bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Impact of Blood Glucose and Antidiabetic Medications on Osteoarthritis: A Mendelian Randomization Study
Authors: Wang Junjie , Li Yuxuan , Wang Binyang , Ma Qing , Yang Lvlin 
Published: March 2024

Abstract

Objective
Blood glucose metabolism is a crucial risk factor for the onset of osteoarthritis (OA). Our aim is to assess the causal relationship between blood glucose levels and the incidence of osteoarthritis, as well as the impact of antidiabetic medications on osteoarthritis outcomes, using Mendelian randomization (MR) methods.
Methods
This is a two-sample Mendelian randomization design. Osteoarthritis was chosen as the outcome, and causal relationships with three exposures—glycated hemoglobin (HbA1c), fasting blood glucose (FG), and postprandial two-hour blood glucose (2hGlu)—were evaluated. Additionally, this study examined the relationship between common antidiabetic medication target genes (GCK, HFE, HK1, HKDC1, TCF7L2, and INS) and osteoarthritis. The inverse variance-weighted method (IVW) is primarily employed for effect estimation.
Results
HbA1c levels were negatively correlated with hip OA (OR 0.725, 95% CI 0.558–0.944) but not associated with knee OA or OA at any site. FG levels were negatively correlated with hip OA (OR 0.675, 95% CI 0.547–0.834) and OA at any site (OR 0.889, 95% CI 0.801–0.986). Gene predictions revealed a negative correlation between GCK and hip OA (OR 0.359, 95% CI 0.238–0.542), HFE and hip OA(OR 0.332, 95% CI 0.181–0.607), HK1 and knee OA (OR 0.735, 95% CI 0.565–0.955) and OA at any site (OR 0.743, 95% CI 0.636–0.868), HKDC1 and knee OA(OR 0.731, 95% CI 0.555–0.963) and OA at any site (OR 0.771, 95% CI 0.655–0.908), while INS shows a positive correlation with knee OA (OR 17.277, 95% CI 4.408–67.722) and OA at any site (OR 4.168, 95% CI 1.844–9.422).
Conclusion
MR analysis revealed a correlation between reduced HbA1c levels and an increased risk of hip OA, and FG was associated with an increased risk of hip OA and OA at any site. Gene predictions suggest that activating GCK, HFE, HK1, and HKDC1 genes with antidiabetic medications may reduce the risk of developing osteoarthritis. Consideration of antidiabetic medications for treating osteoarthritis is plausible, but clinical validation is necessary.
Graded treadmill running protocol on dynamic visual acuity and balance for athletes with and without recent concussion history
Authors: Mitchell Katelyn M. , Dalton Kristine , Cinelli Michael E. 
Published: February 2024

Abstract
Athletes interpret dynamic visual scenes quickly and accurately during physical exertion. It is important to understand how increased exertion may impact vision and cognition following sport-related concussion (SRC).
Purpose: To examine the effect of treadmill exercise on dynamic visual acuity (DVA) for athletes with and without SRC.
Methods:Varsity athletes following recent SRC (CONC=12) were compared to athletes without SRC (ATHLETE=19). The DVA task presented a Tumbling ‘E’ target in four possible orientations during random walk (RW) or horizontal (H) motion at a speed of 30°/s. Participants performed DVA trials standing on a force plate (1000Hz) at four time points: 1) pre-exercise (PRE-EX), 2) immediately (POST1), 3) 10-minutes (POST10), and 4) 20-minutes post- exercise (POST20). Performance was calculated as a change in DVA score from PRE-EX and median response time (RT, ms). Balance control was analyzed using the root mean square of centre of pressure displacement (dCOP).
Results: Both groups maintained DVA scores for both motion types with similar balance strategies post-exercise. CONC responded more slowly by POST10 and POST20 during RW-motion compared to ATHLETE.
Conclusion: Both groups elicited similar exercise-induced benefits on DVA following exercise. However, a portion of athletes with SRC may experience transient cognitive benefits following exercise.
DarkGuardNet: A deep learning framework for imbalanced dark web traffic identification and application classification
Authors: Niu Teng , Li Wei , Liu Yazhi 
Published: February 2024

