bluuebunny/crossref_metadata_2025 huggingface dataset:
Ethical Implications of Social Science Research on Xenotransplantation
Authors: Kögel Johannes , Ernst Paulina , Sauermeister Jochen , Marckmann Georg
Published: November 2024

Social science research has generated extensive knowledge on xenotransplantation, encompassing the perspectives of actual and potential patients, other stakeholders, public opinion and debate, human‐animal relationships, animal production and husbandry, bioeconomy, as well as biotechnology governance and regulation. We therefore convened social science researchers to discuss the latest developments in xenotransplantation research and practice in late 2023. Based on a brief workshop report, we aim to highlight the various ethical implications of this debate. After outlining the role of social science research in the ethical evaluation of xenotransplantation, we elaborate three critical points that may become pivotal in the future evolution of xenotransplantation: the framing of xenotransplantation in the clinical setting and in the public, the potential impact of religious beliefs on patients' transplant choices, and the consequences for the allotransplantation system if xenotransplantation becomes clinically established, including the allocation of allo‐ and xeno‐organs.
The Burns–Krantz rigidity on bounded symmetric domains
Authors: Ng Sui‐Chung , Rong Feng
Published: November 2024

In this paper, we give a Burns–Krantz rigidity result on some fibered domains. As an application, we obtain the Burns–Krantz rigidity on bounded symmetric domains.
Numerical Investigation of Unsteady Flow Characteristics of Planar Plug Nozzle in Overexpanded Conditions
Authors: Trivedi Rahul , Bhaduri Sreejita , Sugarno Mohammed Ibrahim , De Ashoke
Published: November 2024

Plug nozzles are frequently regarded as a strong contender for futuristic single-stage-to-orbit (SSTO) space missions due to their inherent altitude-compensating properties. Optimizing the design of these nozzles to achieve peak performance during the initial ascent phase is of pre-eminent importance. The current research aims to deepen our comprehension of the unsteady behavior of plug nozzles during this ascent phase, commonly referred to as the overexpanded flow regime. It utilizes a full-spike plug nozzle and employs a finite volume-based solver within the OpenFOAM framework to investigate flow features across nozzle pressure ratios (NPRs) ranging from 3 to 8. Additionally, the Ffowcs Williams Hawkings (FW-H) analogy is employed to assess the influence of acoustics in the nozzle's flow field at different NPRs. Spectral analysis and flow visualizations are employed to study the frequency content and the respective flow features of the system. It is observed that the flow exhibits separation beyond NPR 4 and is highly unsteady at NPR 6, which is inferred from the prominence of the recirculation bubble. However, beyond NPR 6, the flow tends to reattach the plug surface, dampening the disturbance.
Selective Deposition and Fusion of AISI 316L: An Additive Manufacturing Process for Space Environments via Direct Ink Writing and Laser Processing
Authors: Hoffmann Miguel , Ye Jiahui , Elwany Alaa
Published: November 2024

Unlocking the potential of additive manufacturing (AM) for space exploration hinges on overcoming key challenges, notably the ability to manufacture or repair parts on-site during exploration missions with consideration of quality, feedstock utilization, and challenges involved in microgravity environments. While there are multiple efforts to investigate the use of existing metal AM processes such as powder bed fusion (PBF), directed energy deposition (DED), and filament-based material extrusion, each process comes with a different set of challenges in space environments. Here, we introduce a new AM method that integrates the benefits of direct ink writing (DIW) to selectively deposit metallic pastes with laser-based processing to locally debind and subsequently melt and fuse metal powder, layer by layer, enabling the manufacturing of AISI 316L samples with densities exceeding 99.0%. The impact of process parameters on single-track dimensions, surface morphology, and porosity was characterized. The efficacy of laser debinding was assessed via secondary-ion mass spectrometry, permitting the carbon content to be estimated at 0.0152%, which is safely below the acceptable limit (0.03 wt%) for AISI 316L.
Modeling Elastic Cable-Surface Friction for Soft Robots
Authors: Matte Christopher-Denny , Kwok Tsz Ho
Published: November 2024

Due to inherent compliance and non-linear behaviour, modelling soft robots is highly complex. While the elasticity of their materials provides the robots with adaptability and resilience, it also causes undesirable effects. Cable-driven soft robots are particularly affected by frictional forces, which can significantly alter their deformed shape. Unfortunately, most existing cable-friction models have been developed for rigid surfaces and do not account for the interactions between elastic cables and surfaces. As a result, research on cable-driven soft robots often neglects friction due to the difficulty of acquiring data and implementing the mathematical models. This paper introduces a novel friction model that considers the asperity behaviour of both the cable and the friction surface. We propose a new methodology that accurately replicates friction interaction in soft robots, which requires as few as nine data points. The methodology is assessed on four distinct material interactions, comprising two cables with different diameters and materials, and two 3D-printed surfaces made from PLA and TPU. By accurately estimating the nonuniform distribution of the joint deformation caused by friction, the new friction formulation achieves a 2.8% error in predicting a soft gripper’s tip locations, while the current state-of-the-art model shows a 16.1% error. We also demonstrate that, with an accurate friction model, it is possible to optimize the cable routing points to achieve the desired grasping strategy for a soft gripper.
A Design for Remanufacturing Framework Incorporating Identification, Evaluation, and Validation: A Case Study of Hydraulic Manifold
Authors: Liu Xinyang , Chung In-Bum , Behtash Mohammad , Davied Matthew , Thompson Todd , Lopez Richard , Lee Michael , Bishop William , Wang Pingfeng , Hu Chao
Published: November 2024

