bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association between high-density lipoprotein cholesterol and reversion to normoglycemia from prediabetes: an analysis based on data from a retrospective cohort study
Authors: Mo Zihe , Hu Haofei , Han Yong , Cao Changchun , Zheng Xiaodan 
Published: January 2024

AbstractThe available evidence on the connection between high-density lipoprotein cholesterol (HDL-C) levels and the reversion from prediabetes (Pre-DM) to normoglycemia is currently limited. The present research sought to examine the connection between HDL-C levels and the regression from Pre-DM to normoglycemia in a population of Chinese adults. This historical cohort study collected 15,420 Pre-DM patients in China who underwent health screening between 2010 and 2016. The present research used the Cox proportional hazards regression model to investigate the connection between HDL-C levels and reversion from Pre-DM to normoglycemia. The Cox proportional hazards regression model with cubic spline functions and smooth curve fitting was employed to ascertain the nonlinear association between HDL-C and reversion from Pre-DM to normoglycemia. Furthermore, a set of sensitivity analyses and subgroup analyses were employed. Following the adjustment of covariates, the findings revealed a positive connection between HDL-C levels and the likelihood of reversion from Pre-DM to normoglycemia (HR 1.898, 95% CI 1.758–2.048, P < 0.001). Furthermore, there was a non-linear relationship between HDL-C and the reversion from Pre-DM to normoglycemia in both genders, and the inflection point of HDL-C was 1.540 mmol/L in males and 1.620 mmol/L in females. We found a strong positive correlation between HDL-C and the reversion from Pre-DM to normoglycemia on the left of the inflection point (Male: HR 2.783, 95% CI 2.373–3.263; Female: HR 2.217, 95% CI 1.802–2.727). Our sensitivity analysis confirmed the robustness of these findings. Subgroup analyses indicated that patients with SBP < 140 mmHg and ever smoker exhibited a more pronounced correlation between HDL-C levels and the reversion from Pre-DM to normoglycemia. In contrast, a less robust correlation was observed among patients with SBP ≥ 140 mmHg, current and never smokers. This study provides evidence of a positive and nonlinear association between HDL-C levels and the reversion from Pre-DM to normoglycemia in Chinese patients. Implementing intensified intervention measures to control the HDL-C levels of patients with Pre-DM around the inflection point may substantially enhance the likelihood of regression to normoglycemia.
Discovering biomarkers associated and predicting cardiovascular disease with high accuracy using a novel nexus of machine learning techniques for precision medicine
Authors: DeGroat William , Abdelhalim Habiba , Patel Kush , Mendhe Dinesh , Zeeshan Saman , Ahmed Zeeshan 
Published: January 2024

AbstractPersonalized interventions are deemed vital given the intricate characteristics, advancement, inherent genetic composition, and diversity of cardiovascular diseases (CVDs). The appropriate utilization of artificial intelligence (AI) and machine learning (ML) methodologies can yield novel understandings of CVDs, enabling improved personalized treatments through predictive analysis and deep phenotyping. In this study, we proposed and employed a novel approach combining traditional statistics and a nexus of cutting-edge AI/ML techniques to identify significant biomarkers for our predictive engine by analyzing the complete transcriptome of CVD patients. After robust gene expression data pre-processing, we utilized three statistical tests (Pearson correlation, Chi-square test, and ANOVA) to assess the differences in transcriptomic expression and clinical characteristics between healthy individuals and CVD patients. Next, the recursive feature elimination classifier assigned rankings to transcriptomic features based on their relation to the case–control variable. The top ten percent of commonly observed significant biomarkers were evaluated using four unique ML classifiers (Random Forest, Support Vector Machine, Xtreme Gradient Boosting Decision Trees, and k-Nearest Neighbors). After optimizing hyperparameters, the ensembled models, which were implemented using a soft voting classifier, accurately differentiated between patients and healthy individuals. We have uncovered 18 transcriptomic biomarkers that are highly significant in the CVD population that were used to predict disease with up to 96% accuracy. Additionally, we cross-validated our results with clinical records collected from patients in our cohort. The identified biomarkers served as potential indicators for early detection of CVDs. With its successful implementation, our newly developed predictive engine provides a valuable framework for identifying patients with CVDs based on their biomarker profiles.
Analysis of microbial communities in solid and liquid pig manure during the fertilization process
Authors: Kim Soo-Ryang , Lee Junkyung , Lee Myung Gyu , Sung Ha Guyn , Hwang Sun-Goo 
Published: January 2024