Abstract

The dark web was often utilized for illicit activities, data breaches, and the dissemination of malicious software. Researchers consistently employed various machine learning and deep learning approaches to detect dark web traffic. However, existing studies overlooked the comprehensive capture of multi-scale information in traffic data, resulting in an inability to fully extract features when dealing with complex structural data, especially in datasets with an imbalanced number of samples. To address this problem, our paper proposed DarkGuardNet for the recognition of dark web traffic and application type classification. Specifically, we conducted dark web traffic analysis based on sessions and designed a Spatio-temporal Feature Fusion (STFF) module to capture multi-scale feature correlations. This module extended the receptive field to deepen the understanding of complex data, allowing for the precise extraction of spatiotemporal features in imbalanced samples. In addition, we used Multi-Head Self-Attention (MHSA) to mine potential relationships between statistical features of dark web traffic, enabling the model to focus on key features of categories with small sample sizes. Finally, we conducted experiments on a new imbalanced dark web traffic dataset, formed by merging ISCXVPN and ISCXTor. The results indicated that the method achieved an accuracy of 0.999 in dark web traffic recognition and an accuracy of 0.986 in application type classification, surpassing other advanced methods. The Data is available at:https://github.com/niu954325618/Darknet2024/tree/main.
Kidney Outcomes and Trajectories of Tubular Injury and Function in Critically Ill Persons with and without Coronavirus-2019
Authors: Granda Michael L. , Tian Frances , Zelnick Leila R. , Bhatraju Pavan K. , Wurfel Mark M. , Hoofnagle Andrew , Morrell Eric , Kestenbaum Bryan 
Published: February 2024

Abstract
Background
Coronavirus disease-2019 (COVID-19) may injure the kidney tubules via activation of inflammatory host responses and/or direct viral infiltration. Most studies of kidney injury in COVID-19 lacked contemporaneous controls or measured kidney biomarkers at a single time point. To better understand mechanisms of AKI in COVID-19, we compared kidney outcomes and trajectories of tubular injury, viability, and function in prospectively enrolled critically ill adults with and without COVID-19.
Methods
The COVID-19 Host Response and Outcomes (CHROME) study prospectively enrolled patients admitted to intensive care units in Washington state with symptoms of lower respiratory tract infection, determining COVID-19 status by nucleic acid amplification on arrival. We evaluated major adverse kidney events (MAKE) defined as a doubling of serum creatinine, kidney replacement therapy, or death, in 330 patients after inverse probability weighting. In the 181 patients with available biosamples, we determined trajectories of urine kidney injury molecule-1 (KIM-1) and epithelial growth factor (EGF), and urine:plasma ratios of endogenous markers of tubular secretory clearance.
Results
At ICU admission, mean age was 55\(\pm\)16 years; 45% required mechanical ventilation; and mean serum creatinine concentration was 1.1 mg/dL. COVID-19 was associated with a 70% greater incidence of MAKE (95% CI 1.05, 2.74) and a 741% greater incidence of KRT (95% CI 1.69, 32.41). The biomarker cohort had a median of three follow-up measurements. Urine EGF, secretory clearance ratios, and eGFR increased over time in the COVID-19 negative group but remained unchanged in the COVID-19 positive group. In contrast, urine KIM-1 concentrations did not significantly change over the course of the study in either group.
Conclusions
Among critically ill adults, COVID-19 is associated with a more protracted course of proximal tubular dysfunction.
Cathepsin in Alzheimer's Disease, Parkinson's Disease and Dementia with Lewy Bodies: Mendelian Randomization Study
Authors: Song Wenjuan , Zhang Junqin , Ruan Guixiang , Wang Xiangping , Li Bin , Wu Dandan , Zhu Aijun , Zhao Liuyan , Ling Hongtao 
Published: February 2024