In recent years, academic researchers, industrial designers, and remanufacturers have widely recognized the imperative to integrate remanufacturing considerations into the initial phases of product design to advance sustainability objectives, acknowledging the importance of Design for Remanufacturing (DfRem). However, existing DfRem guidelines and tools largely rely upon experiential insights and qualitative assessments, leaving a gap in the ability to assess the economic and environmental impacts of design choices quantitatively. To bridge this gap, we present a framework for DfRem that facilitates informed design decisions while accounting for potential remanufacturing options. We rigorously assess our framework through a meticulous examination of the design and remanufacturing processes associated with a hydraulic manifold in heavy-duty tractors’ transmissions. Through this industry-relevant case study, we showcase the practical utility of our framework. Conducting analyses guided by our proposed framework, we identify and validate design modifications that could reduce life cycle costs, energy consumption, and emissions. These modifications are tested with plans for integration into future iterations of the hydraulic manifold design, ensuring sustained improvements in sustainability metrics while maintaining performance and reliability standards.
Sustaining Creatively? Investigating the Effects of Creativity and Sustainability-Focused Evaluation Criteria in Design Tasks
Authors: Alsager Alzayed Mohammad , Starkey Elizabeth M. , Ritter Sarah C. , Prabhu Rohan
Published: November 2024

As the need for environmentally sustainable solutions grows, there has emerged an ongoing effort to integrate considerations for the environment throughout the engineering design process. Towards these efforts, several researchers have employed creativity-invoking methods such as alternate uses tasks to encourage the generation of environmentally sustainable solutions. Moreover, these efforts span the design process, ranging from concept generation to concept selection and evaluation. Prior research suggests that external evaluations play an important role in regulating designers’ motivation, and consequently, the outcomes of their design and creative processes. However, little research has investigated how the evaluation criteria used in sustainable design tasks influence designers’ performance. Our aim in this research is to investigate this research gap through an experimental study with novice designers. Specifically, we compared the solutions generated by designers when given a design problem with either creativity-focused evaluation or sustainability-focused evaluation. From the results of our experiment, we see that the evaluation criteria used in the design problem did not impact either the creativity or the environmental sustainability of the participants’ solutions. This finding calls for a deeper investigation into the role of creativity in the generation of environmentally sustainable solutions. This finding also calls for a further study of the potentially conflicting tradeoffs involved in the design of environmentally sustainable solutions.
Prototype2Code: End-to-End Front-End Code Generation From UI Design Prototypes
Authors: Xiao Shuhong , Chen Yunnong , Li Jiazhi , Chen Liuqing , Sun Lingyun , Zhou Tingting
Published: November 2024

UI-to-code technology has streamlined the front-end development process, reducing repetitive tasks for engineers. prior research mainly use design prototypes as inputs, with the effectiveness of the generated code heavily dependent on these prototypes’ quality, leading to compromised robustness. Moreover, these approaches also exhibit shortcomings in code quality, including issues such as disorganized UI structures and the inability to support responsive layouts. To address these challenges, we introduce Prototype2Code, which achieves end-to-end front-end code generation with business demands. For Prototype2Code, we incorporate design linting into the workflow, addressing the detection of fragmented elements and perceptual groups, enhancing the robustness of the generated outcomes. By optimizing the hierarchical structure and intelligently recognizing UI element types, Prototype2Code generates code that is more readable and structurally clearer. To meet responsive design requirements, Prototype2Code primarily supports flexbox layout model, ensuring code compatibility across various device sizes. To validate the efficacy, we compare Prototype2Code with the commercial code generation platform CodeFun and Screenshot-to-code based on GPT-4 with vision. Employing structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), and mean squared error (MSE) for visual similarity assessment, Prototype2Code’s rendered UI effects align most closely with the design prototypes, exhibiting the minimal errors. We also conduct a user study with five experienced front-end engineers, inviting them to review and revise code generated by the three methods. As a result, Prototype2Code surpasses other methods in readability, usability, and maintainability, better meeting the business needs of industrial development.
Design of Lightweight Structures by Reinforcing Thin-Walled Cylinders
Authors: Sun Ruoyu , Mankame Nilesh , Krishnan Girish
Published: November 2024

