bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrative Transcriptome and Metabolome Analysis Reveals the Regulatory Networks and Key Genes of Wild and Cultivated Gentiana macrophylla Pall
Authors: Liu Juanjuan , Zhang Jialing , Chen Yiyang , Li Ke , Wang Liangcai , Ma Xiaohui , Jin Ling 
Published: November 2024

Abstract

Gentiana macrophylla Pall. is a medicinally important perennial herb used in traditional Chinese and ethnic medicines. Iridoids are the main chemical constituents of G. macrophylla. The scarcity of the wild resource has led to increased attention to cultivated G. macrophylla. However, little is known about the metabolic differences and the regulatory mechanisms between cultivated and wild G. macrophylla. This study utilized untargeted metabolomics and transcriptomics to reveal differences in accumulated metabolites and expressed genes between wild and cultivated. The metabolomics profiling revealed 25587 differentially accumulated metabolites (DAMs) while the transcriptomic profiling identified 6830 differentially expressed genes (DEGs). Analysis revealed that DEGs were predominantly enriched for processes associated with monoterpenoid biosynthesis and flavonoid biosynthesis. In addition, we verified six differential genes involved in monoterpenoid biosynthesis and flavonoid biosynthesis by RT-qPCR. The results showed that the relative expression levels in cultivation were higher than those in the wild. According to KEGG pathway analysis, 10HGO(8-hydroxygeraniol dehydrogenase) may be a key enzyme encoding secoiridoid biosynthesis. The comprehensive results of transcriptome and metabolomics analysis revealed a strong correlation between metabolite content and gene expression, which is helpful to further study the function of G. macrophylla Pall. and the regulation of biosynthesis of active components. It provides a theoretical basis for further development and protection of wild species of G. macrophylla in the future.
Channel Estimation and Interference Management in Multi-User MIMO Systems Using Integrated Deep Learning and Quantum Computing
Authors: Yao Shutong 
Published: November 2024

Abstract

This study presents a novel approach combining deep learning with quantum computing for channel estimation and interference management in multi-user MIMO systems. Addressing the limitations of traditional channel estimation methods in complex wireless communication environments, we introduce quantum computing techniques, including quantum Fourier transforms and quantum state reconstruction algorithms, to enhance the accuracy and efficiency of channel estimation. Building on the results from quantum computing, we further optimize the outcomes using deep learning networks, focusing specifically on interference cancellation and data compression. In the experimental setup, we simulated the channel matrix of a multi-user MIMO system on a quantum computing platform and trained a convolutional neural network (CNN) for deep learning optimization. The findings demonstrate that the integration of quantum computing and deep learning substantially enhances system performance, particularly in managing interference and processing data in complex channel environments. This study not only provides new technical methods for channel estimation and interference management in multi-user communication systems but also paves the way for further research into the combined application of quantum computing and deep learning.
Theoretical model and experimental verification of seepage-transition-spontaneous imbibition in water migration of water-injected coal
Authors: Sun Qiushuang , Chen Jian , guo liwen , Yang Xinda , Yan Xuehan 
Published: November 2024

Abstract

Coal seam water injection is widely applied to prevent mine disasters. In the traditional water migration model of water-injected coal, from ignoring capillary force in the seepage stage to generating the capillary dynamic during the spontaneous imbibition state, no transition state exists from 0 to generating capillary force. In this paper, on the basis of theoretical analysis, an equivalent capillary term is introduced to modify the Forchheimer model, and then a seepage-transition-spontaneous imbibition model that is suitable for water migration of water-injected coal is proposed. The formulas for the upper critical point velocity v1, lower critical point velocity v2, and water migration range of the transition state are derived. An analysis experiment of the spontaneous imbibition state in the coal rock water injection process and a monitoring experiment of the water injection process based on nuclear magnetic resonance method are conducted to verify the accuracy of the model. Experimental results show that the water migration process of water-injected coal cannot be accurately reflected without considering the transition section. In this paper, the water migration model of water-injected coal is improved, which provides theoretical support for an in-depth understanding of the water injection mechanism of coal mine disaster prevention engineering.
Four-Step Approach to Screening Mental Health in Adolescents with Substance Use: A Study Using NSDUH Data
Authors: Pant Dipendra , Skokauskas Norbert , Leventhal Bennett , Nytrø Øystein 
Published: November 2024