Abstract
Background
Observational studies indicate a strong association between most neurodegenerative disorders and cathepsin, although the causative link remains unclear.
Methods
This research utilized Mendelian Randomization (MR) with genetic markers linked to cathepsins as instrumental variables, and analyzed public Genome-Wide Association Studies (GWASs) summary data of individuals with European ancestry for Alzheimer's disease (AD), Parkinson's disease (PD), and dementia with Lewy bodies (DLB) as the outcomes. The study applied the inverse variance-weighted (IVW) method to assess the causal effects of cathepsins on AD, PD, and DLB. Several sensitivity analyses and a heterogeneity test were conducted to evaluate the effectiveness of the results. Confounding variables were accounted for using multivariable MR (MVMR). Additionally, reverse MR research was done to improve forward MR analysis. Lastly, we utilize Bayesian Weighted MR (BWMR) to further validate the robustness of the results.
Results
The MR investigation found an association between cathepsin H and AD and DLB risk. However, there was a negative correlation between PD risk and cathepsin B levels. Effect estimates in MVMR and BWMR analyses with cathepsins as variables remained constant. According to reverse MR analysis, PD decreased cathepsin B levels, and DLB negatively correlated with cathepsin Z levels. However, no reverse causal relationship was found between AD and cathepsins.
Conclusion
While higher cathepsin H levels were associated with AD and DLB risk, the bidirectional association between PD and cathepsin B. By studying how cathepsin influences the development and advancement of AD, PD, and DLB, novel methods for diagnosis and treatment might be investigated.
Sexual and psychosocial experiences of women with advanced-stage cervical cancer at Tikur Anbessa Hospital
Authors: Teshome Roza , Yang Irene , Seife Edom , Girma Eshetu , Higgins Melinda , Wells Jessica 
Published: February 2024

Abstract

Background
Cervical cancer and related treatments can result in multiple side effects that can impact sexual function. There are also psychological sequelae such as anxiety, guilt, and depression. To effectively anticipate, comprehend, and address the issues faced by cancer patients, it is crucial to conduct research on psychosocial and sexual concerns. Therefore, this study aimed to understand the sexual and psychosocial experiences of women with advanced-stage cancer.
Methods and Materials:
A qualitative phenomenological study was performed at the Tikur Anbessa Specialized Hospital Oncology Center. A total of 23 women with advanced-stage cervical cancer were selected. In-depth interviews were conducted using an interview guide. The recorded data were transcribed using verbatim approach and then translated into English. The transcribed data were then imported into the qualitative data analysis software package MAXQDA for coding and categorization.
Results
Several codes arose from the synthesis of the women's transcribed interviews, and these codes were subsequently grouped into three themes and subthemes. The most commonly reported sexual problems were pain during sexual intercourse, bleeding or spotting after sexual intercourse, foul smelling vaginal discharge, and diminished sexual desire. Women reported that it can be challenging for them to start these conversations with providers and that medical providers do not always provide them with information on sexual issues. Most women highlighted how important their partners' psychosocial assistance was to them during difficult times.
Conclusion
Women experienced numerous sexual problems after the onset of cancer symptoms and after undergoing cancer treatment. Patients with cancer will benefit from psychosocial support from their partners, families, and doctors to feel hopeful again.
Friction coefficients of 3D printed tool surfaces
Authors: Kaleem Muhammad Ali , Frohn-Sörensen Peter , Reuter Jonas , Engel Bernd 
Published: February 2024

Abstract
The clamp tools used in forming processes require high coefficient of friction (COF) to impart rigid clamping during the process. The mating surfaces of clamp tools are conventionally machined using CNC machines. Recently introduced metal-based Additive Manufacturing (AM) machines can 3D-print the clamp tools and produce tool surfaces with significantly high COF as compared to CNC processes. An accurate assessment of COF values of clamp tools surfaces is necessary for both numerical and finite element (FE) based modelling and simulation of forming processes. In this research, an investigation is made to determine the precise COF values of as-is surfaces of clamp tools 3D printed by Selective Laser Melting (SLM). The COFs of 3D printed as-is surfaces are compared with corresponding CNC-machined surfaces. The design and FE stress analysis of the clamp tool is carried out in the software Autodesk Inventor. The clamp tool is 3D-printed by a SLM machine using ultra-high strength maraging grade tool steel - X3NiCoTi1895 (1.2709). The surface roughness of both additively manufactured and CNC-machined surfaces is determined and the relationship between surface roughness and COFs of additively manufactured clamp tools is discussed. It is an application based research particularly oriented for metal bending and forming industries. In such industrial processes, the precise values of COF of clamp tools substantially assist to accurately predict the process outcome through modelling and simulation techniques.
Zirconia-Reinforced Lithium Silicate Marginal Gap Evaluation Using Various Self-Adhesive Resin Cements by SEM
Authors: Shely Asaf , Nissan Joseph , Lugassy Diva , Rosner Ofir , Zenziper Eran , Egbaria Tharaa , Ben-Izhack Gil 
Published: February 2024

