bluuebunny/crossref_metadata_2025_split huggingface dataset:
Preoperative prediction of bleeding complications in percutaneous nephrolithotomy using a machine learning model based on CT radiomics and clinical variables
Authors: Zou Xin-Chang , Yuan Rong Man , Zhou Jie , Zheng Guang Hao , Jin Meng , Zeng Tao , Chao Hai Chao 
Published: April 2024

Abstract

Background and objective
Radiomics and machine learning play a significant role in clinical medical research, particularly in the development of prediction models.This study aims to utilize radiomic features and clinical variables in combination with machine learning to predict the risk of postoperative bleeding after percutaneous nephrolithotomy (PCNL).
Materials and Methods
A retrospective study analyzed 151 patients who had PCNL at the Second Affiliated Hospital of Nanchang University.Clinical variables linked to postoperative bleeding were identified using univariate analysis,and radiomic features were screened using the least absolute shrinkage and selection operator algorithm(lasso regression).Logistic regression,Random Forest(RF),and Support Vector Machine(SVM) were then used to develop prediction models based on the correlated clinical variables and radiomic features.The predictive accuracy of these models was assessed through identification and calibration.
Results
The postoperative statistics revealed that the postoperative bleeding rate was 31.1%(n=47),the blood transfusion rate was 1.42%(n=3),and the final probability of requiring vascular embolization was 0.94%(n=2).The accuracy rates for predicting postoperative bleeding in patients with PCNL using logistic regression,RF and SVM algorithms were 75.6%,75.6%,and 71.1% respectively.The corresponding area under the curve AUC(95% CI) were 0.76(0.72-0.81),0.74(0.69-0.79) and 0.63(0.54-0.68).The top four prediction importance scores in logistic regression and RF algorithms were wavelet-HLH_glrlm_ShortRunLowGrayLevelEmphasis,wavelet-HLH_glrlm_LowGrayLevelRunEmphasis,stone shape,operation time and stone shape,stone diameter,operation time,Wavelet-HLH_glrlm_ShortRunLowGrayLevelEmphasis.
Conclusion
The logistic regression model demonstrated the highest efficiency in predicting postoperative bleeding in PCNL.Our study successfully developed an effective machine learning model that can assist urological surgeons in making appropriate treatment decisions for predicting postoperative bleeding in PCNL.
Construction of ecological security patterns and evaluation of connectivity stability under multi-scenario simulation: A case study in desert–oasis area of the Yellow River Basin, China
Authors: Cheng Wenhao , Ma Caihong , Li Tongsheng , Liu Yuanyuan 
Published: April 2024

Abstract
Land use change often has enormous impacts on ecosystem sustainability, and ecological security pattern (ESP) can improve ecological quality through spatial planning. Thus, this study explored a multi-scenario ESPs framework by coupling future land use simulation (FLUS) and minimum cumulative resistance (MCR) for urban agglomerations along the Yellow River Basin in Ningxia, simulated land use change in 2035 under four development scenarios, identified ecological security networks, and assessed the stability of network connectivity in each scenario. The results showed that the areas of ecological sources under the natural development scenario (NDS), economic development scenario (EDS), food security scenario (FSS), and ecological protection scenario (EPS) were 834.82 km2, 715.46 km2, 785.56 km2, and 1091.43 km2, respectively. The overall connectivity (OG) values were 0.351, 0.466, 0.334, and 0.520, respectively. Under the EPS, the construction of ESPs has the largest area of ecological land use and the most stable network structure, which can not only effectively protect natural habitats but also reduce the cost of construction in reality. This study provides a valuable method for identifying ESPs that can respond to diversity and uncertainty for future development and can help decision makers improve the ecological quality of the study area considering different scales and development scenarios.
Research Article: In-Vitro Evaluation of The Stain Removal Efficacy Between Two Whitening Dentifrices During Orthodontic Treatment
Authors: Yeoh Zhen Herr Eugene , Khan Khairil Aznan Mohamed , Nor Murshida Marizan , Baharin Badiah , Rani Haslina 
Published: April 2024

