bluuebunny/crossref_metadata_2025_split huggingface dataset:
Risk factors analysis of Flexible Ureteroscopic Lithotripsy with UTI and construction of clinical prediction model
Authors: Xiong Feng , Zhang Pan , Fan Xiangyi , Qiao Hongliang , Cao Zhongjun , Chen Xiaobo 
Published: April 2024

Abstract
Purpose
The flexible ureteroscope offers advantages such as safety, minimally invasive procedures, quick recovery, and a high rate of stone removal. It has become a standard method for treating ureteral stones as well as small and medium-sized kidney stones. UTI is one of the most common postoperative complications that can lead to sepsis, systemic inflammatory response syndrome, urological sepsis, and even septic shock. Our aim is to analyze the risk factors for UTI following ureteroscopic lithotripsy and to develop corresponding clinical prediction models.
Methods
A retrospective analysis was conducted on patients who underwent FURS surgery for urinary tract stones at our hospital from January 2021 to January 2023. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for postoperative infection and to develop the corresponding Nomogram prediction model.
Results
In total, 560 patients underwent flexible ureteroscopic lithotripsy (FURL) in our hospital, including 111 patients who developed postoperative UTI, resulting in an incidence rate of 19.8%. Analysis of the multivariate logistic regression data showed that renal dysfunction[OR = 2.103(95%CI:1.134–3.907),P = 0.018],positive preoperative urine culture [OR = 6.070(95%CI:1.800-20.474),P = 0.004], positive urinary nitrate [OR = 3.206 (95%CI: 1.599–6.429),P = 0.001],IL-6 > 5.3pg/ml[OR = 6.876(95%CI:3.734–12.661),P < 0.001],uric acid > 430 umol /L [OR = 2.024(95%CI:1.088–3.765),P = 0.026], ureteral stricture[OR = 3.174(95%CI:1.660–6.070), P < 0.001] were independent risk factors for UTI in patients after flexible ureteroscopy. The area under the ROC curve of the constructed nomogram prediction model is 0.89 (95% CI: 0.876–0.937). The concordance index reached 0.841.
Conclusion
Renal dysfunction, positive preoperative urine culture, positive urine nitrite, IL-6 > 5.3 pg/ml, uric acid > 430 umol/L, and ureteral stenosis were identified as risk factors for UTI after flexible ureteroscopic lithotripsy. The nomogram prediction model has high clinical value in the prediction of UTI.
Cold-water coral mortality under ocean warming is associated with pathogenic bacteria
Authors: Chemel Mathilde , Peru Erwan , Binsarhan Mohammad Mutlaq , Logares Ramiro , Lartaud Franck , Galand Pierre E. 
Published: April 2024

Abstract

Cold-water corals form vast reefs that are highly valuable habitats for diverse deep-sea communities. The deep ocean is, however, warming and it’s therefore essential to assess the resilience of cold-water corals to future conditions. Here we investigate the effects of elevated temperatures on the cold-water coral Lophelia pertusa (now named Desmophyllum pertusum) from the north east Atlantic Ocean at the holobiont level, the coral host and its microbiome. We show that at temperature increases of + 3 and + 5°C, L. pertusa exhibits significant mortality concomitant with changes in its microbiome composition. In addition, a metagenomic approach revealed the presence of genes markers for bacterial virulence factors suggesting that coral death was due to infection by pathogenic bacteria. Interestingly, different coral colonies had different survival rates, as well as colony-specific microbiome signatures, indicating strong colony variability in response to warming waters. Our results suggest that L. pertusa can only survive a temperature increase of < 3°C over the long term. Regional variations in deep-sea temperature increase should therefore be considered in future estimates of the global distribution of cold-water corals.
DDANet: Deep DenseAttention Learning-Based for Intrusion Detection in Industrial Control Systems
Authors: Sharma Ankita , Sahu Rakesh , Bajaj Rohit 
Published: April 2024