AbstractUtilizing livestock manure as organic fertilizer in sustainable agriculture is crucial and should be developed through an appropriate manufacturing process. Solid–liquid separation contributes to reducing odor, managing nutrients in livestock excretions, and lowering the cost of transporting manure to arable soil. To investigate the impact of fermentation after solid–liquid separation, we examined the specific correlation between chemical properties and bacterial communities in solid–liquid manures before and after the fermentation process. In terms of chemical properties before fermentation, the levels of electrical conductivity, nitrogen, ammonium nitrogen (NH4+-N), potassium, sodium, and chloride were higher in the liquid sample than in the solid sample. However, the chemical components of the liquid sample decreased during fermentation, which could be attributed to the low organic matter content. Many chemical components increased in the solid samples during fermentation. Fifty-six bacterial species were significantly correlated with NH4+-N and phosphorus. Following fermentation, their abundance increased in the solid samples and decreased in the liquid samples, indicating the potential for NH4+-N release or phosphorus mineralization from organic matter. These results provide information regarding changes in nutrient and bacterial formation when applying the fermentation process after solid–liquid separation.
Vocal fold leukoplakia recurrence risk model
Authors: Klimza Hanna , Jackowska Joanna , Pietruszewska Wioletta , Porębski Andrzej , Nogal Piotr , Leduchowska Agata , Wierzbicka Małgorzata 
Published: January 2024

AbstractThe paper aims to define the variables that elevate the risk of VFL recurrence after adequate primary treatment, and to present the Recurrence Risk Model with practical conclusions to handle pVFL and rVFL. Out of 207 patients with primary vocal fold leukoplakia (pVFL), in 41 (19.8%) recurrent VFL (rVFL) was diagnosed. All patients were assessed by using a trans-nasal flexible video-endoscope using white light, and NBI. The primary measure of our study was to investigate whether morphological features of pVFL in WL, vascular pattern in NBI, and primary histological findings could predict VFL recurrence. To create a model of risk factors, two methods were used: logistic regression and a conditional inference decision tree. The study showed smoking was the factor that significantly and most strongly increased the likelihood of rVFL, as well as the older age groups have a greater odds of rVFL. Types IV, V and VI, according to Ni 2019 classification, were associated with a significantly higher risk of rVFL. The algorithm combining patients’ dependent variables and the combination of two classifications improves the predictive value of the presented VFL Recurrence Risk Model.
Diagnostic significance of HRCT imaging features in adult mycoplasma pneumonia: a retrospective study
Authors: Sui Dong-xin , Ma Han-chen , Wang Chao-chao , Shao Hong-yan , Xu Shao-hua , Fang Ning-ning 
Published: January 2024

AbstractMycoplasma pneumoniae pneumonia (MPP) often overlaps with the clinical manifestations and chest imaging manifestations of other types of community-acquired pneumonia (CAP). We retrospectively analyzed the clinical and imaging data of a group of patients with CAP, summarized their clinical and imaging characteristics, and discussed the diagnostic significance of their certain HRCT findings. The HRCT findings of CAP researched in our study included tree-in-bud sign (TIB), ground-glass opacity (GGO), tree fog sign (TIB + GGO), bronchial wall thickening, air-bronchogram, pleural effusion and cavity. The HRCT findings of all cases were analyzed. Among the 200 cases of MPP, 174 cases showed the TIB, 193 showed the GGO, 175 showed the tree fog sign, 181 lacked air-bronchogram. In case taking the tree fog sign and lack of air-bronchogram simultaneously as an index to distinguish MPP from OCAP, the sensitivity was 87.5%, the specificity was 97.5%, the accuracy was 92.5%. This study showed that that specific HRCT findings could be used to distinguish MPP from OCAP. The combined HRCT findings including the tree fog sign and lacked air-bronchogram simultaneously would contribute to a more accurate diagnosis of MPP.
Finite element analysis and clinical study of chest wall reconstruction using carbon fiber artificial rib
Authors: Zhang Xiang , Cai Zhixia , Liu Bo , Liao Jiqiao , Yu Fenglei , Tan Zhoujian , Wang Bin , Yang Mei , Zhang Bowen 
Published: January 2024