Abstract

This study implements multiple independent models and aggregates them to screen the mental health status of adolescents with substance use problems, aiming to address an observable gap in developing reproducible and replicable Artificial Intelligence (AI) application. We analysed 21,037 adolescents in the year 2021 and 2022 National Survey on Drug Use and Health (NSDUH) data, focusing on multiple target correlates. Data columns with more than 80% missing values, variance below 1%, and correlation above 99% were omitted. Chi-square analysis identified significant associations, while mutual information analysis measured the strength of association. 29 input features related to major depressive episodes, substance use disorders, and mental health treatment history were associated with each of the 16 mental health status target labels, including concentration, depressive symptoms, sleep, energy levels, restlessness, loss of interest and appetite. Analysis of Machine Learning (ML) classifiers, neural networks, and ensemble techniques identified the best-performing models. These model’s predictions and their consensus screen and diagnose adolescents’ status. The resulting AI-based application is deployed at https://huggingface.co/spaces/pantdipendra/AdolescentsMentalHealthPrediction. Finally, the four-step approach, consisting of data extraction, statistical, machine learning analytics, and AI application step, supports reproducible AI application development and makes it accessible to community practices and patient care.
Diagnostic utility of serum PSP94/PSA ratio (PP Index) in minimizing prostate biopsies in lower urinary tract symptoms patients with serum PSA levels between 4-20 ng/ml
Authors: Jagtap Dhanashree D. , Kulkarni Bhalchandra J. , Pawar Prakash , Patil Bhushan , Mallya Adesh D. , Sarma Abhijit , Pathak Bhakti , Fernandes Gwendolyn , Andankar Mukund , Sawant Ajit , Patwardhan Sujata , Mahale Smita D. 
Published: November 2024

Abstract

Background
Serum prostate specific antigen (PSA) test is used globally for prostate cancer screening, however its low specificity causes diagnostic dilemma and a number of patients have to undergo unnecessary biopsies. Our earlier study reported that PSP94, another prostatic protein, when used in conjunction with PSA leads to an improvement in its diagnostic potential. We aim to assess the utility of PSP94/PSA ratio (PP Index) in minimizing referrals for prostate biopsies in patients having lower urinary tract symptoms (LUTS) and with PSA levels between 4–20 ng/ml.
Methods
Patients having LUTS were recruited for this prospective study (n = 833). Estimation of PSP94 was carried out using an in house developed ELISA and PSA tests were carried out at a centralized lab. Samples showing PSA levels in the range of 4–20 ng/ml were considered further for the study (n = 226). Out of these, the biopsy results of 139 participants were available. Receiver operating characteristic (ROC) curve analysis was performed to determine the area under the curve (AUC), sensitivity and specificity of PP Index. To establish the diagnostic potential of PP Index as compared to PSA and PSP94, we performed decision curve analyses (DCA).
Results
On the basis of PSA alone, 100% of the participants in the PSA range of 4–20 ng/ml were recommended for biopsy whereas if PP Index with a cut off value of ≤ 5.26 had been used, ~ 50% of prostate biopsies could have been avoided. At a cut off of ≤ 5.26, the PP Index had a sensitivity of 100% and specificity of 53.49%. The DCA revealed that at a threshold probability of 5%, the PP index can help to avoid 49.64% of the biopsies.
Conclusions
PSP94 as an adjunct marker along with PSA (PP Index) has the ability to differentiate between prostate cancer and BPH at PSA levels between 4–20 ng/ml and thus can help clinicians in better decision making.
Knowledge and attitude on family planning among Egyptian medical students: A Multicentric Cross-Sectional Study
Authors: Azzam Hajer , Kamel Basma , Esawy Ahmed , Awadh Mariam , Rabea Toka , Riad Nouran , Suliman Abdullah , Deibes Tasneem , Ayman Eman , Elbaz Aly , Ashraf Farah , Alemam Doaa 
Published: November 2024

