bluuebunny/crossref_metadata_2025_split huggingface dataset:
Methodological Approaches for Measuring the Association Between Heat Exposure and Health Outcomes: A Comprehensive Global Scoping Review
Authors: Graffy Peter M. , Sunderraj Ashwin , Visa Maxime A. , Miller Corinne H. , Barrett Benjamin W. , Rao Sheetal , Camilleri Sara F. , Harp Ryan D. , Li Chuxuan , Brenneman Anne , Chan Jennifer , Kho Abel , Allen Norrina , Horton Daniel E. 
Published: September 2024

AbstractObjective: To synthesize the methodologies of studies that evaluate the impacts of heat exposure on morbidity and mortality. Methods: Embase, MEDLINE, Web of Science, and Scopus were searched from date of inception until 1 March 2023 for English language literature on heat exposure and health outcomes. Records were collated, deduplicated and screened, and full texts were reviewed for inclusion and data abstraction. Eligibility for inclusion was determined as any article with climate‐related heat exposure and an associated morbidity/mortality outcome. Results: Of 13,136 records initially identified, 237 articles were selected for analysis. The scope of research represented 43 countries, with most studies conducted in China (62), the USA (44), and Australia (16). Across all studies, there were 141 unique climate data sources, no standard threshold for extreme heat, and 200 unique health outcome data sources. The distributed lag non‐linear model (DLNM) was the most common analytic method (48.1% of studies) and had high usage rates in China (68.9%) and the USA (31.8%); Australia frequently used conditional logistic regression (50%). Conditional logistic regression was most prevalent in case‐control studies (5 of 8 studies, 62.5%) and in case‐crossover studies (29 of 70, 41.4%). DLNMs were most common in time series studies (64 of 111, 57.7%) and ecological studies (13 of 20, 65.0%). Conclusions: This review underscores the heterogeneity of methods in heat impact studies across diverse settings and provides a resource for future researchers. Underrepresentation of certain countries, health outcomes, and limited data access were identified as potential barriers.
Intrinsic Organic Carbon Could Contribute to the Unexplained Optical Measurements of Fresh Soot
Authors: Luo Jie , Hu Miao , Zhang Qixing , Li Congcong , Liu Jia , He Hao , Li Kaitao , Sun Yuping 
Published: September 2024

AbstractPrevious modeling studies have not properly explained the measured mass absorption cross section (MAC) at 550 nm, the linear backscattering depolarization ratio (LDR) at 355 and 532 nm, and the scattering matrix of soot at 532 nm. In this work, we attempt to use a black carbon (BC) model with an intrinsic organic carbon (OC) coating to explain the large MAC, large LDR, and measured scattering matrix. Our results show that the bare fractal BC model is not able to explain MAC, LDR, and scattering matrix simultaneously and that the modeling values do not cover the measurement range. This study shows that the modeled LDR and scattering matrix can cover the measurement range if we constrain the MAC of the BC in the measurement range by the intrinsic OC coating when we consider the effects of monomer radius, monomer number, and monomer overlap simultaneously. Therefore, intrinsic OC coating can be a significant source of uncertainty in the optical properties of fresh soot.
Pharmacologic or genetic targeting of peripheral nerves prevents peri-articular traumatic heterotopic ossification
Authors: Zhu Manyu , Yea Ji-Hye , Li Zhao , Qin Qizhi , Xu Mingxin , Xing Xin , Negri Stefano , Archer Mary , Mittal Monisha , Levi Benjamin , James Aaron W. 
Published: September 2024