Abstract

Industrial control systems (ICSs) are integrated with communication networks and the Internet of Things (IoT), they become more susceptible to cyberattacks, which can have catastrophic effects. However, the lack of sufficient high-quality attack examples has made it very difficult to withstand cyber threats like large-scale, sophisticated, and heterogeneous ICS. Conventional intrusion detection systems (IDSs), designed primarily to assist IT systems, rely heavily on pre-established models and are mostly trained on particular types of cyberattacks. Furthermore, most intrusion detection systems suffer from low accuracy and high false-positive rates when used because they fail to take into account the imbalanced nature of datasets and feature redundancy. In this article,the Deep DenseAttention Learning Model (DDAnet), a novel and inventive deep learning scheme described in this article, is intended to identify and detect cyber attacks that target industrial control systems. The intrusion activity is regarded as a densenet-based network intrusion detection model with an attention model along with a random forest as a classifier. The DDAnet learning scheme has been extensively tested on a real industrial control system dataset. The results of these experiments reveal the great effectiveness of the scheme in identifying different types of data injection attacks on industrial control systems. Furthermore, the scheme has been found to have superior performance compared to state-of-the-art schemes and existing methodologies. The proposed strategy is a versatile method that can be easily deployed in the current ICS infrastructure with minimal effort.
Temporal clustering of streamflow extremes and relevance to flood insurance claims: a stochastic investigation for the contiguous USA
Authors: Papoulakos Konstantinos , Iliopoulou Theano , Dimitriadis Panayiotis , Tsaknias Dimosthenis , Koutsoyiannis Demetris 
Published: April 2024

Abstract

Recent research highlights the importance of Hurst-Kolmogorov dynamics (else known as long-range dependence), characterized by strong correlation and high uncertainty in large scales, in flood risk assessment, particularly in the dynamics of flood occurrence and duration. While several catastrophe modeling professionals nowadays incorporate scenarios that account for previous historical extreme events, traditional flood risk estimation assumes temporal independence of such events, overlooking the role of long-range dependence that has been observed in hydrometeorological processes. This study delves into the validity implications of these assumptions, investigating both the empirical properties of streamflow extremes from the US-CAMELS dataset and the ones of flood insurance claims from the recently published FEMA National Flood Insurance Program database. Analyzing the US-CAMELS dataset, we explore the impact of streamflow’s clustering dynamics on return periods, event duration, and severity of the over-threshold events and corroborate empirical findings with stochastic simulations reproducing the observed dynamics. The association between the observed flood event properties, considered as proxies of collective risk, and the FEMA aggregate flood insurance claims is then investigated. New insights are derived with respect to the strength of their linkage and its spatial variability, which are essential to accurate flood insurance and reinsurance practices.
Energetic constraints of metal-reducing bacteria as biocatalysts for microbial electrosynthesis
Authors: Miller Shaylynn , Ford Kathryne C. , Cross Megan C. Gruenberg , TerAvest Michaela A. 
Published: April 2024

Abstract
Background
As outlined by the Intergovernmental Panel on Climate Change, we need to approach global net zero CO2 emissions by approximately 2050 to prevent warming beyond 1.5°C and the associated environmental tipping points. Future MES systems could decrease net CO2 emissions by capturing it from industrial sources. Microbial electrosynthesis (MES) is a process where electroactive microorganisms convert the carbon from CO2 and reduction power from a cathode into reduced organic compounds. However, no MES system has attained an efficiency compatible with a financially feasible scale-up. To improve MES efficiency, we need to consider the energetic constraints of extracellular electron uptake (EEU) from an electrode to cytoplasmic electron carriers like NAD+. In many microbes, EEU to the cytoplasm must pass through the respiratory quinone pool (Q-pool). However, electron transfer from the Q-pool to cytoplasmic NAD+ is thermodynamically unfavorable. Here, we model the thermodynamic barrier for Q-pool dependent EEU using the well-characterized bidirectional electron transfer pathway of Shewanella oneidensis, which has NADH dehydrogenases that are energetically coupled to proton-motive force (PMF), sodium-motive force (SMF), or uncoupled. We also tested our hypothesis that Q-pool dependent EEU to NAD+ is ion-motive force (IMF)-limited in S. oneidensis expressing butanediol dehydrogenase (Bdh), a heterologous NADH-dependent enzyme. We assessed membrane potential changes in S. oneidensis + Bdh on a cathode at the single-cell level pre to post injection with acetoin, the substrate of Bdh.
Results
We modeled the Gibbs free energy change for electron transfer from respiratory quinones to NADH under conditions reflecting changes in membrane potential, pH, reactant to product ratio, and energetically coupled IMF. Of the 40 conditions modeled for each method of energetic coupling (PMF, SMF, and uncoupled), none were thermodynamically favorable without PMF or SMF. We also found that membrane potential decreased upon initiation of EEU to NAD+ for S. oneidensis on a cathode.
Conclusions
Our results suggest that Q-pool-dependent EEU is both IMF-dependent and is IMF-limited in a proof-of-concept system. Because microbes that rely on Q-pool-dependent EEU are among the most genetically tractable and metabolically flexible options for MES systems, it is important that we account for this thermodynamic bottleneck in future MES platform designs.
Deep peroneal nerve block may be a new treatment way for plantar fasciitis
Authors: Lin Ping , Ying Yujuan , Zhong Chaoping , Zhu Yuanfang , Gao Yang 
Published: April 2024