Abstract

Background
This in-vitro study aimed to assess and compare the efficacy of a newly developed whitening dentifrice, Dentaklin White (TG), to Colgate Total® Whitening (CG), utilising a toothbrushing simulator machine.
Methods
Twenty enamel specimens were prepared and randomly divided into CG and TG. Orthodontic brackets were attached to the enamel specimens and were then stained with a mixture of coffee, tea, and chlorhexidine. A short 0.019x0.025” stainless steel (SS) archwire was ligated onto the brackets subsequently. All the specimens were subjected to a toothbrushing simulator for specific duration. The CIE L*a*b* colour change (ΔE) was evaluated using digital image analysis at T1 (2 weeks), T2 (4 weeks), and T3 (12 weeks) compared to T0 (baseline). Archwire roughness was analysed using a profilometer at T4 (2 years) compared to T0.
Results
The results indicated that there was a significant change in tooth colour associated with brushing duration for both CG and TG (p < 0.05) with no significant difference between the two dentifrices (p > 0.05). Both dentifrices notably removed more stains at Site A (p < 0.05) and increased wire surface roughness (p < 0.05) without a statistically difference between them (p > 0.05).
Conclusion
Dentaklin White (TG) demonstrated comparable efficacy to Colgate Total® Whitening (CG).
Genome-wide identification of the oat DMP gene family and its expression analysis in response to seed aging
Authors: Ma Yuan , Liu Huan , Wang Jinglong , Zhao Guiqin , Niu Kuiju , Zhou Xiangrui , Zhang Ran , Yao Ruirui 
Published: April 2024

Abstract

Background:
The Domain of unknown function 679 membrane proteins (DMPs) family, as a green plant-specific membrane protein, plays an important role in plant reproductive development, stress response and aging. To identify the DMP gene members of oat (AsDMP) and to investigate their family structural features and tissue expression profile characteristics, a study was conducted. Based on the whole genome and transcriptome data, in this investigation, we have scrutinized the physicochemical properties, gene structure, cisacting elements, phylogenetic relationships, conserved structural (CS) domains, CS motifs and expression patterns of the AsDMP family of oat.
Results
The DMP family genes of oat were found distributed across 17 chromosomal scaffolds with 33 members. We could divide the AsDMP genes into five subfamilies based on phylogenetic relationships. The gene structure suggests that oats may have also undergone an intron loss event during evolution. Covariance analysis suggests that genome-wide duplication/segmental duplication may be the major contributor to the expansion of the AsDMP gene family. Ka/Ks selective pressure analysis of oat DMP gene family, suggests that DMP gene pairs tend to be conserved over evolutionary time. The upstream promoter of these genes containing several cis-acting elements indicates a plausible role in abiotic stress and hormone induction. Gene expression pattern according to transcriptome data revealed participation of the DMP genes in tissue and organ development. In this study, AsDMP genes (AsDMP1, AsDMP19, and AsDMP22) were identified as potentially regulating oat seed senescence, and can be used as candidate genes for seed longevity and anti-aging germplasm breeding studies in oat. The study provides valuable information on the regulatory mechanism of the AsDMP gene family in the aging process of oat germplasm, and also provides theoretical support for further function investigation in the oat DMP gene and the molecular mechanism of seed anti-aging.
Conclusions
In this study, we found that the AsDMP gene is involved in the aging process of oat seeds, which is the first report on the potential role of DMP genes in oat seeds.
MicroRNA-195-5p targets neurofibromin 2 to mediate hyperoxia-induced alveolar dysplasia
Authors: Bai Dongqin , Wu Di , Yang Miao , Wu Bo , Xu Wei 
Published: April 2024