AbstractHeterotopic ossification (HO) is a pathological process that commonly arises following severe polytrauma, characterized by the anomalous differentiation of mesenchymal progenitor cells and resulting in the formation of ectopic bone in non-skeletal tissues. This abnormal bone growth contributes to pain and reduced mobility, especially when adjacent to a joint. Our prior observations suggested an essential role of NGF (Nerve Growth Factor)-responsive TrkA (Tropomyosin Receptor Kinase A)-expressing peripheral nerves in regulating abnormal osteochondral differentiation following tendon injury. Here, we utilized a recently developed mouse model of hip arthroplasty-induced HO to further validate the role of peripheral nerve regulation of traumatic HO. Nerve ingrowth was either modulated using a knockin transgenic animals with point mutation in TrkA, or local treatment with an FDA-approved formulation of long acting Bupivacaine which prevents peripheral nerve growth. Results demonstrate exuberant sensory and sympathetic nerve growth within the peri-articular HO site, and that both methods to reduce local innervation significantly reduced heterotopic bone formation. TrkA inhibition led to a 34% reduction in bone volume, while bupivacaine treatment resulted in a 50% decrease. Mechanistically, alterations in TGFβ and FGF signaling activation accompanied both methods of local denervation, and a shift in macrophages from M1 to M2 phenotypes was observed. In sum, these studies reinforce the observations that peripheral nerves play a role in the etiopathogenesis of HO, and that targeting local nerves represents a potential therapeutic approach for disease prevention.
Drug-induced change in transmitter identity is a shared mechanism generating cognitive deficits
Authors: Pratelli Marta , Hakimi Anna M. , Thaker Arth , Jang Hyeonseok , Li Hui-quan , Godavarthi Swetha K. , Lim Byung Kook , Spitzer Nicholas C. 
Published: September 2024

AbstractCognitive deficits are long-lasting consequences of drug use, yet the convergent mechanism by which classes of drugs with different pharmacological properties cause similar deficits is unclear. We find that both phencyclidine and methamphetamine, despite differing in their targets in the brain, cause the same glutamatergic neurons in the medial prefrontal cortex of male mice to gain a GABAergic phenotype and decrease expression of their glutamatergic phenotype. Suppressing drug-induced gain of GABA with RNA-interference prevents appearance of memory deficits. Stimulation of dopaminergic neurons in the ventral tegmental area is necessary and sufficient to produce this gain of GABA. Drug-induced prefrontal hyperactivity drives this change in transmitter identity. Returning prefrontal activity to baseline, chemogenetically or with clozapine, reverses the change in transmitter phenotype and rescues the associated memory deficits. This work reveals a shared and reversible mechanism that regulates the appearance of cognitive deficits upon exposure to different drugs.
Exploring microbial diversity and biosynthetic potential in zoo and wildlife animal microbiomes
Authors: Schmartz Georges P. , Rehner Jacqueline , Schuff Miriam J. , Molano Leidy-Alejandra G. , Becker Sören L. , Krawczyk Marcin , Tagirdzhanov Azat , Gurevich Alexey , Francke Richard , Müller Rolf , Keller Verena , Keller Andreas 
Published: September 2024

AbstractUnderstanding human, animal, and environmental microbiota is essential for advancing global health and combating antimicrobial resistance (AMR). We investigate the oral and gut microbiota of 48 animal species in captivity, comparing them to those of wildlife animals. Specifically, we characterize the microbiota composition, metabolic pathways, AMR genes, and biosynthetic gene clusters (BGCs) encoding the production of specialized metabolites. Our results reveal a high diversity of microbiota, with 585 novel species-level genome bins (SGBs) and 484 complete BGCs identified. Functional gene analysis of microbiomes shows diet-dependent variations. Furthermore, by comparing our findings to wildlife-derived microbiomes, we observe the impact of captivity on the animal microbiome, including examples of converging microbiome compositions. Importantly, our study identifies AMR genes against commonly used veterinary antibiotics, as well as resistance to vancomycin, a critical antibiotic in human medicine. These findings underscore the importance of the ‘One Health’ approach and the potential for zoonotic transmission of pathogenic bacteria and AMR. Overall, our study contributes to a better understanding of the complexity of the animal microbiome and highlights its BGC diversity relevant to the discovery of novel antimicrobial compounds.
Optical nonlinearity of thin film lithium niobate: devices and recent progress
Authors: Wang Lei , Du Haoyang , Zhang Xiuquan , Chen Feng 
Published: September 2024