AbstractCarbon fiber composites are emerging as a promising new biomaterial for chest wall reconstruction implants due to their mechanical properties and biocompatibility. This work evaluates the biomechanics of carbon fiber artificial ribs using finite element analysis and clinical implementation. Static simulations of normal breathing process show the maximum stress on the implant is only 2.83 MPa, far below the material ultimate strength of 60 MPa, indicating the excellent fit for maintaining respiratory function. Dynamic collision simulations demonstrate the artificial rib model could withstand a 4 kg rigid object impact at 2 m/s without fracture. Reconstructing the artificial rib with a human rib in the finite element analysis model increases the overall stress tolerance. The impact force required for fracture increases 48% compared to the artificial rib alone, suggesting improved strength from rib integration. Clinically, 10 of 13 patients receiving the artificial rib implants show no significant loss of pulmonary function based on spirometry tests. Based on our findings, the combined simulations and clinical results validate the strong mechanical performance and biocompatibility of the carbon fiber artificial ribs for chest wall reconstruction under static and dynamic loading while maintaining normal respiratory function.
ER+/PR− phenotype exhibits more aggressive biological features and worse outcome compared with ER+/PR+ phenotype in HER2-negative inflammatory breast cancer
Authors: Luo Yunbo , Li Qingyun , Fang Jiang , Pan Chaoying , Zhang Lingxing , Xu Xia , Qian Shuangqiang , Zhao Xiaobo , Hou Lingmi 
Published: January 2024

AbstractThe loss of progesterone receptor (PR) often predicts worse biological behavior and prognosis in estrogen receptor-positive (ER +) breast cancer. However, the impact of PR status on inflammatory breast cancer (IBC) has not been studied. Therefore, the purpose of our study was to investigate the influence of PR on IBC. Patients with ER+ and HER2-negative IBC were selected from the Surveillance, Epidemiology and End Results database. Pearson’s χ2 test was used to compare the clinicopathological characteristics between patients with estrogen receptor-positive/progesterone receptor-positive (ER+/PR +) and patients with estrogen receptor-positive/progesterone receptor-negative (ER+/PR−). Univariate and multivariate analyses were performed to investigate the effects of PR status on the breast cancer-specific survival (BCSS) and overall survival (OS) in IBC. Overall, 1553 patients including 1157 (74.5%) patients with ER+/PR+ and 396 (25.5%) patients with ER+/PR− were analyzed in our study. The patients with ER+/PR− were more likely to be high histological grade (p < 0.001) and liver metastasis (p = 0.045) compared to patients with ER+/PR+. Despite higher chance of receiving chemotherapy (83.6% vs 77.3%, P = 0.008), patients with ER+/PR− showed worse BCSS (5-year BCSS rate, 34.3% vs 51.3%, P < 0.001) and OS (5-year OS rate, 31.3% vs 46.1%, P < 0.001) compared with ER+/PR+ phenotype. Multivariate survival analysis showed that patients with ER+/PR− still had worse BCSS (hazard ratios [HR]: 1.764, 95% confidence intervals [CI] 1.476–2.109, P < 0.001) and OS (HR: 1.675, 95% CI 1.411–1.975, P < 0.001) than ER+/PR+ phenotype. Furthermore, patients with ER+/PR− showed worse outcomes than ER+/PR+ phenotype in most subgroups, especially in patients with younger age (≤ 60 years), lower histological grade, lymph node involved and distant metastasis. Patients with ER+/PR− had more aggressive biological behaviors and worse outcomes than patients with ER+/PR+ in IBC. Stronger treatments maybe needed for IBC patients with ER+/PR−.
Relationship between paravertebral muscle degeneration and spinal-pelvic sagittal parameters in patients with lumbar disc herniation
Authors: Bao Tianlian , Wang Chunmei , Wang Yongjiang , Wang Tiantian , Zhang Qingxin , Gao Feng , Liu Hao , Tao Xiaoyang , Gao Gang , Zhang Tinxin , Yang Wupeng , Zhao Keyu 
Published: January 2024