There is an enduring need for structures that are strong, stiff, and lightweight. In this work, we explore a rational approach to the design of such structures by building on the work of Wegst and Ashby [1]. Wegst and Ashby proposed partitioning the design space of thin-walled cylinders subject to pure bending loads based on the dominant failure mode to guide the selection of circular cross section shapes that maximize strength per unit mass. We extend this work by using the same framework to guide the selection of discrete internal reinforcements for these tubes. The partitioned design space, referred to as the Failure Mode Space (FMS), is generated for a given base tube using finite element analysis. Each branch of the failure envelope in the FMS is associated with a unique failure mode. We investigate three different reinforcement strategies: a) structural foam lining, b) a longitudinal rib and c) a ring stiffener to improve the mass-specific strength of a given base tube. Mass equivalence between the reinforced and un-reinforced tubes is used to project the reinforced tubes onto the FMS generated for the un-reinforced tubes. FE analysis of the reinforced tubes reveals that different reinforcement strategies behave differently in different partitions of the FMS based on the associated failure modes. The approach demonstrated in this preliminary study can be extended to more complex structures under generalized loading conditions.
Three-Dimensional Visualization of Energy Consumption Data in Additive Manufacturing
Authors: Hansen Morten Hejlskov , Vernica Teodor , Mansour Rami , Ramanujan Devarajan
Published: November 2024

This paper addresses the growing interest in design for sustainable manufacturing, focusing particularly on Additive Manufacturing (AM). While AM offers advantages like customized geometries and reduced material usage, there’s a need to address energy consumption in 3D printing beyond the conventional emphasis on material reduction. While previous research has explored various techniques for predicting and reducing the energy consumption of AM processes, there is limited work on guiding designers to generate more energy-efficient designs via localized geometric changes. This paper introduces a method to visualize energy consumption directly on 3D objects, aiming to guide designers in optimizing object shapes for sustainability. The methodology presented in the paper involves several steps: data collection, interpolation of positional points, classification of objects, support structures, and rapid movements. Following this, support and rapid movement energy are allocated to the printed object. Finally, the energy required for printing the object is directly visualized on a 3D model of the object using a mesh interpolation scheme. A use case demonstrating the potential application of the visualization method for reducing printing energy consumption is presented, through introducing a local shape modification to an axle bracket based on the visualization information. This modification resulted in a 7.5% energy reduction in this analyzed region compared to the original design. Thus, results showcase the ability of the proposed visualization method to support sustainability-oriented design for AM, through incorporating local shape modifications.
Exploring Human-Machine Interaction in Level 4 AVS: A Study on Take-Over Maneuver in a Roundabout Scenario
Authors: Boscaro Linda , Fossati Andrea , De Guglielmo Veronica , Galbiati Andrea , Gobbi Massimiliano , Mastinu Giampiero , Previati Giorgio , Sabbioni Edoardo , Signorini Maria Gabriella , Somma Antonella , Subitoni Luca , Uccello Lorenzo
Published: November 2024

Currently, one of the most important challenges in the field of road vehicles concerns the reduction of road accidents and fatalities. The development of new advanced driver assistance or automated driving technologies may contribute to this goal in the future. This research delves into the analysis of Level 4 (L4) automated vehicles (AVs), specifically focusing on the take-over manoeuvre when the AV exits its Operational Design Domain (ODD). It aims to analyse how the take-over changes, considering factors such as the human driver’s state, the machine’s operation, and the output devices used to alert the driver. To carry out the preliminary tests, an urban road network, including a mini-roundabout, was replicated in the VI-WorldSim environment, and real human drivers experienced the simulation through a dynamic driving simulator. Drivers were assessed qualitatively, using questionnaires to analyse their perception of L4 AVs, and quantitatively, examining the take-over time needed and their heart rate to investigate the physiological response. Preliminary results show that participants perceived the simulation as realistic and immersive, and they reported an ease of use of AVs. Furthermore, physiological data highlighted an increase in heart rate upon the start of take-over, validating the cognitive load of the individual. The study is part of the HL4IT project aimed at supporting the development of Level 4 AVs in an Italian traffic environment.
Developing Heuristics for Resource Allocation and Utilization in Systems Design: A Hierarchical Reinforcement Learning Approach
Authors: Gadi Vikranth S. , Szajnfarber Zoe , Panchal Jitesh H.
Published: November 2024

This paper presents an approach that integrates systems engineering principles with reinforcement learning (RL) to solve complex design problems under resource constraints. Product design processes often involve decomposing a large system into interconnected subsystems, with resources allocated across teams responsible for optimizing each subsystem. We formulate this process as a hierarchical multi-armed bandit (MAB) problem, where decisions are made at both the system level (allocating budget across subsystems) and subsystem level (selecting heuristics for sequential information acquisition). We employ Thompson Sampling, a Bayesian RL technique, to concurrently learn effective decision-making policies at each level. This hierarchical RL agent aims to maximize the overall system performance while adhering to fixed budgets for design evaluations. To demonstrate the approach, we present an illustrative example of a race car optimization in The Open Racing Car Simulator (TORCS) environment. Results show that the RL agent can learn to allocate resources strategically, prioritize the most impactful subsystems, and identify effective information acquisition heuristics for each subsystem team. The results also indicate that our method converges to high-performing car configurations with greater efficiency when compared to Bayesian Optimization.
Inverse Design With Conditional Cascaded Diffusion Models
Authors: Habibi Milad , Fuge Mark
Published: November 2024

Adjoint-based design optimizations are usually computationally expensive and those costs scale with resolution. To address this, researchers have proposed machine learning approaches for inverse design that can predict higher-resolution solutions from lower cost/resolution ones. Due to the recent success of diffusion models over traditional generative models, we extend the use of diffusion models for multi-resolution tasks by proposing the conditional cascaded diffusion model (cCDM). Compared to GANs, cCDM is more stable to train, and each diffusion model within the cCDM can be trained independently, thus each model’s parameters can be tuned separately to maximize the performance of the pipeline. Our study compares cCDM against a cGAN model with transfer learning.