Abstract
Thin-film lithium niobate (TFLN), also known as lithium niobate on insulator, is an important integrated optical platform due to its broad transparency window (from ultraviolet to mid-infrared) and exceptional nonlinear optical (NLO) properties. TFLN is a revolutionary technology that revitalizes micro/nano photonics based on LN, which holds prime importance in on-chip frequency conversion owing to its remarkable NLO properties. This review focuses on the optical nonlinearity of thin film lithium niobate and its applications in integrated optics. We commence with a brief overview of the TFLN platform. Followed by an introduction to the common device structures. We then present the recent advancements of TFLN in NLO frequency conversion, including χ
(2) based optical frequency generation processes (second harmonic generation, sum frequency generation, and difference frequency generation, etc), frequency comb generation, and supercontinuum generation, etc. Finally, we propose future prospects for nonlinear photonic integrated circuits based on the TFLN platform.
Cyclicity of slow–fast cycles with one self-intersection point and two nilpotent contact points*
Authors: Yao Jinhui , Huang Jicai , Huzak Renato , Ruan Shigui 
Published: September 2024

Abstract
In this paper, we study the cyclicity of slow–fast cycles with one self-intersection point and two nilpotent contact points in planar slow–fast systems, where the nilpotent contact point is a jump point or a slow–fast Hopf point. These slow–fast cycles can be classified into three cases based on the two nilpotent contact points: (i) both are generic jump points, (ii) one is a generic jump point and the other is a slow–fast Hopf point, and (iii) both are slow–fast Hopf points. By using slow divergence integrals and entry–exit functions, we show that the cyclicity of slow–fast cycles with one self-intersection point and two generic jump points (or one generic jump point and one slow–fast Hopf point) is at most two, and the cyclicity of slow–fast cycles with one self-intersection point and two slow–fast Hopf points is at most three under some specific conditions. Finally, we apply the main results to two predator-prey models.
Recent progress in soft robots: principles, designs, and applications
Authors: Li Yuxin , Wang Hainuo , Li Xin , Wang Yu , Lu Sheng , Tang Qifu , Luo Jiufei , Yang Ping-an 
Published: September 2024

Abstract
With advancements in the manufacturing industry persisting, soft robots have experienced rapid development, progressively emerging as a pivotal focus in the future trajectory of robotic technology. As a new type of robot technology, soft robots have significant differences from traditional robots in terms of principles, driving methods, design control, and other aspects. Here, we sort out and summarize the latest developments in soft robotics. Firstly, typical principles and driving methods were introduced, including rope drive, variable stiffness drive (gas negative pressure, intelligent fluids, etc), electromagnetic drive, and so on. Secondly, the main materials and characteristics of soft robots are analyzed, including hydrogels, shape memory alloys, photosensitive materials, electromagnetic rheological elastomer, biodegradable materials, etc. Then, typical soft robot structures and processing methods were introduced, including fluid static skeleton structures, muscle fluid static skeleton structures, and others. Finally, the problems of soft robots are analyzed, and the future development direction and importance are summarized. This paper highlights the recent progress in smart functional materials, typical biomimetic structures, and assembly methods applicable to soft robots, which is expected to assist the development and advancement of the next generation of soft robots.
Design and manufacturing of mechanical parts based on CAD and CAM technology
Authors: Ye Li 
Published: September 2024