Abstract

Background:
Family planning is a crucial practice that helps couples achieve their desired number of children and spacing between pregnancies. Effective family planning can prevent abortions, maternal morbidity, and maternal deaths. However, studies have shown that medical students need more knowledge regarding family planning. This study aims to assess the knowledge and attitude of Egyptian medical students towards family planning and the factors affecting them. Family planning not only supports individual health but also contributes to broader public health goals, including improved maternal and child health outcomes. Furthermore, enhancing medical students' understanding of family planning can positively influence their future clinical practice and patient counseling, ultimately leading to better healthcare delivery in their communities.
Methods:
This was a multi-centric cross-sectional descriptive study with an analytical component. We collected data using a multistage stratified cluster sampling method. The study tool was a questionnaire from a previously published study that showed an accepted reliability in a pilot study, a = 0.825 for knowledge and 0.906 for attitude. It included questions about family planning, contraceptive methods, and their providers in the students' localities. We analyzed data using IBM Statistical Package for Social Science (SPSS) software version 25. Results were considered statistically significant if the p-value was ≤ 0.05.
Results
This cross-sectional study surveyed 926 medical students, predominantly aged 17 to 27 years (mean 21.42 ± 1.90 years), with a balanced gender distribution (52.15% males). Most participants were enrolled in clinical years (63.4%) at governmental universities (74.9%). The majority of students showed poor knowledge of family planning (85.9%), despite significant variations in attitudes with a bigger percentage of inappropriate attitudes (52.7%). We also found that gender significantly influenced knowledge levels (p = 0.04), with higher female scores.
Conclusion
We report a prevalent deficiency in knowledge among Egyptian medical students, with females having better knowledge than males. Attitudes toward family planning are mostly inappropriate, which states the need for effective educational and awareness programs.
Trial Registration
Not applicable.
Study Protocol - The Australian National Child Hearing Health Outcomes Registry (ANCHOR): Connecting and collecting national data to drive child deafness research
Authors: Sung Valerie , Smith Libby , Elliott Kayla , Beswick Rachael , Ching Teresa Y.C. , Feller Hollie , Harkus Samantha , Kluk Karolina , Kong Kelvin , Liddle Karen , McHugh Lauren , McMahon Catherine M , O'Keeffe Isabel , O'Shea Amie , Pang Jermy , Parkinson Bonny , Porter Ann , Poulakis Zeffie , Shepard Emily , Shepherd Daisy , Van-Buynder Patricia , Waters Philip , Leigh Greg , Wake Melissa 
Published: November 2024

Abstract

Background
Despite early identification of deafness through universal newborn hearing screening, deaf and hard of hearing children can still face inequitable challenges in their development and life opportunities. Large scale registries, collecting standardised information including all individuals in a population with the relevant condition, can reveal variations in practices, processes, and outcomes, and identify targets for improvement. For childhood deafness, where practices, processes and outcomes all span multiple service sectors, data linkage is the only possible way to bring data together. Data linkage also minimises the burden and costs of data entry by service providers, increasing future sustainability of large-scale data for research.
Methods and Design:
The Australian National Child Hearing Health Outcomes Registry (ANCHOR) program has been established to connect and collect child hearing health information to drive research and service delivery improvements. Its vision is to give all deaf and hard of hearing children the best opportunities to reach their full potentials. The ANCHOR program aims to map Australia’s child hearing-specific services and datasets nationally and by state; create a single cross-state data system spanning two states for future national extension; develop a Core Outcome Set to measure what matters to children, young people, families, and services; and evaluate the costs and benefits of developing and maintaining ANCHOR. The ANCHOR program brings together expertise in child hearing health, education, lived experience, and research, with its guiding principle centred around community engagement.
Discussion
If successful, ANCHOR will provide a national platform to facilitate population-based research for deaf and hard of hearing children, a pathway to national reporting of developmental and educational outcomes, and a national child evidence base for future hearing policies, service delivery models, and supports. Ultimately, ANCHOR will drive research to improve models of service delivery and equity of access for deaf and hard of hearing children and their families, in particular those from deaf and Aboriginal and Torres Islander communities. This paper provides an overview of the established and evolving methodologies of the ANCHOR program to achieve its aims.
Data Augmentation in Cancer Image Classification Problem with Quantum GAN
Authors: Andra Muhammad Bagus , Yuliani Asri R. , Kadar Jimmy A. , Ramdan Ade , Pardede Hilman F. 
Published: November 2024