Abstract
Background: This study aimed to evaluate the impact of three different self-adhesive resin cements on the marginal gap of full monolithic zirconia-reinforced lithium silicate (ZLS) single crowns.
Methods: We divided forty-five typodont teeth, fully prepared for full monolithic crowns, into three groups (fifteen each) for the use of three different self-adhesive resin cements. We created a fourth control group (Temp-bond) by taking five teeth from each group before cementation with self-adhesive resin cements. All forty-five abutments were scanned using Primescan (an intra-oral scanner (IOS)), followed by digital design and grinding of zirconia-reinforced lithium silicate (ZLS) crowns with a four-axis machine. We first cemented the crowns of the control group (Temp-bond) and evaluated the marginal gap using a scanning electronic microscope (SEM). After removing the crowns from the abutments, we cemented the crowns for each group using a different self-adhesive resin cement and observed them under the SEM to evaluate the marginal gap. We used a Kolmogorov-Smirnov test, which found no normal distribution in the study variables (p < 0.05), followed by Mann-Whitney tests (α = .05).
Results: The total mean marginal gap of the control group (24.67 ± 4.43 µm) was significantly lower compared to the self-adhesive resin cements groups (p < 0.0005). The total mean marginal gap of the G-cem ONE group (50.48 ± 6.38 µm) was significantly lower compared to the TheraCem group (p < 0.026) and RelyX U200 group (P < 0.008). The total mean marginal gap of the TheraCem group (66.28 ± 7.23 µm) was significantly higher than the G-cem ONE group (p < 0.026) but showed no significant difference with the RelyX U200 group (70.07 ± 10.12 µm, p > 0.110).
Conclusions: All four groups showed a clinically acceptable marginal gap (< 120 microns). Although all three groups of self-adhesive resin cements demonstrated a significant increase in the marginal gap compared to Temp-bond group, they were within the limits of clinical acceptability. Regarding the marginal gap, in everyday dentistry it is recommended to use G-cem ONE self-adhesive resin cement for ZLS single crowns.
Health system facilitators and barriers to the integration of mental health services into primary care in the Democratic Republic of the Congo: a multimethod study
Authors: Mayoyo Erick Mukala , Chenge Faustin , Sow Abdoulaye , Criel Bart , Michielsen Joris , Broeck Kris Van den , Coppieters Yves 
Published: February 2024

Abstract
Background
The integration of mental health into primary care—i.e., the process by which a range of essential mental health care and services are made available in existing multipurpose health care settings that did not previously provide them—can be facilitated or hindered by several health system factors that are still poorly understood. This study aimed to identify health system facilitators and barriers to the integration of mental health services into primary care in the Democratic Republic of the Congo (DRC) to improve the success rate of integration programs.
Methods
We conducted a multimethod, cross-sectional exploratory study. Stakeholders from sixteen of the twenty-six provinces of the DRC participated. We collected qualitative data through 31 individual, semistructured, face-to-face key informant interviews. We then collected quantitative data through a population-based survey of 413 respondents. We analyzed the interviews via thematic analysis, assigning verbatims to predefined themes and subthemes. For the survey responses, we performed descriptive analysis followed by binomial logistic regression to explore the associations between the variables of interest.
Results
Strong leadership commitment, positive attitudes toward mental health care, the availability of care protocols, dedicated mental health care spaces, mental health task sharing (p < 0.001), and sufficient numbers of primary care providers (PCPs) (p < 0.001) were identified as key health system facilitators of successful integration. However, barriers to integration are mainly related to a poor understanding of what integration is and what it is not, as well as to the poor functionality and performance of health facilities. In addition, stigma, low prioritization of mental health, lack of mental health referents, health professionals’ instability, lack of reporting tools, lack of standardized national guidelines for integration (p < 0.001), lack of funding (p < 0.001), shortage of mental health specialists to coach PCPs (p < 0.001), and lack of psychotropic medications (p < 0.001) were identified as health system barriers to integration.
Conclusion
Improving the functionality of primary care settings before integrating mental health care would be beneficial for greater success. In addition, addressing identified barriers, such as lack of funding and mental health-related stigma, requires multistakeholder action across all building blocks of the health system.
Toward Capturing Effective Interactions of Transformer based Models for Click-Through Rate Prediction
Authors: Kim Soyoung , Lee Dongjun , Kim Jaekwang 
Published: March 2024