AbstractLumbar disc herniation (LDH) is a clinically common degenerative disease of the spine, and spinal–pelvic sagittal balance and paravertebral muscle degeneration have been a research focus in recent years. To explore the relationship between the degeneration of paravertebral muscle and the changes in the spinal–pelvic sagittal parameters in LDH patients, 105 LDH patients (experimental group) and 63 healthy volunteers (control group) hospitalized in Ordos Central Hospital from January 2020 and January 2023 were included as study subjects. All the patients underwent lumbar magnetic resonance imaging and spinal X-ray using uniform criteria. The correlation between the paravertebral muscle and sagittal–pelvic sagittal parameters of the patients with LDH was obtained from two imaging examinations, and the data were organized and grouped to explore the correlation between these parameters. No significant difference in general data existed between the groups (P > 0.05). In the L4/5 LDH patients group, the ratio of fat infiltration (FIR) in the healthy side [multifidus (MF) and erector spinae (ES)] was negatively correlated with the lumbar lordosis (LL) (r = −0.461, r = −0.486, P < 0.05). The relative cross-sectional area (RCSA) of the bilateral MF was positively correlated with the pelvic tilt (r = 0.549, r = 0.515, P < 0.05). The bilateral ES RCSA was negatively correlated with the sagittal vertical axis (r = −0.579, r = −0.621, P < 0.05). A positive correlation existed between the RCSA and thoracic kyphosis in the healthy side ES (r = 0.614, P < 0.05). In the L5/S1 LDH patients group, a negative correlation existed between the FIR and LL in the healthy side ES (r = −0.579, P < 0.05). Thus, the paravertebral muscle parameters were correlated with the spinal–pelvic sagittal parameters in the patients with LDH.
Remote sensing based forest cover classification using machine learning
Authors: Aziz Gouhar , Minallah Nasru , Saeed Aamir , Frnda Jaroslav , Khan Waleed 
Published: January 2024

AbstractPakistan falls significantly below the recommended forest coverage level of 20 to 30 percent of total area, with less than 6 percent of its land under forest cover. This deficiency is primarily attributed to illicit deforestation for wood and charcoal, coupled with a failure to embrace advanced techniques for forest estimation, monitoring, and supervision. Remote sensing techniques leveraging Sentinel-2 satellite images were employed. Both single-layer stacked images and temporal layer stacked images from various dates were utilized for forest classification. The application of an artificial neural network (ANN) supervised classification algorithm yielded notable results. Using a single-layer stacked image from Sentinel-2, an impressive 91.37% training overall accuracy and 0.865 kappa coefficient were achieved, along with 93.77% testing overall accuracy and a 0.902 kappa coefficient. Furthermore, the temporal layer stacked image approach demonstrated even better results. This method yielded 98.07% overall training accuracy, 97.75% overall testing accuracy, and kappa coefficients of 0.970 and 0.965, respectively. The random forest (RF) algorithm, when applied, achieved 99.12% overall training accuracy, 92.90% testing accuracy, and kappa coefficients of 0.986 and 0.882. Notably, with the temporal layer stacked image of the Sentinel-2 satellite, the RF algorithm reached exceptional performance with 99.79% training accuracy, 96.98% validation accuracy, and kappa coefficients of 0.996 and 0.954. In terms of forest cover estimation, the ANN algorithm identified 31.07% total forest coverage in the District Abbottabad region. In comparison, the RF algorithm recorded a slightly higher 31.17% of the total forested area. This research highlights the potential of advanced remote sensing techniques and machine learning algorithms in improving forest cover assessment and monitoring strategies.
Multi-pose-based convolutional neural network model for diagnosis of patients with central lumbar spinal stenosis
Authors: Park Seyeon , Kim Jun-Hoe , Ahn Youngbin , Lee Chang-Hyun , Kim Young-Gon , Yuh Woon Tak , Hyun Seung-Jae , Kim Chi Heon , Kim Ki-Jeong , Chung Chun Kee 
Published: January 2024

AbstractAlthough the role of plain radiographs in diagnosing lumbar spinal stenosis (LSS) has declined in importance since the advent of magnetic resonance imaging (MRI), diagnostic ability of plain radiographs has improved dramatically when combined with deep learning. Previously, we developed a convolutional neural network (CNN) model using a radiograph for diagnosing LSS. In this study, we aimed to improve and generalize the performance of CNN models and overcome the limitation of the single-pose-based CNN (SP-CNN) model using multi-pose radiographs. Individuals with severe or no LSS, confirmed using MRI, were enrolled. Lateral radiographs of patients in three postures were collected. We developed a multi-pose-based CNN (MP-CNN) model using the encoders of the three SP-CNN model (extension, flexion, and neutral postures). We compared the validation results of the MP-CNN model using four algorithms pretrained with ImageNet. The MP-CNN model underwent additional internal and external validations to measure generalization performance. The ResNet50-based MP-CNN model achieved the largest area under the receiver operating characteristic curve (AUROC) of 91.4% (95% confidence interval [CI] 90.9–91.8%) for internal validation. The AUROC of the MP-CNN model were 91.3% (95% CI 90.7–91.9%) and 79.5% (95% CI 78.2–80.8%) for the extra-internal and external validation, respectively. The MP-CNN based heatmap offered a logical decision-making direction through optimized visualization. This model holds potential as a screening tool for LSS diagnosis, offering an explainable rationale for its prediction.
Aniseikonia and retinal morphological changes in eyes undergoing macular hole surgery
Authors: Takeyama Asuka , Imamura Yutaka , Fujimoto Taichi , Iida Toshiya , Komiya Yuko , Ishida Masahiro 
Published: January 2024