Abstract
Background
Toe dorsiflexion is considered to be an important cause of plantar fasciitis, and the deep peroneal nerve (DPN) is the only nerve innervating the ankle joint and toe dorsiflexion. We hypothesized that blocking the DPN at the lower part of the tibia can reduce dorsiflexion of the toes at rest and in motion, thereby reducing plantar fascia tension, and will not affect the patient's normal activities.
Methods
Under ultrasound guidance, a DPN block was performed 2 cm above the ankle joint. Blocking twice a week for two consecutive weeks. The VAS pain scores at rest and movement were evaluated before and after treatment. The toe dorsiflexion angle change was observed in a static state, and the plantar fascia thickness changes before and after the block were observed by ultrasound to reflect the plantar fascia tension.
Results
We analyzed the location of DNP block on the specimen, and implemented DNP block in 18 patients with unilateral plantar fasciitis. DPN block reduces the heel pain in patients with plantar fasciitis both at rest and movement, the visual analog score (VAS) at rest at baseline with a MD (95% CI) of 3.77 (2.96 to 4.59) and at 2 weeks of treatment of 1.16 (0.62 to 1.71), the VAS at movement of baseline with a MD (95% CI) of (5.22 4.75 to 5.69) and at 2 weeks of treatment of 3.16 (2.43 to 3.89). After the block the angle of toe dorsiflexion at baseline with a MD (95% CI) of 20.50° (18.7 to 22.26) was decreased to 13.08° (10.88 to 15.27), and the thickness of plantar fascia at baseline with a MD (95% CI) of 4.56 mm (4.18 to 4.95) was increased to 5.53 mm (4.95 to 5.04), showing signs of decreased fascial tension.
Conclusion
From the perspective of balancing the biological force of the plantar fascia, using DPN block can improve the biomechanical position and tension of the plantar fascia to a certain extent to promote the recovery of the damaged fascia block. As far as we know, this treatment concept may be a new treatment way for plantar fasciitis.
Knowledge Graph Link Prediction via Hyperbolic Attenuated Attention Networks
Authors: Zhang Xuanyu , Wu Jianbin , Peng Hao , Wang Junkai 
Published: April 2024

Abstract
Graph Attention Networks serve as prevalent models for knowledge graph link prediction, enabling the completion of link prediction tasks on general knowledge graphs. However, most current models embed nodes in Euclidean space, leading to distortion in node embedding features. Additionally, existing methods overlook the issue of assigning weights to n-hop neighbors during node embedding aggregation and fail to investigate the prediction of different relation patterns in hyperbolic space. In this paper, we propose a Hyperbolic Graph Attenuated Attenuation Network (HGAAT) model for link prediction, utilizing hyperbolic graph attention networks to handle relations and entity representations in knowledge graphs. By introducing a attenuated attention mechanism, HGAAT effectively integrates information from n-top neighboring nodes, thereby generating more accurate entity and relation embeddings in complex relational graphs. Extensive experiments demonstrate the effectiveness and superiority of the HGAAT model in knowledge graph link prediction tasks.
Physician characteristics and implicit bias in disparate rates of primary cesarean delivery in Black vs. non-Black patients
Authors: Roloff Kristina A , Okekpe Chioma C , Stowe Robert J , Valenzuela Guillermo J 
Published: April 2024

