bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comprehensive analysis based on classification of immunogenic cell death reveals immunologic and prognostic characteristics of breast cancer
Authors: Chen Letian , Cen Yinghuan , Zhou Wenbin 
Published: October 2023

Abstract
Background: Breast cancer (BC) is a main cause of cancer-related mortality in women globally. The immune system plays a vital role in various processes of cancer development and therapy. Neoplastic cells are constantly interacting with and shaping the tumour microenvironment (TME) which in turn influences the cancer development. Immunogenic cell death (ICD) is sufficient to activate an adaptive immune response and contribute to immunotherapy via release of danger signals or damage associated molecular patterns.
Method: The Cancer Genome Atlas database and the Gene Expression Omnibus dataset were used to collect 1139 samples, which were then categorized using R software packages. The ICD-related genes were classified into two clusters according to their expression level. The relationships between the different subgroups and clinical pathological characteristics, immune infiltration characteristics, mutation status of the TME and ICD level were investigated. Furthermore, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses used to build an immunological prognostic model was developed to estimate patient survival probability and effect of immunotherapy.
Results: We enrolled 1139 patients for analysis and divided the ICD-related genes into two groups based on the expression level. 22 types of tumour infiltrating immune cells in primary BC were quantified by estimating relative subsets of RNA transcripts (CIBERSORT). The results of univariate Cox regression revealed that 9 genes were substantially associated with BC patients' overall survival (OS). OS was significantly shorter in the high-risk group than in the low-risk group, regardless of other characteristics of BC. 7 genes were shown to be closely correlated with the risk score system which was established by the model and utilizing the immune score model may predict the prognosis and immunotherapy effect in patients with BC.
Conclusion: The classification system of BC based on ICD signatures is efficient to predict the prognosis of BC patients as well as the effect of immunotherapy.
Distinct microbiota assembly and functional patterns revealed by comparative analysis of disease resistant and susceptible tobacco (Nicotiana tabacum) varieties
Authors: Yang Luhua , Guo Yuan , Yang Hui , Li Shun , Zhang Yunzeng , Gao Cheng , Hao Likai 
Published: October 2023

Abstract
Plant microbiota is believed to be an accessory genome extending plant functions, forming holobiont together with the host plant. Plant disease resistance, therefore, is inextricably linked with plant microbiota, which play important roles in plant growth and health. In order to explore the relationship between plant microbiota and disease resistance, we investigated the tobacco microbiome of two varieties with contrasting disease resistance levels to bacterial wilt and black shank. Comparative microbiome analysis indicated that the resistant variety assembled a distinct microbiota with higher network complexity and diversity. While Pseudomonas and Ensifer, that contain biocontrol and beneficial members, were enriched in the rhizosphere of the resistant variety, Ralstonia, a genus including the known causative pathogen, was enriched in the susceptible variety. Metagenome sequencing revealed that biocontrol functions were more abundant in the resistant variety, such as hydrogen cyanide synthase, pyochelin biosynthesis, and arthrofactin-type cyclic lipopeptide synthetase. Further analysis indicated that contigs encoding the corresponding genes were mostly assigned to Pseudomonas. Among all the metagenome-assembled-genomes, positive selection was suggested in the genome assigned to Pseudomonas only in the rhizosphere of the resistant variety. The search of biosynthetic gene clusters in the Pseudomonas genome revealed a non-ribosomal peptide synthetase, the compound of which was brabantamide A, with known antimicrobial activity. Collectively, our study suggests that the plant microbiota might be involved in the microbe-mediated disease resistance. Particularly, our results highlight Pseudomonas in the rhizosphere of the disease-resistant variety as the promising biocontrol candidate. Our study may facilitate further screening of bacterial isolates and the targeted design of microbial communities.
Feasibility and safety report on robotic assistance for cervical pedicle screw fixation: a cadaveric study
Authors: Ryu Seungjun , Ha Byungjun , Yoon Sunjin , Lee Chang Kyu , Shin Dong Ah , Kim Keung-Nyun , Yi Seong 
Published: October 2023