Abstract
MicroRNAs (miRs) have been shown to disrupt normal lung development and function by blocking alveolation and vascularization, leading to the development of bronchopulmonary dysplasia (BPD). However, the role of miR-195-5p in BPD has not been reported. Therefore, this study aimed to understand whether the biological role of miR-195-5p in BPD is achieved by targeting neurofibromin 2 (NF2) regulation. Here, we report that miR-195-5p plays a key role in hyperoxia-induced alveolar dysplasia in BPD. First, increased expression of miR-195-5p was detected in the lung tissues of hyperoxia-induced rat models of BPD and neonatal rat lung type II alveolar epithelial cells (AECIIs) exposed to hyperoxic conditions. Second, NF2, a tumor suppressor gene that plays an important role in the proliferation and differentiation of AECIIs, was identified as the specific target of miR-195-5p. Cell-based luciferase analysis revealed that the overexpression of miR-195-5p and its target gene NF2 in lung AECIIs could partially alleviate the impaired differentiation of AECIIs induced by hyperoxia, suggesting that miR-195-5p could hinder the differentiation of AECII into AECI by inhibiting NF2 expression. Finally, animal intervention experiments confirmed that miR-195-5p aggravated alveolar dysplasia in BPD by downregulating NF2 expression. In conclusion, our study confirmed a novel mechanism wherein miR-195-5p exacerbates alveolar dysplasia in BPD by inhibiting AECII differentiation to AECI by targeting NF2. These results may help clarify some molecular mechanisms of the poor proliferation and differentiation of AECII in BPD alveolar dysplasia and provide novel targets for future clinical molecular interventions.
Inter-joint coordination with and without dopaminergic medication in Parkinson's disease: a case-control study
Authors: Saegner Karolina , Romijnders Robbin , Hansen Clint , Holder Jana , Warmerdam Elke , Maetzler Walter 
Published: April 2024

Abstract
Background
how the joints exactly move and interact and how this reflects PD-related gait abnormalities and the response to dopaminergic treatment is poorly understood. A detailed understanding of these kinematics can inform clinical management and treatment decisions. The aim of the study was to investigate the influence of different gait speeds and medication on/off conditions on inter-joint coordination, as well as kinematic differences throughout the whole gait cycle in well characterized pwPD.
Methods
29 controls and 29 PD patients during medication on, 8 of them also during medication off walked a straight walking path in slow, preferred and fast walking speeds. Gait data was collected using optical motion capture system. Kinematics of the hip and knee and coordinated hip-knee kinematics were evaluated using Statistical Parametric Mapping (SPM) and cyclograms (angle-angle plots). Values derived from cyclograms were compared using repeated-measures ANOVA for within group, and ttest for between group comparisons.
Results
PD gait differed from controls mainly by lower knee range of motion (ROM). Adaptation to gait speed in PD was mainly achieved by increasing hip ROM. Regularity of gait was worse in PD but only during preferred speed. The ratios of different speed cyclograms were smaller in the PD groups. SPM analyses revealed that PD participants had smaller hip and knee angles during the swing phase, and PD participants reached peak hip flexion later than controls. Withdrawal of medication showed an exacerbation of only a few parameters.
Conclusions
Our findings demonstrate the potential of granular kinematic analyses, including > 1 joint, for disease and treatment monitoring in PD. Our approach can be extended to further mobility-limiting conditions and other joint combinations.
Trial registration:
The study is registered in the German Clinical Trials Register (DRKS00022998).
Clinical utility of the pan-immune-inflammation value in intrahepatic cholangiocarcinoma patients
Authors: 寇 晓萱 , Qing Qiuying , Jin Linlin , Li Dong , Zhou Fei , Zhang Xiaoyong , Liu Hongyan 
Published: April 2024

Abstract
Objectives
The prognosis of pan-immune inflammatory value (PIV) in intrahepatic cholangiocarcinoma (ICCA) remains unclear. The aim of this study was to explore the clinical utility of the PIV in intrahepatic cholangiocarcinoma patients.
Methods
138 patients with intrahepatic cholangiocarcinoma diagnosed for the first time were retrospectively collected. The optimal cutoff value for baseline PIV, determined by the maximally selected rank statistics method for OS. Based on the estimated cutoff value, 106 patients (75.5%) were included in the low PIV cohort (≤ 765.31) and 32 patients (24.5%) were included in the high PIV cohort (> 765.31).
Results
In the study, we showed that a novel pan-immune inflammatory value has an independent prognostic impact in patients with intrahepatic cholangiocarcinoma. Our results showed that high PIV is associated with a poorer OS prognosis. In addition, patients with high PIV and no surgery for the first time had a worse prognosis when stratified by baseline PIV and treatment regimen. Furthermore, early PIV variation and baseline as biomarkers to predict overall survival have added value, as its inclusion in the multivariate model also increased the concordance index.
Conclusions
In this study, we identified PIV as a novel biomarker that is strongly associated with the overall prognosis of patients with intrahepatic cholangiocarcinoma at first diagnosis. Of course, prospective validation of dynamic evaluation is still needed.
Investigating the impact of concurrent type 2 diabetes on the occurrence of liver cancer in 2501 patients with chronic hepatitis B
Authors: Lai Changxiang , Zhang Xiulian , Xian Wenjie , Zhong Wenqing , Tang Qiyuan , Li Zhiyu , Zhou Xuan , Chen Ruikun , Tang Qingrong , wang fang 
Published: April 2024