Abstract
Background
Black patients experience a higher chance of cesarean delivery (5–19% increased incidence over white patients) and reductions in low-risk cesarean deliveries in white patients have surpassed reductions among Black patients. The reasons driving this health care disparity are largely unknown. Here, we assess physician demographic characteristics and a measure of implicit bias in relation to primary cesarean delivery in Black vs. non-Black patients as possible contributing reasons for disparate rates of cesarean delivery by patient race.
Methods
This is a retrospective study of patients delivered at term at a single safety-net hospital. Demographics of the attending physician responsible for the delivery, including physician gender, race, years in practice, type of training, and physicians' results of an Implicit Association Test were compared to determine associations between provider factors on mode of delivery (cesarean or vaginal) by maternal race (Black vs. non-Black). Multinomial regression analysis was used to model primary cesarean delivery rates in Black compared to non-Black patients.
Results
In 4,847 singleton, term deliveries without a prior cesarean delivery, we found a significant difference in mode of delivery (cesarean or vaginal delivery) by race in the sample, with higher cesarean delivery rates in Black patients (21.3%) compared to non-Black patients (12.9%) (P < 0.001). Ten of 22 physicians (47.6%) responded to a request to share implicit association test results. Multinomial regression demonstrated higher rate of cesarean delivery in Black vs. non-Black patients that persisted for all physician attributes: gender (aOR 0.53, 0.20–1.38 95% CI), race and ethnicity (aOR 1.01, 0.94–1.09 95% CI), years in practice (aOR 0.71, 0.25-2.00 95% CI), training type (aOR1.05 0.84–1.32 95% CI), and measure of implicit bias (aOR 0.99, 0.82–1.19 95% CI).
Conclusion
We did not find that higher primary cesarean delivery in Black vs. non-Black patients were related to physician characteristics or implicit association test results.
The relationship between fetal tissue chromosomal karyotype and clinical characteristics in patients with spontaneous abortion: a retrospective study
Authors: Liu Lin , Yang Yanting , Huo Huyan , Hu Ning , Wang Fang 
Published: April 2024

Abstract
Background
Abnormal fetal tissue chromosome karyotypes are one of the important pathogenic factors for spontaneous abortion (SA). To analyze the characteristics of fetal tissue chromosomal karyotype in 778 women with a history of SA and its relationship with clinical features.
Methods
A retrospective study collected maternal age, body mass index (BMI), gestational weeks at miscarriage, the number of previous pregnancy losses and fetal tissue karyotypes CNV-seq data of 778 SA couples from Lanzhou University Second Hospital from October 2019 to December 2023, and described the characteristics of fetal tissue chromosomal karyotype and its relationship with clinical features.
Results
In our study, 432 patients (55.53% of total) had abnormal fetal tissue chromosomal karyotypes, with the highest incidence being trisomy syndrome (46.99%,203/432). Advanced maternal age(>35 years), early pregnancy(<12 weeks), and a history of less than four previous pregnancy losses were all identified as risk factors for fetal tissue chromosomal abnormalities.
Conclusion
The results of this study indicate that fetal tissue chromosomal abnormalities are the primary factor leading to SA. Additionally, advanced maternal age(>35years), early pregnancy(<12 weeks=, and the fewer number of previous pregnancy losses(≤ 4 times) are associated with a higher risk of fetal tissue chromosomal abnormalities following miscarriage.
Assessing the Performance of Plugin-Integrated ChatGPT-4 in the German Medical Board Examination: An Experimental Study on the Advancements and Limitations of Modern AI Modelling Approaches
Authors: Madrid Julian , Diehl Philipp , Selig Mischa , Rolauffs Bernd , Hans Felix Patricius , Busch Hans-Jörg , Scheef Tobias , Benning Leo 
Published: April 2024