Our results demonstrate that the cCDM excels in capturing finer details, preserving volume fraction constraints, and minimizing compliance errors in multi-resolution tasks when a sufficient amount of high-resolution training data (more than 102 designs) is available. Furthermore, we explore the impact of training data size on the performance of both models. While both models show decreased performance with reduced high-resolution training data, the cCDM loses its superiority to the cGAN model with transfer learning when training data is limited (less than 102), and we show the break-even point for this transition. Also, we highlight that while the diffusion model may achieve better pixel-wise performance in both low-resolution and high-resolution scenarios, this does not necessarily guarantee that the model produces optimal compliance error or constraint satisfaction.
Metamodels and Vision Obstruction: A New Lens on Driver Visibility
Authors: Firouzi M. Amin , Bhaskaran Vignesh , Demirel H. Onan , Hoyle Christopher
Published: November 2024

Driver visibility studies, particularly focusing on the impact of A-pillar designs and cutout modifications, are a critical challenge in the automotive industry. Utilizing Gaussian Process Regression (GPR) modeling, we comprehensively analyze how different A-pillar cutout sizes influence visibility in various traffic scenarios. Our research compares two vehicle types, SUVs and sedans, across a spectrum of real-world situation, including interactions with traffic lights, bicycles, and pedestrian crossings. The uniqueness of our approach lies in the application of digital human modeling data to construct surrogate models, which facilitates a nuanced understanding of the relationship between driver anthropometry, visibility, and cutout design. The results reveal a paradox in A-pillar design, where increasing the number of cutouts does not linearly correlate with enhanced visibility, thus challenging conventional design practices. Additionally, the study highlights the multimodal nature of visibility across different driver heights, suggesting the need for a tailored approach in automotive design. Looking forward, our research sets the foundation for future work that aims to optimize cutout designs using techniques like Bayesian Optimization, with a particular focus on improving visibility for drivers of smaller stature. This study contributes significantly to the evolution of automotive design, advocating for a shift towards more inclusive and ergonomic vehicles that cater to the diverse needs of drivers, thereby enhancing overall road safety.
Graph Neural Network-Based Link Prediction for Highly Imbalanced Network Data
Authors: Xiao Yinshuang , Sha Zhenghui
Published: November 2024

The rapid advancement of graph neural networks (GNN) has revolutionized the integration of complex network and neural network models, fostering diverse engineering applications such as the classification of assembly parts and the prediction of customer preferences. GNN-based link prediction (LP), as a representative study, has shown utility in resource allocation and system performance evaluation, as evidenced in the existing literature. However, the inherent challenge of imbalanced network data (i.e., sparse network) from engineering domains poses obstacles to accurate link predictions due to the lack of training data of positive links, leading to biases and reduced performance. In contrast to existing studies that focus on enhancing model architecture, this paper concentrates on exploring preprocessing methods, e.g., the data undersampling strategies, and two post-processing methods for accuracy calculation based on 1) probability threshold-based labeling and 2) probability rank-based labeling, and studies their impacts on the prediction results with a given GNN-based LP model architecture. Real-world network data sourced from shared mobility systems and product market systems, which exhibit various levels of imbalance, are used as test cases. This study contributes to a better understanding of effective data undersampling strategies and post-processing methods for handling imbalanced network data when applying GNN-based LP to real-world complex systems.
Designing Remote Monitoring for Smart Manufacturing Facilities: Hazard Identification and Classification
Authors: Ballestas Caseysimone , Singh Mansidak , Vu Duy , Fillingim Kenton Blane , Goucher-Lambert Kosa
Published: November 2024

This study investigates the process of hazard identification in complex manufacturing environments during the design phase, emphasizing the significance of the design process in developing designs that effectively mitigate hazards in contexts with numerous variables, such as a variety of machines, sensors, actuators, and agents. Through a mixed-methods approach, the objective of this work is to understand how the evolution of design outcomes across various stages might influence a designer’s ability to recognize both standard and novel hazards. To achieve this understanding, an experimental design task was conducted with six designers from a national lab specializing in manufacturing technologies. This approach combined qualitative and quantitative data analysis from a one-hour virtual session with participants. Findings suggest that the complexity of identifying hazards in a high-dimensional design space is challenging within a limited time frame and that the identification of hazards is significantly influenced by the stage of the design task and the initial design decisions, indicating the need for extended time and strategic initial planning in the design process to enhance hazard identification.
Gear Prediction System Based on Ultrasonic Radar and Machine Learning
Authors: Feng Xu , Yang Bo , Yu Liangyao , Hu Ruibo
Published: November 2024