Abstract
This paper comprehensively discusses the core applications and innovation strategies of CAD/CAM technology in mechanical parts manufacturing, with a special focus on automatic path planning, CNC programming, multi-axis and high-speed machining technology, as well as intelligent upgrading of quality control and production management. By introducing advanced models such as Deep Graph Neural Reinforcement Learning Path Planner (DGNet-RPP), it demonstrates how to utilize the fusion of Deep Reinforcement Learning and Graph Neural Network to adaptively optimize the tool path planning of complex parts to ensure machining efficiency and accuracy. Meanwhile, the importance of optimization and post-processing techniques for NC programming, such as simulated annealing and ant colony optimization, is emphasized to improve machining efficiency and code adaptability. The implementation of multi-axis machining and high-speed machining technology has greatly promoted the progress of complex parts machining accuracy and surface quality, especially in high-end manufacturing fields such as aerospace. In addition, the article also explains the key role of CAM systems in quality control and production scheduling, how to ensure the quality of parts through real-time monitoring and data analysis, as well as through advanced planning and scheduling to optimize the production process, reduce costs, and improve market responsiveness.
Estimation of SOC for Li-ion battery-powered three-wheeled electric vehicle using machine learning methods
Authors: Rout Smitanjali , Samal Sudhansu Kumar , Mahapatro Soumya Ranjan 
Published: September 2024

Abstract
The Battery Management System (BMS) serves as the heart of the electric vehicle system, in which estimating the state of charge (SOC) is the crucial part of the BMS to ensure the durability, reliability, and sustainability of the battery pack. Due to its nonlinear characteristics, accurately estimating the SOC for a slow degradation of the charge is highly cumbersome. The literature provides a series of machine learning algorithms (MLA) to estimate and predict the SOC of lithium-ion (Li-ion) battery systems for electric vehicle (EV) applications. The literature has proposed various MLA, coulomb counting, and different Kalman filter methods to address this challenge and estimate the SOC of Li-ion battery systems for EV applications. This research looks at the differences and similarities between the coulomb counting method, the unscented Kalman filter method, and a number of machine learning algorithms. These include linear regression, polynomial linear regression, support vector regression, decision trees, random forests, artificial neural networks (ANN), and long short-term memory (LSTM). The goal is to assess the MLAs’ accuracy in estimating battery SOC. Analyzing model errors optimizes the battery’s performance parameter. We identify ANN and LSTM as the two most efficient methods for accurate SOC estimation in an EV-operated BMS system by evaluating the performance indices of the aforementioned machine learning methodologies. Once again, the LSTM model for SOC estimation has proven to be highly accurate in analyzing the discrepancy between the actual and predicted traveling ranges of the designed prototype. We design a MATLAB/SIMULINK EV powertrain by collecting real-time data from the Li-ion battery pack, analyzing the SOC variation data, and using the previously mentioned MLA in the Python platform to estimate the SOC and its accuracy. It highlights the effectiveness of advanced MLAs in improving SOC estimation, thereby enhancing the performance and reliability of EV battery systems.
Spatiotemporal statistical features of velocity responses to traffic congestions in a local motorway network
Authors: Wang Shanshan , Schreckenberg Michael , Guhr Thomas 
Published: September 2024

Abstract
The causal connection between congestions and velocity changes at different locations induces various statistical features, which we identify and measure in detail. We carry out an empirical analysis of large-scale traffic data on a local motorway network around the Breitscheid intersection in the North Rhine-Westphalia, Germany. We put forward a response function which measures the velocity change at a certain location versus time conditioned on a congestion at another location. We use a novel definition of the corresponding congestion indicator to ensure causality. We find that the response of velocities to the congestion exhibits phase changes in time. A negative response at smaller time lags transforms into positive one at larger time lags, implying a certain traffic mechanism. The response decays as a power law with the distance. We also identify a scaling property leading to a collapse of the response functions on one curve.
AI-based antibody discovery platform identifies novel, diverse, and pharmacologically active therapeutic antibodies against multiple SARS-CoV-2 strains
Authors: Loomis Cristina Moldovan , Lahlali Thomas , Van Citters Danielle , Sprague Megan , Neveu Gregory , Somody Laurence , Siska Christine C , Deming Derrick , Asakawa Andrew J , Amimeur Tileli , Shaver Jeremy M , Carbonelle Caroline , Ketchem Randal R , Alam Antoine , Clark Rutilio H 
Published: September 2024

Abstract

Background
We are entering a new era of antibody discovery and optimization where machine learning (ML) processes will become indispensable for the design and development of therapeutics.