Abstract
Purpose Exploring the occurrence of adverse outcomes time in patients with chronic Hepatitis B virus infection and type 2 diabetes mellitus who develop liver cancer.Methods A total of 2501 patients who were hospitalized at Shenzhen Third People’s Hospital from January 2017 to January 2023 and met the inclusion criteria were collected. The patients were divided into diabetes group and non-diabetes group based on whether they had type 2 diabetes at admission. Through subsequent follow-ups, the occurrence of liver cancer in the two groups of patients during the follow-up period was observed, with follow-up time ending in January 2014. At the same time, the Cox proportional hazard regression model was used to analyze the impact of coexisting type 2 diabetes on the risk of developing hepatitis B virus-related liver cancer.Results 2,501 patients were followed up on average for 43.8 ± 5.2 months, with a total of 23 cases of liver cancer occurring during the follow-up period. Among them, 61 patients were diagnosed with type 2 diabetes (diabetes group), with an average follow-up duration of 44.7 ± 9.6 months and 7 cases of liver cancer occurring during the follow-up period, with a 5-year cumulative incidence of liver cancer of 15%. In the non-diabetes group of 2,440 patients, the average follow-up duration was 43.8 ± 5.0 months, with 16 cases of liver cancer occurring during the follow-up period and a 5-year cumulative incidence of liver cancer of 2.3%. The difference in cumulative incidence of liver cancer between the two groups was statistically significant (P < 0.05). Results of Cox univariate regression analysis showed that the risk of liver cancer in the diabetes group was 6.968 times higher than that in the non-diabetes group (95% confidence interval, CI: 2.240–21.671, P = 0.02); after adjusting for factors such as age, gender, history of hepatitis B, family history of liver cancer, antiviral treatment, different liver inflammation and fibrosis, and alcohol consumption in the Cox regression multivariate analysis, the risk of liver cancer in diabetic patients with hepatitis B virus infection was 3.833 times higher than that in the non-diabetes group (95% CI: 1.134–12.952, P = 0.031).Conclusion Type 2 diabetes and hepatitis B virus are related to the incidence of liver cancer, and the presence of type 2 diabetes increases the risk of liver cancer occurrence within 5 years in patients infected with hepatitis B virus.
“Knowing how to play the game”: Clinician experiences of treating patients with a compensable injury in Australia
Authors: Sim Alison , McNeilage Amy G. , Rebbeck Trudy , Ashton-James Claire E. 
Published: April 2024

Abstract

Purpose
Previous research indicates that the compensation process is stressful for people with a compensable injury, contributing to poorer recovery. However, little is known about the challenges faced by clinicians who work in this setting. This study aims to qualitatively explore the experiences of clinicians delivering care to patients with compensable injuries in Australia.
Materials and methods
Semi-structured interviews were conducted with 26 experienced clinicians providing care to compensable patients in Australia. The interviews were transcribed, and data were analysed using reflective thematic analysis.
Results
Participants described their work as challenging due to factors such as high patient distress, poor clinical outcomes, and high administrative load. However, they responded to these challenges in varying ways. While some reported feelings of vicarious injustice, emotional exhaustion, and self-doubt, others derived a sense of meaning, purpose, and mastery from these challenges. Clinician responses to the challenge of working with people with a compensation claim were associated with access to mentoring, continuous education and training, and a supportive workplace culture.
Conclusion
Clinicians reported both positive and negative responses to the challenges of working with people with a compensable injury. Understanding individual and workplace factors shaping clinician responses to the demands of working with compensable patients may be crucial for retaining the clinical workforce and improving access to compensable care.
An intelligent threshold selection method to improve orbital angular momentum-encoded quantum key distribution under turbulence
Authors: Li Jia-Hao , Tang Jie , Wang Xing-Yu , Xue Yang , Yu Hui-Cun , Deng Zhi-Feng , Cao Yue-Xiang , Liu Ying , Wu Dan , Hu Hao-ran , Wang Ya , Lun Hua-zhi , Wei Jia-hua , Zhang Bo , Liu Bo , Shi Lei 
Published: April 2024