With the rapid development of intelligent vehicles, the emergence of various assisted driving functions has enhanced safety during driving. However, the current mode of shifting in vehicles is mainly through the driver actively operating the gear lever. This mode of shifting not only reduces the usable space inside the vehicle due to the presence of the shifting mechanism but also, because shifting relies more heavily on the driver’s judgment of the environment, incidents of traffic accidents caused by driver’s misoperations and misjudgments occur frequently. To address this issue, this paper proposes a method for predicting the driver’s intention to move forward or backward based on ultrasonic radar. Firstly, a method for detecting obstacles around the vehicle using ultrasonic radar is proposed, which utilizes a pair of ultrasonic radars arranged in an array to locate obstacles around the vehicle based on the principle of elliptical positioning. Based on the location information of obstacles, a simplified vehicle kinematics model is used in conjunction with basic vehicle parameter information to determine the vehicle’s passability. Furthermore, a dataset for different gear shifting targets of the driver in various scenarios is established and trained, equipping the model with the capability to automatically shift gears for the vehicle in different situations. Experimental results show that this method can accurately select the appropriate gear for the vehicle in daily shifting scenarios, thereby enhancing the convenience and safety of driving for the driver in different shifting contexts.
Exploring Latent System Design Description and Requirement Similarities Using Transformer Based Contextual Embeddings
Authors: Carroll Cody L. , Yang Xiaoou , Chen Cheng , Morkos Beshoy
Published: November 2024

Engineering design is heavily influenced by system requirements, as they span the entire design process. Generally, requirements are not utilized to convey system information outside the design process. System information is generally conveyed to stakeholders, such as end users, through generalized descriptions. While requirements and system descriptions both represent the same system to different audiences, the understanding of how each class is related is not well explored, which Large Language Models have now allowed us to do. We employ a method of using pre-trained contextual embeddings from RoBERTa and the resulting UMAP projections to draw conclusions about local and global embedding space characteristics from text-based system information. Though some systems may exhibit overlap or regionalization, results demonstrate that each class (requirements and descriptions) can be utilized to compare similarities between systems from a functional perspective but cannot be directly compared when trying to use requirements and descriptions jointly in the embedding space. The degree to which a system is novel is distinct in the description-based embedding space only by means of the underlying technological principles and not from the form. The implications of this have impacts on designers attempting to leverage LLMs in an attempt to understand how products are differentiable and novel in comparison to other existing systems when either the function of the product is unique, or the physical aspects of the product are significantly different.
Standardized Approach for Assessing Fiber Device Resiliency
Authors: Galligan Conor , Alves Daniel
Published: November 2024

Fiber-attached photonic devices are critical to myriad government systems, e.g. Laser Communication [1], yet most commercially available photonic devices are not tested to the harsh environments required of fielded systems. While there are well-established guidelines for electronic device component testing, such as NASA’s EEE-INST-002 [2], there is no such specification for photonics destined for ruggedized non-telecom environments. This paper presents a specification developed to guide the evaluation of fiber-attached photonic devices for use in ruggedized systems. Component-level testing is specified with the intent of evaluating the likelihood of failure prior to integration into a higher-level assembly, well before system-level environmental testing. This specification was developed leveraging MIT Lincoln Laboratory’s decades of experience successfully upscreening fiber devices for use in delivered government prototypes, as well as surveys of government and industry photonic and electronic device standards. The document a) identifies the technical risks inherent in various component types, b) provides a framework to assess the relevance of manufacturers’ testing, and c) suggests tests that could be performed to burn down the identified risks as a function of key mission parameters such as environment, cost, schedule, and risk tolerance.
Evaluation of Additively Printed Filters on High-Temperature Performance on the Aerojet Platform Using Ceramics Substrate and Laser Ablation Process
Authors: Lall Pradeep , Karakitie Daniel , Soni Ved , Miller Scott
Published: November 2024

Additive processes have gained prominence, employing liquid nanoparticle inks with volatile organic solvent carriers. Printed electronics, known for their advantages over conventional subtractive manufacturing, have found widespread application, particularly in mass-producing antennas for consumer electronics. Aerosol jet printing has been extensively researched for its versatility across orthogonal and traditional 2D surfaces, including compatibility with wire bonding and the development of sensor components crucial for IoT technologies. This research focuses on exploring the performance and process-property interactions of the chips-first fabrication approach with water-based inks on ceramic substrates. Using an iterative approach involving computer-aided design, laser ablation of component pockets, component attachment in pockets, additive printing on fixed components on ceramic substrates with several layers of metallization, and performance testing using frequency response analysis were undertaken. The initial phase meticulously tests the traces printing on a ceramic substrate, followed by the functionality and performance of discrete components. Subsequently, a systematic investigation assessed the circuit realization and the performance. The study aimed to identify key parameters and techniques optimizing the attachment process on ceramic substrates, ensuring the performance and functionality of realized circuits.
Advances in microneedles for delivery of active ingredients of natural herbals
Authors: Fan Lin , Sun Jiang , He Dawei
Published: November 2024