Methods
We have constructed a Humanoid Antibody Library for the discovery of therapeutics that is an initial step towards leveraging the utility of artificial intelligence and ML. We describe how we began our validation of the library for antibody discovery by isolating antibodies against a target of pandemic concern, SARS-CoV-2. The two main antibody quality aspects that we focused on were functional and biophysical characterization.

Results
The applicability of our platform for effective therapeutic antibody discovery is demonstrated here with the identification of a panel of human monoclonal antibodies that are novel, diverse, and pharmacologically active.

Conclusions
These first-generation antibodies, without the need for affinity maturation, exhibited neutralization of SARS-CoV-2 viral infectivity across multiple strains and indicated high developability potential.
Use of local treatment in managing infections: Focus on antimicrobial locks, beads, and cement
Authors: Kufel Wesley D , Kufel Julia E 
Published: September 2024

Abstract

Purpose
The purpose of this review is to describe important considerations with local antimicrobial therapies such as locks, beads, and cement for adjunctive infection management or prevention.

Summary
Local delivery of antimicrobials with locks, beads, and cement has been used for infection management with retained devices in an effort to improve clinical success. However, their use has been controversial due to conflicting clinical data and logistical issues. Antimicrobial lock therapy (ALT) has been used for both adjunctive treatment and prevention of catheter-related bloodstream infections for certain pathogens and based on patient-specific scenarios. ALT has been a controversial method for sterilizing the catheter lumen by delivering high concentrations of antibiotics with or without heparin into the catheter for prolonged durations. Studies differ regarding the selection and concentrations of antibiotics, dwell duration, presence of heparin in the ALT, clinical outcomes/definitions, and use for prevention or treatment of catheter-related bloodstream infections. Antibiotic beads and cement have been used for various surgical procedures but are predominately considered in orthopedic surgeries. Despite the widespread use of the antibiotic-loaded bone cement in orthopedics, studies differ regarding the selection and concentrations of antibiotics, clinical outcomes/definitions, and use for prevention or treatment of infections.

Conclusion
Although antimicrobial locks, beads, and cement are commonly used for adjunctive treatment or prevention of infections, more data are needed to support their use to provide clinical efficacy and safety with consistent antimicrobial selection and logistics.
Veno-arterial extracorporeal membrane oxygenation supported transcatheter aortic valve implantation in a high-risk COVID-19 patient: a comprehensive case report
Authors: Vizzari Giampiero , De Ferrari Tommaso , Costa Francesco , Mancini Nastasia , Franzino Marco , Ceresa Fabrizio , Patanè Francesco , Micari Antonio 
Published: September 2024

Abstract

Background
The sudden onset of heart failure in high-risk transcatheter aortic valve implantation (TAVI) candidates poses significant challenges, necessitating meticulous planning and consideration of mechanical circulatory support options. Nevertheless, existing data on the efficacy and safety of mechanical circulatory support in this context are limited, along with criteria for patient selection.

Case summary
An 87-year-old patient, with severe low-flow low-gradient aortic stenosis, presented with acute heart failure and concurrent COVID-19 pneumonia. Despite initial conservative management, her clinical condition deteriorated, requiring inotropic support. The decision was made to perform a rescue TAVI procedure with veno-arterial extracorporeal membrane oxygenation (ECMO) support. The patient underwent successful TAVI while managing complications, including cardiac arrest, with haemodynamic support from veno-arterial ECMO. Post-procedure, the patient showed improved cardiac function and was discharged in stable condition.

Discussion
This case underscores the significance of strategic patient selection, proactive haemodynamic management, and the judicious use of veno-arterial ECMO in high-risk TAVI, particularly in complex scenarios involving acute heart failure and respiratory insufficiency, exacerbated by COVID-19. It highlights the challenges and critical decision points in TAVI planning, emphasizing the need for further research and standardized guidelines to refine indications for prophylactic mechanical circulatory support in TAVI procedures.