Abstract

This cadaveric study aimed to evaluate the safety and usability of a novel robotic system for posterior cervical pedicle screw fixation. Two human cadaveric specimens and C2-T3 were included. Freshly frozen human cadaver specimens were prepared and subjected to robot-assisted posterior cervical pedicle screw fixation using the robotic system. The accuracy of screw placement, breach rate, and critical structure violations were evaluated. The results were statistically compared with those of previous studies that used different robotic systems for cervical pedicle screw fixation. The robotic system demonstrated a high accuracy rate in screw placement. A significant number of screws were placed within predetermined safe zones. The total entry offset was 1.08 ± 0.83 mm, the target offset was 1.86 ± 0.50 mm, and the angle offset was 2.14 ± 0.77°. Accuracy rates comparable with those of previous studies using different robotic systems were achieved. The system was also feasible, allowing precise navigation and real-time feedback during the procedure. This cadaveric study validated the safety and usability of the novel robotic system for posterior cervical pedicle screw fixation. The system exhibited high precision in screw placement, and the results support the extension of the indications for robot-assisted pedicle screw fixation from the lumbar spine to the cervical spine.
GAN-based bone suppression imaging for high-accurate markerless motion tracking of lung tumors in CyberKnife treatment
Authors: Mochizuki Zennosuke , Saito Masahide , Suzuki Toshihiro , Mochizuki Koji , Hasegawa Junichi , Nemoto Hikaru , Takahashi Hiroshi , Onishi Hiroshi 
Published: October 2023

Abstract
Purpose
Lung tumor tracking with CyberKnife sometimes misrecognizes tumor location when there are overlapping bony structures in the search area near the tumor. This study aimed to develop a bone suppression technique for kV-X-ray imaging using machine learning.
Methods
CT images were created with or without bony structures using a 4D extended cardiac-torso phantom (XCAT phantom) in 56 cases. Subsequently, X-ray projection images in the left and right oblique 45-degree directions from these images were then divided into nine squares for 1120 images. Images with bone were input into six general adversarial network (GAN) and the bone suppressed images on the XCAT phantom (BSIphantom) were created. They were then compared to images without bone using the structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR), frechet inception distance (FID). Next, the bone suppressed image (BSIpatient) were created from 1000 non-simulated treatment images of the actual patient. Zero means normalized cross correlation (ZNCC) by template matching between each of treatment images and BSIpatient were calculated.
Results
BSIphantom were calculated the highest SSIM and PSNR of 0.96 ± 0.02 and 36.93 ± 3.93, respectively, compared to images without bone shadows in the test data. Five out of six algorithms significantly improved ZNCC, showing a higher ZNCC than the actual treatment images. FID evaluation was showed that the SimDCL was the most promising model with 68.93.
Conclusions
The proposed GAN-based bone suppression image processing technique improved image recognition and enabled highly accurate dynamic tracking irradiation.
Effect of nanofibrillated cellulose on shrinkage of cement pastes
Authors: de Souza Letícia Oliveira , de Souza Lourdes Maria Silva , Silva Flávio de Andrade , Mechtcherine Viktor 
Published: October 2023