The active ingredients of natural herbs have been extracted to act on different targets in the body to exert multiple effects. However, traditional oral administration and intravenous injection of herbal medicines are also susceptible to many side effects. Transdermal drug delivery by microneedles can overcome the shortcomings of these traditional drug delivery systems. The active ingredients of natural herbs can be delivered to the dermis or the connective tissue layer by five types of microneedles: solid, hollow, coated, dissolving, and hydrogel. Subsequently, the herbal ingredients are delivered to different target points of the body through body circulation to exert their effects. In this study, we classified the microneedles that can deliver the active ingredients of natural herbs and summarized their advantages and disadvantages as well as their preparation methods and applications, to guide the development and clinical applications of other herbal transdermal microneedles.
Sports and the Limits of the Binary: An Introduction
Authors: Posbergh Anna , Baeth Anna , Bekker Sheree , Rochon Roc
Published: November 2024

In this special issue introduction for “Sports and the Limits of the Binary: Trans and Nonbinary Athletes and Equity in Sport,” we provide an overview of the contemporary landscape of trans/nonbinary athlete inclusion, from both academic and nonacademic perspectives. We especially highlight the sociology of sport’s contributions to the literature on this topic, as well as the key foundations and influences from black, queer, decolonial/postcolonial, and disabled scholars. We then introduce ourselves as the guest editors of this special issue and how we arrived at this area of research before closing with brief synopses of each article in this issue.
Targeted antimicrobial regimens for Gram-negative prosthetic joint infections: a prospective multicenter study
Authors: Hanssen Jaap L. J. , van der Wal Robert J. P. , Mahdad Rachid , Keizer Stefan , Delfos Nathalie M. , van der Lugt Joris C. T. , Veldkamp Karin Ellen , Nolte Peter A. , Leendertse Masja , Gelinck Luc B. S. , Mollema Femke P. N. , Schippers Emile F. , Wattel-Louis Hanke G. , Nelissen Rob G. H. H. , Scheper Henk , de Boer Mark G. J.
Published: November 2024

Fluoroquinolones (FQs) are considered the most effective antimicrobial treatment for Gram-negative prosthetic joint infection (GN-PJI). Alternatives are needed due to increasing FQ resistance and side effects. We aimed to compare different targeted antimicrobial strategies for GN-PJI managed by debridement, antibiotics, and implant retention (DAIR) or one-stage revision surgery (1SR) and to review the literature of oral treatment options for GN-PJI. In this prospective, multicenter, registry-based study, all consecutive patients with a PJI caused by a Gram-negative microorganism (including mixed infections with Gram-positive microorganisms), managed with DAIR or 1SR from 2015 to 2020, were included. Minimum follow-up was 1 year. Patients underwent targeted therapy with oral FQ, oral cotrimoxazole, or intravenous or oral β-lactams. Survival analysis was performed with use of Kaplan-Meier and Cox proportional hazards models to identify factors potentially associated with treatment failure. Seventy-four patients who received either FQ (
n
= 47, 64%), cotrimoxazole (
n
= 13, 18%), or β-lactams (
n
= 14, 18%) were included. Surgical strategy consisted of DAIR (
n
= 72) or 1SR (
n
= 2). Median follow-up was 449 days (interquartile range 89–738 days). Failure free survival did not differ between the FQ (72%) and cotrimoxazole (92%) groups (log rank,
P
= 0.13). This outcome did not change when excluding all pseudomonal PJI in the FQ group. Cotrimoxazole is a potential effective targeted antimicrobial therapy for patients with GN-PJI. A randomized controlled trial is needed to confirm the findings of this study.
A conserved interaction between the effector Sca4 and host clathrin suggests additional contributions for Sca4 during rickettsial infection
Authors: Vondrak Cassandra J. , Sit Brandon , Suwanbongkot Chanakan , Macaluso Kevin R. , Lamason Rebecca L.
Published: November 2024

Intracellular bacterial pathogens deploy secreted effector proteins that manipulate diverse host machinery and pathways to promote infection. Although many effectors carry out a single function or interaction, there are a growing number of secreted effectors capable of interacting with multiple host factors. However, few effectors secreted by arthropod-borne obligate intracellular
Rickettsia
species have been linked to multiple host targets. Here, we investigated the conserved rickettsial secreted effector Sca4, which was previously shown to interact with host vinculin in donor cells to promote cell-to-cell spread in the model
Rickettsia
species
R. parkeri
. We discovered that Sca4 also binds the host cell protein clathrin heavy chain (CHC,
CLTC
) via a conserved segment in the Sca4 N-terminus. In mammalian host cells, ablation of
CLTC
expression or chemical inhibition of endocytosis reduced
R. parkeri
cell-to-cell spread
,
indicating that clathrin promotes efficient spread. Unexpectedly, the contribution of CHC to spread was independent of Sca4 and appeared restricted to the recipient host cell, suggesting that the Sca4–clathrin interaction regulates another aspect of the infectious lifecycle. Indeed,
R. parkeri
lacking Sca4 or expressing a Sca4 truncation unable to bind clathrin had markedly reduced burdens in tick cells, hinting at a cell type-specific function for the Sca4–clathrin interaction. Sca4 homologs from diverse
Rickettsia
species also bound clathrin, suggesting that the function of this novel effector–host interaction may be broadly important for rickettsial infection. We conclude that Sca4 has multiple targets during infection and that rickettsiae may manipulate host endocytic machinery to facilitate several stages of their life cycles.
A global lipid map of severe fever with thrombocytopenia syndrome virus infection reveals glycerophospholipids as novel prognosis biomarkers
Authors: Tian Panpan , Zhao Liwei , Zhang Guiting , Chen Shixing , Zhang Wanying , Ou Mingrong , Sun Yidan , Chen Yuxin
Published: November 2024