Abstract

In this paper, we propose a novel approach leveraging Quantum Generative Adversarial Networks (QGANs) for data augmentation in cancer image classification tasks. Cancer diagnosis from medical images plays a crucial role in early detection and treatment planning. However, imbalance nature of medical image data pose significant challenges for training accurate classification models. Our proposed methodology utilizes QGANs to generate synthetic medical images that closely mimic the characteristics of real cancer images classes, effectively addressing the data imbalance issue. Our QGAN architecture, which combines quantum circuits for the generator with a classical neural networks for the discriminator, was trained to synthesize medical images for augmentation. The performance of the convolutional neural networks (CNN) classifier was evaluated using accuracy and the area under the receiver operating characteristics curve (AUC-ROC) as metrics. Results show that augmented datasets significantly improve the classif ication performance. For instance, the AUC-ROC for the Basal Cell Carcinoma (BCC) class increased by 0.031, and the Dermatofibroma (DF) class saw a reduction in validation loss by 0.06. Moreover, segmentation-based QGAN training demonstrated considerable advantages in computational efficiency. The training time was reduced to just one hour, and inference times were less than a second per image.
Cervical pedicle screw fixation with the Tianji orthopedic surgical robot.
Authors: Shen Hao , Zhou Jinlong , Yu Lipeng 
Published: November 2024

Abstract

Objective
To compare the accuracy and safety of implanting cervical pedicle screws (CPS) between orthopedic surgical robot-assisted technique and traditional fluoroscopy-assisted free-hand technique.
Methods
Retrospective analysis of 95 patients treated with posterior cervical spinal surgery using either Tianji orthopedic surgical robot-assisted or traditional fluoroscopy-assisted free-hand pedicle screw implantation technology from March 2021 to March 2024, including 44 cases in the orthopedic surgical robot group and 51 cases in the traditional fluoroscopy group.
Results
Compared with the traditional fluoroscopy group, the orthopedic surgical robot group had better accuracy in screw implantation that is, a higher acceptable rate of screws (p = 0.0083). In addition, compared with the traditional fluoroscopy group, postoperative hospital stay was shorter in the orthopedic surgical robot group (p = 0.0447), but operation duration was longer (p = 0.0038). There was no significant difference in intraoperative blood loss between groups (p = 0.0872). There were 2 cases of cerebrospinal fluid leakage and 1 case of decreased left handgrip strength in the traditional fluoroscopy group, while only 1 case of cerebrospinal fluid leakage occurred in the orthopedic surgical robot group.
Conclusions
In this retrospective study, the accuracy of spine surgery with CSP implantation assisted by orthopedic surgical robot is often superior to that of spine surgery using traditional fluoroscopy-guided CPS implantation technique, while maintaining comparable safety.
Design of a surgical robot servo control system based on RBF neural network adaptive PID
Authors: Meng Panpan , Jin Xiaoyi , Niu Yibo , Kong Weibiao , Xi Ying 
Published: November 2024

Abstract

This paper presents the design of a servo control system for flexible endoscope surgical robots. For the system with a certain degree of uncertainty, an Radial Basis Function (RBF) neural network adaptive Proportional-Integral-Derivative (PID) control algorithm is proposed. This algorithm fully utilizes the adaptivity, self-learning ability, and excellent nonlinear approximation ability of RBF neural network to achieve real-time online adjustment of PID. We developed a mathematical model and transfer function of the servo and conducted a detailed simulation study with the help of MATLAB platform. The simulation results show that the RBF neural network adaptive PID control algorithm not only significantly outperforms the traditional PID controller in terms of performance, demonstrating stronger adaptability and anti-interference ability, but also greatly improves the control effect for nonlinear time-varying systems. We establish the block diagram of the servo control system on the LABVIEW platform and further confirmed the superiority of the algorithm in practical applications through experimental verification. This is specifically manifested in the effective reduction of system overshooting and the significant improvement of response speed and control accuracy.
Topological-insulating grain boundary networks for high-performance Fe2VAl thermoelectrics
Authors: Garmroudi Fabian , Serhiienko Illia , Parzer Michael , Ghosh Sanyukta , Ziolkowski Pawel , Oppitz Gregor , Nguyen Hieu Duy , Bourgès Cédric , Hattori Yuya , Riss Alexander , Steyrer Sebastian , Rogl Gerda , Rogl Peter , Schafler Erhard , Kawamoto Naoyuki , Müller Eckhard , Bauer Ernst , de Boor Johannes , Mori Takao 
Published: November 2024