Abstract
The high-dimensional quantum key distribution (HD-QKD) encoded by orbital angular momentum (OAM) presents significant advantages in terms of information capacity. However, perturbations caused by free-space atmospheric turbulence introduce random fluctuations in OAM transmittance, impacting the performance of the system. Currently, there exists a gap in theoretical analysis concerning the statistical distribution of OAM-encoded QKD systems. In this study, we analyze the security of QKD systems by combining probability distribution of transmission coefficient (PDTC) of OAM with decoy-state BB84 method. To address the problem that the invalid key rate is calculated in the part transmittance interval of the post-processing process, an intelligent threshold method based on neural network is proposed to improve OAM-encoded QKD, which aims to conserve computing resources and enhance system efficiency. Our findings reveal that the ratio of root mean square (RMS) OAM-beam radius to Fried’s atmospheric coherence width plays a crucial role in ensuring secure key generation. Moreover, the training error of neural network is at the magnitude around 10 −3 , indicating the ability to predict optimization parameters quickly and accurately. This research contributes to the advancement of parameter optimization and prediction for free-space OAM-encoded HD-QKD systems. Furthermore, it provides valuable theoretical insights to support the development of free-space experimental setups.
C-Dots/UiO-66-NH 2 -enhanced composite modified electrode for simultaneous detection of Pb 2+ and Cd 2+
Authors: Chen Shaohua , Wang Yihua , Zhang Biao , Li Mingming , Zhang Jinhua , Hu Qiangfei , Qian Quan 
Published: April 2024

Abstract
Carbon dots and metal-organic frameworks (MOFs) have been widely used in a variety of applications such as sensing, energy storage, and catalysis, with fewer applications in electrochemical sensing. In this study, C-Dots/UiO-66-NH2 was prepared as a modified material for glassy carbon electrodes for the detection of cadmium and lead ions in water by electrochemical methods (DPV) by selecting m-phenylenediamine as a source of carbon dots and amino-functionalized zirconium-based metal-organic frameworks, which are the combination of these two popular materials. Due to the complexation of amino groups with metal ions, a sufficient amount of amino groups provided a good interface for the adsorption of metal ions. Under the optimal deposition conditions, C-Dots/UiO-66-NH2 exhibited good linearity and excellent detection limits for metal ions (Cd2+, Pb2+) in the concentration range of 30 to 180 µg/L. The results showed that C-Dots/UiO-66-NH2 was suitable for the determination of Cd2+ and Pb2+ in water. In addition, the C-Dots/UiO-66-NH2/GCE sensor has good immunity to interference and detection stability.
Analyzing and Predicting Dynamic Fluctuations of Physiological State in Healthcare Workers
Authors: Zhao Huihan , Wang Fubo , He Yu , Zhang Huiyong , Li Qiuxia , Feng Qiming , Huang Zhaoquan 
Published: April 2024

Abstract
Background
Healthcare workers face continuous exposure to various physiological and psychological stressors, which can lead to dynamic changes in their physiological environment and potentially culminate in debilitating disease. This study was conducted to analyze the dynamic changes in physiological measures of health examination and anticipate health status and disease risk in healthcare workers.
Methods
A retrospective study extracting health examination data from healthcare workers from 2018 to 2022 was carried out. Principal component analysis (PCA) was employed for unsupervised dimensionality reduction to identify the combinations of measures to best capture the variation in the population. The average path length on the two-dimensional graph of the subjects with 3 ~ 5 health examination records was calculated and analyzed. Based on machine learning, we also developed predictive models to anticipate healthcare workers' dynamic changes in physiological measures.
Results
The results showed that 4.65% of healthcare workers exhibited unusually high average path length and were identified as outliers in abnormal fluctuation in physiological measures. Additionally, we identified statistically significant differences in the average path length between different genders, departments, and ages. Notably, the average path length was significantly correlated with hemoglobin, platelet count, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, platelet crit, creatinine, uric acid, and low-density lipoprotein cholesterol. We also developed random forest, support vector machine, and K-nearest neighbors regressions, which showed strong predictive performance for the average path length.
Conclusions
This study provides novel insight into the assessment of subtle changes in physiological measures and anticipatory analytics of the healthcare workers’ health status. This will provide an important reference value for healthcare workers’ health prediction, promotion, and management.