Severe fever with thrombocytopenia syndrome (SFTS) is a rapidly progressing infectious disease caused by a novel bunyavirus characterized by high fever, thrombocytopenia, and multiple organ damage. While lipids play an important role in viral infections, the specific alterations in lipid metabolism during SFTSV infection remain unclear. This study aimed to elucidate the global lipid metabolic profiles of SFTS patients with mild, severe, and fatal outcomes. A total of 60 SFTS patients, consisting of 30 mild, 15 severe and 15 fatal patients, and 30 healthy controls, were enrolled for the investigation of global lipidomics in serum using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Our findings revealed global alterations in the lipid signature induced by SFTSV infection and further confirmed that the glycerophospholipid metabolism pathway was profoundly affected during the progression of mild, severe, and fatal outcomes in SFTS patients. Importantly, LysoPC (20:0) and LysoPC (P-16:0) are strongly correlated with the clinical parameters of SFTSV infection. Furthermore, we demonstrated the substantial prognostic value of LysoPC (20:0) and LysoPC (P-16:0) by receiver operating characteristic (ROC) curve analysis, providing evidence for their remarkable value as prognostic biomarkers for predicting SFTS clinical outcomes. In particular, LysoPC (20:0) and LysoPC (P-16:0), along with APTT, yielded superior prognostic performance for fatal SFTS [area under the curve (AUC) = 98.4%], outperforming routine clinical parameters. Collectively, our findings revealed the lipidomic landscape after SFTSV infection, which offers new insights into the mechanisms of SFTS disease progression and suggests that targeting lipid metabolism may serve as a potential therapeutic strategy.

IMPORTANCE

This study systematically investigated the lipid landscape profile of SFTS-infected patients with different clinical outcomes. Our results revealed a global alteration in the lipid signature, particularly the glycerophospholipid metabolic pathway, induced by SFTSV infection. Notably, LysoPC (20:0) and LysoPC (P-16:0) presented remarkable prognostic value as novel biomarkers for SFTSV infection and may contribute to the prognosis of SFTS progression and appropriate interventions.
When more sugar is better—a GPI side chain modification results in a less virulent phenotype during a protozoan infection
Authors: Seeber Frank
Published: November 2024

The assembly and function of side chain modifications of glycosylphosphatidylinositol (GPI) units (anchors or free forms) are poorly defined. In a recent study, two enzymes, PIGJ and PIGE, of the protozoan parasite
Toxoplasma gondii
were identified and shown to be involved in the assembly of such GPI side chains (J. A. Alvarez, E. Gas-Pascual, S. Malhi, J. C. Sánchez-Arcila, et al., mBio 15:e00527–24, 2024,
https://doi.org/10.1128/mbio.00527-24
). PIGJ adds N-acetylgalactosamine to the GPI core structure, while PIGE subsequently adds a terminal glucose. Deletion of PIGJ resulted in the loss of the side chain and, strikingly, increased mortality in infected mice, in contrast to PIGE knockouts. Absence of the side chain led to increased binding of the scavenger receptor CD36 to mutant parasites. In galectin-3 knockout mice, the virulent phenotype of side-chain-deficient parasites was largely lost. While the exact mechanisms remain to be elucidated by more experiments, these findings provide the first evidence for the importance of GPI side chains in parasite-host interactions
in vivo
.
Complete genome sequence of
Marinomonas
sp. strain THO17 isolated from the leaf surface of the seagrass (
Thalassia hemrichii
)
Authors: Tsuchiya Yuki , Yokoyama Ushio , Takahashi Reiji , Nakagawa Tatsunori
Published: November 2024

Here, we report the genome sequence of the
Marinomonas
sp. strain THO17. The assembled genome consisted of a single circular chromosome of 3,920,899 bp, with a 43.6% G+C content. Genome analysis revealed that strain THO17 potentially interacts with marine plants.
Dynamics and biodiversity of microbial community among seasons in Shanxi mature vinegar fermentation by semisolid-solid process
Authors: Li Chen , Kou Rong , Jia Yingying , Fan Xiaojun , Shi Ying , Chen Qihe
Published: November 2024