Abstract

Decoupling charge and heat transport is essential for optimizing thermoelectric materials. Strategies to inhibit lattice-driven heat transport, however, also compromise carrier mobility, limiting the performance of most thermoelectrics, including Fe2VAl Heusler compounds. Here, we demonstrate an innovative approach, which bypasses this tradeoff: via liquid-phase sintering, we incorporate the archetypal topological insulator Bi1-xSbx between Fe2V0.95Ta0.1Al0.95 grains. Structural investigations alongside extensive thermoelectric and magneto-transport measurements reveal distinct modifications in the microstructure, a reduced lattice thermal conductivity and a simultaneously enhanced carrier mobility arising from topologically protected charge transport along the grain boundaries. This yields a huge performance boost - far beyond the effective-medium limit - and results in one of the highest figure of merits among both half- and full-Heusler compounds, z ≈ 1.6 x 10^-3 K^-1 (zT ≈ 0.5) at 295 K. Our findings highlight the potential of topological-insulating secondary phases to decouple charge and heat transport and call for more advanced theoretical studies of multiphase composites.
Effect of cholecalciferol supplementation on CVD, inflammation and bone metabolism markers in CKD: results of feasibility phase of randomized double blind controlled placebo trial
Authors: Kamboj Kajal , Manoharan Karthikeyan , Sharma Shubham , Khera Himanshi , Shafiq Nusrat , Kohli Harbir Singh , Yadav Ashok Kumar , Kumar Vivek , Jha Vivekanand 
Published: November 2024

Abstract

Background: Vitamin D deficiency is common in chronic kidney disease (CKD) and associated with cardiovascular disease (CVD) and bone mineral metabolism. Despite short term favourable effects, long term impact of cholecalciferol supplementation is unknown. We tested the effects of cholecalciferol supplementation on CVD outcome [major adverse cardiovascular events (MACE)], progression of CKD and markers of bone-mineral metabolism and inflammation in patients with pre-dialysis CKD.
Methods: The study was a single centre, prospective, randomized (1:1), placebo controlled, double blind clinical trial. Inclusion criteria were ages between 18-75 years, estimated glomerular filtration rate 10-45 ml/min/1.73m2, serum 25(OH)D levels 20-50 ng/ml and clinically stable course for last 3 months. After 2 weeks run-in phase, participants received either cholecalciferol 60000 IU once/2 weeks or matching placebo and followed up at every 3 months till 36 months after enrolment. All clinical, demographic characters and biomarkers were analysed at baseline and annual follow up.
Results: 692 participants were screened, out of which 126 were enrolled. However, 37 participants dropped out before randomization on account of COVID-19 related lockdowns or other reasons. The pilot phase was stopped in April 2023. Follow up course of 89 participants were available till that time: 46 participants were in the cholecalciferol group whereas 43 were in the placebo group. Both the groups were similar with respect to MACE events, need of renal replacement therapy and all-cause mortality. Over one year, serum 25 (OH)D increased in the cholecalciferol group [Mean diff between groups: 31.89, 95% CI: 20.46 to 43.32, P<0.001]. Serum calcium increased whereas C-reactive protein and bone specific alkaline phosphatase levels decreased in the cholecalciferol group.
Conclusions: Cholecalciferol treatment did not affect CVD outcome or progression of CKD in vitamin D insufficient patients with stage G3-G4 CKD, however it favourably affected markers of inflammation and bone metabolism in these patients.
Trial Registration: The trial was prospectively registered at the Clinical Trials Registry of India (www.ctri.nic.in, trial registration number CTRI/2019/05/019211 dated 20 May 2019).