Abstract
This study investigates the effect of nanofibrillated cellulose (NFC) on the total and autogenous shrinkage deformation of cement pastes. Three different water-to-cement ratios (w/c) were used, namely 0.30, 0.35, and 0.40, along with NFC inclusion percentages of 0.000%, 0.025%, and 0.050%. The effects of NFC were evaluated through total and autogenous shrinkage measurements. Total shrinkage evolution was measured using 24-hour-old prisms, while autogenous shrinkage deformation was monitored using sealed prisms and corrugated tubes, and their results were compared. The corrugated tube method provided early-age deformation measurements, while the sealed prism method allowed for direct comparison with free-drying shrinkage specimens. Flow table and bleeding water tests were conducted to support the understanding of the impact of NFC on the cementitious system. The NFC reduced the expansion by up to 85%. Regarding total shrinkage deformation, there was a 36% decrease at the end of 28 days for specimens with a w/c of 0.30 and NFC inclusion of 0.050%. However, this outcome varied for different combinations of w/c and nanocellulose inclusion percentage. The presence of NFC modified the fresh state properties of cement pastes, significantly reducing bleeding water and decreasing the expansion. These findings highlight the potential of NFC as a material for controlling shrinkage deformation, depending on the dosage, and emphasize the importance of considering different measurement methods for accurate assessment.
A Multi-Objective Fuzzy Robust Optimization Model for Open-Pit Mining Planning under Uncertainty
Authors: soleimani-bafghi Sayed Abolghasem , Nasab Hasan Hosseini , Fakhrzad Mohammad Bagher , Soltani Roya , Yarahmadi-Bafghi Ali-Reza 
Published: October 2023

Abstract

Today, carrying ore from the pit to the unloading sites is very important in open-pit mines. In the mines, due to changes in working conditions such as climate and the physical and mental condition of the workforce, uncertainty in the arrival time of trucks and the rate of ore transport is constantly discussed. This study provided a multi-objective mathematical model for programming the allocation of trucks to different loading sites to optimize cost, production, and environmental objectives. Fuzzy Robust Optimization(FRO) is used for the uncertainty, and the model is solved using LP-Metric. Chadormalu mine has been selected as a case study, and a shift transport was planned. Sensitivity analysis of the main parameters showed that the model could control and deal with uncertainty. The results showed that the optimality robustness factor only affects the value of the objective function \({Z}_{t}\), but the feasibility robustness does not affect any of the measurments.
Electrocardiographic abnormalities to the patients infected with HIV/AIDS under antiretroviral tritherapy at the University Clinics of Kinshasa
Authors: Masikini Benjamin Lupenzi , kisoka christian , Longo-Mbenza Benjamin 
Published: October 2023

Abstract
Introduction: Electrocardiogram (ECG) abnormalities are common to HIV-infected patients on antiretroviral therapy (ART). However, the relationship between ART, cardiovascular risk and cardiac electrical activity to patients living with HIV (PLWHIV) remains poorly studied in Kinshasa. The objective of this study was to describe the impact of tritherapy on the electrocardiogram of HIV-infected patients. Methods: This was a retrospective, descriptive, evaluative cohort with secondary analysis of a clinical cases serie of 155 HIV-infected patients under ART in the internal medicine department of University hospitals of Kinshasa (UHK) from 2013 to 2020. Results: The mean age of the patients was 54±11 years, with extremes ranging from 16 to 80 years, a sex ratio M/F=1. The dominant comorbidities were High blood pressure (HBP) at 23.4% and Pulmonary tuberculosis at 18. 8%. Dyspnea, HBP and lower limb edema were the main complaints, respectively 29.9%, 22.7% and 20.1%. The majority of patients were treated with TDF+3TC+EFV at 86.4% and a small proportion at 13.6% for TDF+3TC+ LPV/r. A total of 83.1% or 128 HIV-infected patients showed cardiac abnormalities on ECG. These were dominated by Left Ventricular Hypertrophy (LVH) 37%, sinus tachycardia 35% and repolarization disorders (subepicardial ischemia, subendocardial ischemia) 16.2%. With the TDF+3TC+LPV/r regimen, cardiac ECG abnormalities were more observed than with the TDF+3TC+EFV regimen with P<0.05; Right Ventricular Hypertrophy (RHV) at 40.4% with TDF+3TC+LPV/r regimen versus 4.7% with TDF+3TC+EFV P<0.001; myocardial ischaemia observed at 28.3% versus 11.2% with TDF+3TC+EFV regimen P=0.020. Conclusion: Electrocardiographic abnormalities are frequent and polymorphic to PLWHIV under ART (83.1%), often aggravated by protease inhibitors. The ECG should be used as a tool to screen for these abnormalities before and after 6 months of ART initiation.
Semi-Supervised Deep Learning Coupled with Laser-induced Breakdown Hyperspectral Imaging for the Margin Distance Determination of Non-small Cell Lung Cancer
Authors: Lin Qingyu , Chen Youyuan , Xie Shaohua , Chen Li , Xu Yingtong , Hu Bin , Li Qiang , Fan Qingwen , Duan Yixiang 
Published: October 2023