Abstract
Predicting click-through rates involves estimating how likely it is that users will click on a website’s recommendations, such as advertisements or product listings. With the growth in data complexity and volume, it has become economically vital for online platforms to recommend appropriate items to users. Yet, this task remains difficult due to the sparse and high-dimensional categorical nature of the data inputs used in prediction models. Thanks to the superior performance of deep learning models compared to traditional methods, various deep learning strategies have been introduced to understand both simple and complex interactions from the mentioned data inputs. Nevertheless, feed-forward networks struggle to effectively capture common feature interactions and are limited in their capacity to efficiently model functions involving complex, high-order interactions. Moreover, as the complexity of the model layers increases, it becomes more challenging to reflect simple, low-order interactions in the output. In this paper, we introduce Low-Order Cross Attention Networks (LOCAN) designed to explicitly capture high-order interactions while also reflecting low-order interactions in the final prediction. We incorporate low-order interactions, identified through Factorization Machines, into the attention layer in a continuous manner, ensuring these interactions are carried through to the final prediction. Our experiments on three real-world datasets show that our model surpasses current leading methods, confirming the effectiveness of the proposed model.
Mechanism of ferroptosis induced by iodine in Nthyori3-1 cells by activating Nrf2 / HO-1 / ERK signaling pathway
Authors: Zhang Huijin , Wang Baohua , Liu Yanyan , Zhang Lu , He Mengfan , Liu Haixia 
Published: February 2024

Abstract
Purpose
In this study, iodine stimulated Nthyori3-1 cell was used as the research object to explore the relationship between high iodine stimulated thyroid cells and ferroptosis, and further clarify its pathogenesis. This study will help to provide new clues for the treatment of thyroid related diseases.
Methods
Intervene human normal thyroid cells with iodine. The levels of apoptosis and proliferation were detected by CCK-8 and MDA. The protein levels of Nrf2、HO-1、p-ERK1 and GPX4 were determined by western blotting. Flow cytometry was performed to detect ROS production.
Results
Iodine induces ferroptosis in Nthyori3-1 cells, and the application of the inhibitor ferroptosis-1 can reverse the ferroptosis state of cells. Nrf2 / HO-1 / ERK pathway is involved in the pathogenesis of thyroid cells induced by high iodine.
Conclusion
High iodine induces ferroptosis in Nthyori3-1 thyroid cells. The addition of ferroptosis inhibitor ferroptosis-1 partially reversed the ferroptosis of cells. High iodine is involved in the regulation of Nrf2 / HO-1 / ERK signaling pathway and may be related to ferroptosis.
Minimum magnitude boundaries in probabilistic seismic hazard analysis: an insight from structural engineering
Authors: Azarbakht Alireza 
Published: March 2024

Abstract
In order to systematically advance our understanding of the minimum magnitude limit (Mmin) in Probabilistic Seismic Hazard Analysis (PSHA) calculations, a novel and useful approach utilising a broad range of Single-Degree-of-Freedom (SDOF) oscillators and hazard conditions is being developed and tested. We have determined the most reasonable Mmin value for a variety of structure groups by examining the impact of Mmin on the Mean Annual Frequency (MAF) of various limit states (including the collapse capacity). The originality of the suggested methodology in the current work, known as the MAF saturation strategy, is the recommended Mmin, which is the cut-off value at which lesser magnitude events do add to the hazard but do not significantly change the MAF. The current work is the first to offer the MAF saturation strategy methodology, which searches for the cut-off magnitude at which the MAF value essentially remains constant even when smaller values of this cut-off are utilised as Mmin for hazard assessments. Therefore, given a series of carefully chosen ground motions in each oscillator instance, an Incremental Dynamic Analysis (IDA) is carried out (by applying the Hunt and Fill algorithm), and the appropriate LS (including the collapse capacity defined as global instability) points are calculated. Thus, the relationship between the distribution of LSs and the Engineering Demand Parameter (EDP) and Intensity Measure (IM) is found. The hazard curve can convoluted with this distribution, yielding the structure-specific MAF. In order to find the cut-off lower magnitude (Mmin), this convolution is repeated for several Mmin values. This cut-off is defined as the point at which, when lower values are utilised as Mmin in the PSHA computation, the MAF's values do not change considerably (with a five per cent threshold). The acquired data were thoroughly discussed in relation to various structural features and seismic input factors.