Abstract
Background
The Generative Pre-trained Transformer (GPT-4) is a large language model (LLM) trained and fine-tuned on an extensive dataset. After the public release of its predecessor in November 2022, the use of LLMs has seen a significant spike in interest, and a multitude of potential use cases have been proposed. In parallel, however, important limitations have been outlined. Particularly, current LLM encounters limitations, especially in symbolic representation and accessing contemporary data. The recent version of GPT-4, alongside newly released plugin features, has been introduced to mitigate some of these limitations. Before this background, this work aims to investigate the performance of GPT-3.5, GPT-4, GPT-4 with plugins, and GPT-4 with plugins using pre-translated English text on the German medical board examination. Recognizing the critical importance of quantifying uncertainty for LLM applications in medicine, we furthermore assess this ability and develop a new metric termed 'confidence accuracy' to evaluate it.
Methods
We employed GPT-3.5, GPT-4, GPT-4 with plugins, and GPT-4 with plugins and translation to answer questions from the German medical board examination. Additionally, we conducted a thorough analysis to assess how the models justify their answers, the accuracy of their responses, and the error structure of their answers. Bootstrapping and confidence intervals were utilized to evaluate the statistical significance of our findings.
Results
This study demonstrated that available GPT models, as LLM examples, exceeded the minimum competency threshold established by the German medical board for medical students to obtain board certification to practice medicine. Moreover, the models could assess the uncertainty in their responses, albeit exhibiting overconfidence. Additionally, this work unraveled certain justification and reasoning structures that emerge when GPT generates answers.
Conclusion
The high performance of GPTs in answering medical questions positions it well for applications in academia and, potentially, clinical practice. Its capability to quantify uncertainty in answers suggests it could be a valuable AI agent within the clinical decision-making loop. Nevertheless, significant challenges must be addressed before AI agents can be robustly and safely implemented in the medical domain.
Comparative Cell Viability of Dentin-Bonding Adhesive Systems on Human Dental Pulp Stem Cells: Time-Dependent Analysis
Authors: Kazak Magrur , Gungor Ayca Sarialioglu , Ozman Zeynep , Donmez Nazmiye 
Published: April 2024

Abstract
Background
Restorative materials are in prolonged contact with living tissues such as oral mucosa, dentin, pulp, periodontal, and periapical tissues. Therefore, the potentially harmful effects of these materials and their components on oral tissues should be evaluated before clinical use. This study aimed to compare the cell viability of different dentin-bonding adhesive systems (DBASs) on human dental pulp stem cells (hDPSCs).
Methods
Three DBASs that combining MDP monomer with new hydrophilic amide monomers [Clearfil Universal Bond Quick(CUBQ), Kuraray Noritake], self-reinforcing 3D monomer [Bond Force II(BFII), Tokuyama)], and dual-cure property [Futurabond DC(FBDC), VOCO] were used. Three (n = 3) samples were prepared for each group. Samples were incubated in Dulbecco's modified Eagle's medium (DMEM) for 24 hours (h), 72 h, and 7 days (d) to obtain extracts. For the control group, cells were cultured without DBA samples. Cell viability of DBASs extracts was measured using a cell proliferation detection kit (WST-1, Roche). Statistical analysis was performed using two-way ANOVA and post-hoc (Duncan) tests (p < 0.05).
Results
At 24 and 72 h statistically significant differences were determined between control and BFII, control and FBDC groups (p < 0.05), while no differences between control and CUBQ groups (p > 0.05). On the 7th d, statistically significant differences were found between the control and experimental groups (p < 0.05), while no differences between experimental groups (p > 0.05). A statistically significant difference was detected for the BFII group over the three-time interval (p < 0.05). The lowest cell viability was observed for the FBDC group at 24 h, and the difference was statistically significant when compared with 72 h and 7th d (p < 0.05).
Conclusion
All DBASs showed different cell viability values at different contact times. In addition to the contents of DBASs, their pH should also be taken into account in terms of biocompatibility.
Research Hotspots and Evolution Trends of “Reused Brick”: A Bibliometric Analysis based on VOSviewer
and Citespace 1977-2022
Authors: Yu Boyuan , Luo Jianing , Li Yangzhi , Fingrut Adam 
Published: April 2024

Abstract
Recycling and reuse alleviate the already scarce natural resources to some extent and promote a rational distribution of resources. This study summarizes various aspects of the current recycling phase of reused bricks. It discusses the drawbacks of various utilization methods in the building and construction sector and the non-degradable recycling potential. This study aims to visualize the current state of research and knowledge structure of the literature related to reused bricks based on the scientific bibliometric survey of Citespace and VOSview. Intuitively, topics within the field were clustered and analyzed. It was found that most of the waste originates from urban development processes, such as construction waste (CDW); material recycling research in building and construction materials manufacturing and construction is mainly based on the mechanical kinetic energy of the material to degrade it and use it as an aggregate for new bricks and as a new aggregate for brick making or mixing concrete. In this study, a systematic review of the material degradation and reuse processes involved in the reuse brick topic is presented, and related studies are clustered summarized, and discussed, with the expectation of providing a theoretical basis and technical support for future research in the field of reuse brick and its subfields.