AbstractEven after idiopathic macular hole (MH) surgery and with successful closure of MH, aniseikonia is a common postoperative symptom. We investigated the correlation of MH diameter, retinal displacement and retinal layer thicknesses with aniseikonia in 41 eyes of 41 patients undergoing MH surgery with internal limiting membrane peeling. Aniseikonia was measured with the New Aniseikonia Test. Retinal displacement (RD%) was defined as change of retinal distance between the temporal margin of the optic papilla and the intersection of the retinal vessels. Changes of thicknesses of the inner nuclear layer (INL%) and the outer retinal layer (OR%) were calculated. Aniseikonia improved postoperatively. Preoperative aniseikonia and their improvement at 6 months correlated with MH diameters (P = 0.004–0.046). Improvement of aniseikonia correlated with temporal RD% (P = 0.002–0.012). Improvement of vertical aniseikonia correlated with INL% at 2 weeks and with the nasal OR% at 1, 3, and 6 months (P = < 0.001–0.028). MH diameter and age were significant predictors for improvement of aniseikonia. The greater the temporal retina displacement, and the thinner the postoperative INL and OR, the greater the improvement of aniseikonia. MH diameter and age are strong predictors for improvement of aniseikonia after MH surgery.
Overestimation of black carbon light absorption due to mixing state heterogeneity
Authors: Zeng Linghan , Tan Tianyi , Zhao Gang , Du Zhuofei , Hu Shuya , Shang Dongjie , Hu Min 
Published: January 2024

AbstractBlack carbon (BC) aerosols, which arise from incomplete combustion processes, possess the capacity to absorb solar radiation, thereby contributing significantly to the issue of climate warming. However, accurately estimating their radiative effect is challenging, influenced by emissions, sizing, morphology, and mixing state. BC particles undergo aging processes that can alter their physical characteristics and mixing state, consequently affecting their optical properties. In this study, we assessed the mixing state of BC across diverse atmospheric environments. Results demonstrate that mixing state heterogeneity is a ubiquitous phenomenon. In background atmospheres, BC exhibited less homogeneous states compared to those in urban and suburban areas, where heterogeneity was driven by primary emissions. Our study provides direct observational evidence that the heterogeneity of particle-particle mixing can reduce the light absorption enhancement of BC in all atmospheres, with a deviation of up to approximately 24% under background conditions.
Recessive TMOD1 mutation causes childhood cardiomyopathy
Authors: Vasilescu Catalina , Colpan Mert , Ojala Tiina H. , Manninen Tuula , Mutka Aino , Ylänen Kaisa , Rahkonen Otto , Poutanen Tuija , Martelius Laura , Kumari Reena , Hinterding Helena , Brilhante Virginia , Ojanen Simo , Lappalainen Pekka , Koskenvuo Juha , Carroll Christopher J. , Fowler Velia M. , Gregorio Carol C. , Suomalainen Anu 
Published: January 2024

AbstractFamilial cardiomyopathy in pediatric stages is a poorly understood presentation of heart disease in children that is attributed to pathogenic mutations. Through exome sequencing, we report a homozygous variant in tropomodulin 1 (TMOD1; c.565C>T, p.R189W) in three individuals from two unrelated families with childhood-onset dilated and restrictive cardiomyopathy. To decipher the mechanism of pathogenicity of the R189W mutation in TMOD1, we utilized a wide array of methods, including protein analyses, biochemistry and cultured cardiomyocytes. Structural modeling revealed potential defects in the local folding of TMOD1R189W and its affinity for actin. Cardiomyocytes expressing GFP-TMOD1R189W demonstrated longer thin filaments than GFP-TMOD1wt-expressing cells, resulting in compromised filament length regulation. Furthermore, TMOD1R189W showed weakened activity in capping actin filament pointed ends, providing direct evidence for the variant’s effect on actin filament length regulation. Our data indicate that the p.R189W variant in TMOD1 has altered biochemical properties and reveals a unique mechanism for childhood-onset cardiomyopathy.