Abstract
An optimal margin distance determination is crucial for successful resection surgeries targeting early-stage non-small cell lung cancer (NSCLC). Yet, there has been no clear evidence regarding optimal margin distance, which is tightly associated with the recurrence and mortality after the operation. In this study, we proposed an innovative approach, a laser-induced breakdown hyperspectral imaging (LIBS-HSI) technique, capable of capturing the multi-element distribution within tumour tissues to probe optimal margin distance. The imaging quality of LIBS-HSI was enhanced by hyperspectral image (HSI) denoising algorithms founded on sparse representation and low-rank constraint, complemented by the application of the Butterworth notch resist filter. A semi-supervised deep learning model was developed to achieve pathological imaging segmentation recognition of malignant areas. This technique revealed the margin distance after getting malignant areas prediction and gradient, based on pseudo-colour imaging of elements composition within NSCLC samples. It stands as a promising candidate in postoperative pathological reports, enabling doctors to evaluate surgical outcomes in the future effectively.
Associative Games with Virtual Agents: unexpectedness increases willingness to continue dialog
Authors: Matsui Tetsuya 
Published: October 2023

Abstract
In the field of human-agent interaction, increasing agents' trustworthiness, inelligence perceived and users' motivation to continue interacting are important issues.Prior research has attempted to solve this problem by having "agents meet user expectations".In this paper, we attempted to show that, on the contrary, "agents contradicting user expectations" can increase agents' trustworthiness and users' motivation to continue dialogue.In this study, we conducted an experiment using an "association game" task.In this task, participants were given three hints and answered what those hints have in common.The correct answer is then given, along with a fourth hint.In the first condition, the "expected" condition, the correct answer was the one that the majority of participants associate with.In the second condition, the "unexpected" condition, the correct answer is different from the answer that the majority of participants associate with.After this task, participants answered the question about the extent to which they felt the agents' trustworthiness, intelligence and motivation to continue the interaction using a 7-point Likert scale.The experiment was conducted on the web.The results of the experiment showed that agents' trustworthiness and users' motivation to continue the interaction were significantly higher in the "unexpected" condition than in the "expected" condition.This result indicates that "the agent contradicts the user's expectations" can increase the agent's intelligence perceived and the user's motivation to continue the interaction.The results show the effectiveness of a new method in human-agent interaction that has not received much attention.
Transcriptomic Insights into UTUC: Role of Inflammatory Fibrosis and Potential for Personalized Treatment
Authors: Li Keqiang , Huang Zhenlin , Xie Guoqing , Huang Budeng , Song Liang , Zhang Yu , Yang Jinjian 
Published: October 2023