The dynamic succession and seasonal characteristics of microbiota throughout the Shanxi mature vinegar (SMV) fermentation by the semisolid-solid process were explored using high-throughput sequencing techniques. The results showed that the richness and diversity of fungi were higher than those of bacteria in a complete seasonal SMV fermentation cycle, and the microbial community was dominated by 11 taxa of bacteria and 16 taxa of fungi. In all four seasons, lactic acid bacteria and acetic acid bacteria were the dominant bacteria, while the dominant fungi varied.
Saccharomyces
and
Pichia
played an important role in spring.
Aspergillus
and
Issatchenkia
were enriched in the summer.
Kazachstania
was the dominant microorganism in autumn. While
Mesenteroides
and
Meyerozyma
were enriched in winter. Unweighted pair group method with arithmetic mean (UPGMA) cluster analysis demonstrated that seasonality had a more decisive impact on microbiota composition than the fermentation stage within a season, and the microbiota structure in summer was significantly different from that in the other three seasons. Combined with the highest operational taxonomic units (OTUs) percentage (37%) of summer fungi in the Venn diagrams, it is speculated that the specific fungi may be the root cause for the relatively low SMV quality in summer. This work provided critical insights into the dynamic succession of the microbial community in SMV fermentation from a seasonality view, and the results could enrich our understanding of the microbiota involved in SMV fermentation and guide process control.

IMPORTANCE

Understanding the changes in microbial communities across different seasons is crucial for ensuring the quality of Shanxi mature vinegar (SMV) by the semisolid-solid process. In a complete seasonal cycle, the richness and diversity of fungi were higher than those of bacteria. The microbial community in summer fermentation was significantly different compared to the other three seasons. For example, the dominant microorganisms such as
Acetobacter
and
Lactobacillus
decreased in summer. Screening or modifying this group of bacteria to enhance their tolerance to high fermentation temperature is an approach to improve industrial SMV fermentation. Through co-occurrence network analysis, eight highly connected genera were identified, which may play important roles in ecosystem stability. These results also lay a theoretical foundation for the further development of multi-microbial co-fermentation. This work provides an understanding of SMV fermentation from a seasonal perspective and offers new guidance for the process control of grain vinegar brewing.
A chlorine isotope transect across Sudbury Basin (Canada) impact deposits reveals systematic isotope fractionation
Authors: Barrett T.J. , Nagashima K. , Huss G.R. , Boyce J.W. , Robinson K.L. , Kring D.A.
Published: November 2024

Large-scale impacts are known to have a significant effect on volatile systematics (e.g., hydrogen and chlorine) owing to syn- and post-shock pressures and temperatures allowing for ready volatile loss and isotopic fractionation. We determined the Cl isotopic composition and [Cl] and [H2O] for apatite from 10 samples of the Sudbury impact structure in Canada. The high [Cl] and invariant δ37Cl values in the lower norite are attributed to footwall assimilation in agreement with recent Zn and Pb data. The granophyre, the top of the Sudbury Igneous Complex, displays loss and fractionation of Cl (up to +6.26‰) indicative of degassing under a high gas pressure regime with high [H2O] further buffering isotope fractionation. Similar impacts on dry, airless bodies such as the Moon may have permitted greater amounts of isotopic fractionation, supporting extremely fractionated lunar materials as evidence for the large-scale impact-derived degassing hypothesis. The modest fractionation (up to +8.15‰) and morphologically distinct apatite of the Onaping Formation can be explained by post-impact hydrothermal alteration.
Supplemental Material: Distinctive source and hydration state of gold-ore–forming arc magmas
Authors: Mafra Carolina , Loucks Robert R. , Fiorentini Marco L.
Published: November 2024

Datasets used to plot fertility indicators ratios. Description of samples selection criteria, filtering data, and derivations of fertility indicators.  
Qualitative service evaluation of a multimodal pilot service for early detection of liver disease in high-risk groups: ‘Alright My Liver?’
Authors: Archer Ann Jane , May Tom , Bowers Hannah , Kesten Joanna , Tilden Sally , Abeysekera Kushala , Gordon Fiona H , Hickman Matthew , Yardley Lucy
Published: November 2024

Objective

Liver disease is a growing cause of premature death in the UK. The National Health Service in England (NHS England) has funded regional early detection programmes through Community Liver Health Check pilots. ‘Alright My Liver?’ is Bristol and Severn’s pilot service offering early detection of liver disease through screening events serving populations at risk, including people with a history of drug or alcohol use, type 2 diabetes and obesity. The service offers point-of-care testing for liver disease and a supported follow-up process.

Methods

Semistructured interviews were conducted with 14 service users and six service providers over a 6-month period using diversity sampling. Topic guides encouraged discussion of experiences of the service as well as barriers and facilitators to accessing the service. Data were analysed using thematic analysis, and positive and negative comments pertaining to the service were collated in a ‘table of changes’ to inform optimisation.

Results

Three main themes were identified: (1) motivations for engagement, (2) experience of the service and (3) health impacts. Key motivations for engagement were screening as a novel opportunity, a response to immediate health concerns or as reassurance. Service users commented on its convenience and that staff interactions were warm and informative. Some felt that follow-up could be more intensive. Impacts varied depending on perceived risk factors and screening results but generally involved stating a commitment to healthy lifestyle changes, including reducing alcohol use.

Conclusion

Targeted screening for liver disease in high-risk groups through this pilot service was deemed an appropriate and accessible intervention, with important optimisations identified.