood operators. Additionally, the onlooker bees’ selection method selects the most promising solutions based on label similarity, which improves the algorithm’s search capabilities. Finally, the Metropolis acceptance strategy is replaced by the original greedy acceptance strategy to avoid the premature convergence problem. Systematic experiments are conducted to verify the effectiveness of the neighborhood solution generation method, the selection operation based on label similarity, and the Metropolis acceptance strategy in this paper. In addition, experimental comparisons were made at different instances and label densities. The experimental results show that the algorithm proposed in this paper is better or more competitive with the compared algorithm.

Characterization of Pharmacokinetics, Biotransformation and Elimination of Pomotrelvir Orally Administered in Healthy Male Adults Using Two [14C]-labeled Microtracers with Separate Labeling Positions.

Pomotrelvir is an orally bioavailable, target antiviral inhibitor of the main protease (Mpro) of coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of Coronavirus Disease 2019 (COVID-19). The pharmacokinetics, metabolism and elimination of two [14C]-labeled microtracers of 5 µCi/700 mg pomotrelvir with separate labeling positions (isotopomers), [lactam carbonyl-14C-pomotelvir] and [benzene ring-U-14C-pomotrelvir], following a single oral dose in healthy adult males was evaluated in two separate cohorts. Pomotrelvir was rapidly absorbed and eliminated primarily through metabolism and subsequently excreted via urine and feces. There were no differences in pomotrelvir pharmacokinetics between the two cohorts. The mean total radioactive dose recovered was 93.8% (n=8) in the lactam cohort (58% in urine and 36% in feces) and 94.2% (n=8) in the benzene cohort (75% in urine and 19% in feces), with {greater than or equal to} 80% of [14C] recovered within 96 hours after dosing. About 5% and 3% of the intact pomotrelvir was recovered in feces and urine, respectively. Eleven major metabolites were detected and characterized using LC-accelerator mass spectrometry (AMS) and LC-MS/MS methods, with 3 and 6 different metabolites elucidated in the samples collected from lactam and benzene cohorts, respectively, and 2 metabolites observed in both cohorts. The major metabolism pathway of pomotrelvir is through hydrolysis of its peptide bonds followed by phase II conjugations. These results support that the application of two radiolabeled isotopomers provided a comprehensive metabolite profiling analysis and was a successful approach in identifying the major disposition pathways of pomotrelvir that has complex routes of metabolism. Significance Statement An unconventional approach using two differentially labeled [14C] microtracers, [lactam carbonyl-14C-pomotrelvir] and [benzene ring-U-14C-pomotrelvir] evaluated the mass balance of orally administered pomotrelvir in healthy adult males in two separate cohorts. The radioactive dose recovered in excreta was about 94% for both cohorts. While the two isotopomers of the radiolabeled-pomotrelvir showed no major differences in pharmacokinetics overall, they allowed for differential detection of their radiolabeled metabolites and appropriate characterization of their plasma exposure and excretion in urine and feces.

Particle fusion of super-resolution data reveals the unit structure of Nup96 in Nuclear Pore Complex

Single molecule localization microscopy offers resolution nearly down to the molecular level with specific molecular labelling, and is thereby a promising tool for structural biology. In practice, however, the actual value to this field is limited primarily by incomplete fluorescent labelling of the structure. This missing information can be completed by merging information from many structurally identical particles in a particle fusion approach similar to cryo-EM single-particle analysis. In this paper, we present a data analysis of particle fusion results of fluorescently labelled Nup96 nucleoporins in the Nuclear Pore Complex to show that Nup96 occurs in a spatial arrangement of two rings of 8 units with two Nup96 copies per unit giving a total of 32 Nup96 copies per pore. We use Artificial Intelligence assisted modeling in Alphafold to extend the existing cryo-EM model of Nup96 to accurately pinpoint the positions of the fluorescent labels and show the accuracy of the match between fluorescent and cryo-EM data to be better than 3 nm in-plane and 5 nm out-of-plane.