Abstract
Background: Upper tract urothelial carcinoma (UTUC) is a rare disease, belonging to the same category of urothelial cancers as bladder cancer (BC). Despite sharing similar non-surgical treatment modalities, UTUC demonstrates a higher propensity for metastasis compared to BC. Additionally, while both cancers exhibit many similar molecular disease emergence mechanisms, sequencing data reveals some differences. Our study aims to understand the transcriptomic distinctions between UTUC and BC, explore the causes behind UTUC's heightened metastatic tendency, construct a model for UTUC metastasis and prognosis, and propose personalized treatment strategies for UTUC.
Methods: In our research, we utilized differential gene expression analysis, interaction networks, and Cox regression to explore the enhanced metastatic propensity of UTUC. We formulated and validated a prognostic risk model using a diverse set of techniques, which include cell co-culture, reverse transcription quantitative polymerase chain reaction (rt-qPCR), Western blot, and Transwell experiments. Our methodological approach also involved survival analysis, risk model construction, and drug screening leveraging the databases of CTRPv2, PRISM and CMap. For histological assessments, we employed the Masson staining technique. All statistical evaluations were conducted using R software and GraphPad Prism 9, reinforcing the rigorous and comprehensive nature of our research approach.
Results: Screening through inflammatory fibrosis revealed a reduction of extracellular matrix and cell adhesion molecules regulated by proteoglycans in UTUC compared to BC, making UTUC more metastasis-prone. We demonstrated that five molecules, SDC1, LUM, VEGFA, WNT7B, and TIMP3, play critical roles in promoting UTUC metastasis. A risk model based on these five molecules can effectively predict the risk of UTUC metastasis and disease-free survival time. Given UTUC's unique molecular mechanisms distinct from BC, we discovered that UTUC patients could better mitigate the issue of poor prognosis associated with UTUC's easy metastasis by using Tyrosine Kinase Inhibitors (TKIs) alongside the conventional gemcitabine and cisplatin chemotherapy regimen.
Conclusions: 1. The poor prognosis of UTUC due to its high metastatic propensity is intimately tied to inflammatory fibrosis induced by ROS accumulation. 2. The biological model constructed using the five molecules SDC1, LUM, VEGFA, WNT7B, and TIMP3 can effectively predict patient prognosis. 3. UTUC patients require specialized treatments in addition to traditional regimens, with TKIs showing significant potential.
Role of Environmental Specificity in Casp Results
Authors: Roterman Irena , Stapor Katarzyna , Konieczny Leszek 
Published: October 2023

Abstract
Background
Recently, significant progress has been made in the field of protein structure prediction by application of artificial intelligence techniques, as shown by the results of the CASP13 and CASP14 (Critical Assessment of Structure Prediction) competition. However, the question of the mechanism behind the protein folding process itself remains unanswered. Correctly predicting the structure also does not solve the problem of, for example, amyloid proteins, where a polypeptide chain with an unaltered sequence adopts a different 3D structure.
Results
This work was an attempt at explaining structural variation by considering the contribution of the environment to protein structuring. The application of the fuzzy oil drop (FOD) model to assess the validity of the selected models provided in the CASP13, CASP14 and CASP15 projects reveals the need for an environmental factor to determine the 3D structure of proteins. Consideration of the external force field in the form of polar water (FOD) and a version modified by the presence of the hydrophobic factor, FOD-M reveals that the protein folding process is environmentally dependent. An analysis of selected models from the CASP competitions indicates the need for structure prediction as dependent on consideration of the protein folding environment.
Conclusions
The conditions governed by the environment direct the protein folding process occurring in the certain environment. Therefore, the variation of the external force field should be taken into account in the models used in protein structure prediction.
The significance of incorporating spatial disparities in scale development for assessing latent constructs in the field of bioenergy
Authors: BALAGUEMAN Rodrigue Ogoulonou , ASSEDE Emeline S. P. , MOUMOUNI-MOUSSA Ismail , AYEGNON David Théophile Dakpo , BIAOU Samadori Sorotori Honoré 
Published: October 2023

Abstract
This study explored the importance to account for spatial disparities while measuring latent variables. Specifically, we investigated the potential influence of spatial disparities on scale validity and reliability with the purpose of developing a new scale for assessing biomass supply intention for bioenergy production along with five common intention predictors (environmental concern, attitudes, subjective norms, perceived behavioral control and knowledge of renewable energy). We generated our data from a sample of 247 participants randomly surveyed in two socioeconomically disparate regions. We used factor analysis, confirmatory factor analysis, and Cronbach alpha (α) as methodological frameworks. We found 21 (33.33%) items out of the initial pool that were deemed reliable (α = 0.84 to 0.98) for future use. We found that spatial disparities impacted the scale items, with substantial divergence in scale reliability and composition between geographic regions. However, we found excellently reliable items that hold consistency across geographic regions. Our findings imply that ignoring region-specific context in scale development may lead to distorting inferences and ineffective policies. We aspire to bolster the reliability rate in forthcoming studies using a more rigorous item selection method.