bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of the Teaching Industry Program in Developing the Entrepreneurial Spirit of Graphic Design Students
Authors: Pertiwi Annisa , Masunah Juju , Prawira Nanang Ganda , Karyono Tri 
Published: December 2024

The creative industry in the hospitality sector faces a huge challenge to innovate in the digital era. The entrepreneurial competence of vocational students is important to meet the needs of the dynamic world of work. This study aims to evaluate the implementation of the Teaching Industry program in developing the entrepreneurial skills of students of the Diploma Program in Graphic Design, Widyatama University through a case study at the Malaka Hotel Bandung for the 2022–2024 period. This Teaching Industry program is designed using the Work-Based Learning approach to provide real work experience, Experiential Learning for hands-on learning, Collaborative Learning to train teamwork, and Project-Based Learning to complete tasks in the field of digital marketing, such as content planning, graphic design, photography, videography, and social media management. This study uses a mixed method, with a qualitative approach through interviews, observations, and document analysis (logbook, internship report, work presentation, and performance evaluation), as well as a quantitative approach through questionnaires and evaluation of supervisors. The results of the study showed the development of student entrepreneurship indicators, namely: 1) leadership collaboration and teamwork (88%), 2) motivation and confidence in achievement (82%), 3) initiative and courage to take risks (76%), and 4) independence and responsibility (70%). Overall, the program recorded a 79% success rate. Of the 17 students who participated, 3 of them were successfully recommended as contract employees, including 1 student who was recruited as a member of the Malacca Hotel Digital Marketing team. This program is effective in improving digital marketing technical skills as well as teamwork, leadership, and project management skills relevant to the needs of the creative industry.
Enhancing Malaria Detection and Classification using Convolutional Neural Networks - Vision Transformer Architecture
Authors: Ahishakiye Emmanuel , Kanobe Fredrick , Taremwa Danison , Nantongo Bartha Alexandra , Nkalubo Leonard , Ahimbisibwe Shallon 
Published: December 2024

Abstract

Malaria remains a significant global health challenge, particularly in sub-Saharan Africa. Despite advancements in treatment and prevention, malaria continues to cause substantial morbidity and mortality, particularly among vulnerable populations such as children and pregnant women. Although effective, traditional diagnostic methods, such as microscopy, are time-consuming and require skilled personnel prone to human error, leading to delays in diagnosis and treatment. More so, existing machine learning models used in malaria detection and classification have low performance and overfitting issues. This study presents an enhanced malaria detection and classification model using an ensemble of Convolutional Neural Networks (CNN) and Vision Transformers (ViT). The proposed ensemble model, which combines CNN and ViT, outperforms each individual model, achieving an accuracy of 99.64%, precision of 99.23%, recall of 99.75%, F1 score of 99.51%, and a cross-entropy loss of 0.01. The proposed model demonstrated superior performance compared to those reported in the literature. These results highlight the potential of the CNN-ViT ensemble model for accurate and reliable malaria detection, offering a significant improvement over existing methods.
Spectroscopic and molecular insights into humic substances in compost amended with varying biochar levels
Authors: Zhu Nennen , Cheng Ao , Yu Xufang , Zhou Xiujuan , Liu Xiaolong , Ji Wenchao , Cao Tao , Fan Xingjun 
Published: December 2024

Abstract

This study explores the effects of biochar (BC) amendments at varying levels (0%, 1%, 2%, and 5%) on the molecular and structural characteristics of humic substances (HS), specifically humic acids (HA) and fulvic acids (FA), in compost. The addition of BC significantly increased the HA content by 13-16% while reducing the FA content by 12-32%, with the most pronounced effects observed at a 5% BC addition. Spectroscopic analyses, including UV-Vis and fluorescence, revealed enhanced aromaticity and molecular weight (MW) of HA, driven by microbial activity and polymerization facilitated by BC amendments, whereas FA aromaticity remained largely unchanged. The weight-average molecular weight (Mw) and number-average molecular weight (Mn) of HA increased significantly, indicating improved humification and stabilization. Fourier-transform infrared (FTIR) spectroscopy showed that BC addition had minimal impact on the functional group composition of HA and FA but altered the proportions of carbon types. Electron paramagnetic resonance (EPR) analysis demonstrated higher persistent free radical (PFR) levels in HA, correlating with increased molecular size and a higher degree of condensation. These findings underscore the potential of BC amendments to enhance compost quality by promoting the formation of stable and complex humic substances with improved reactivity.
Prognostic Nomogram and Risk Prediction Management for 'Vascular Mimicry' in Oral Squamous Cell Carcinoma Based on MMP3
Authors: Que Fan , Wang Jie , Li Yulin , Qin Dan , Long Jiao , Nie Minhai , Liu Xuqian 
Published: December 2024

Abstract

Oral squamous cell carcinoma has a high incidence rate in the population and a high metastasis rate. Despite ongoing improvements by clinicians in diagnosis and treatment, effective enhancement of survival rates remains elusive. In this study, it was found that MMP-3 can promote the formation of vascular mimicry in oral squamous cell carcinoma, facilitating tumor cells invasion and metastasis. Survival analysis reveals a negative correlation between matrix metalloproteinase 3 and overall survival in patients; multivariable Cox analysis and nomograms indicate that matrix metalloproteinase 3 is a biomarker of poor prognosis in oral squamous cell carcinoma. In summary, our findings suggest that MMP3 serves as a biomarker for unfavorable prognosis in patients with oral squamous cell carcinoma, and research targeting matrix metalloproteinase 3 as a therapeutic approach may represent a valuable new treatment strategy.
BushenHuoxue formula improved osteoporosis by suppressing the miR370 expression to directly alter the MAPK cascade and NFIC regulator
Authors: Chen Yuqi , Huang Yifei , Zheng Yushan , Yan Feng , Mao Dun , Liu Yong , Wang Qiang , Shao Shuaiming , Tan Lihui , Dong Jianjian , Jin Chenkai , Wei Rong 
Published: December 2024

Abstract

Osteoporosis (OP) is a major public health problem. Previously, we found that BSHXF could alleviate OP symptoms. However, the underlying mechanism remained unclear. Here, we found that BSHXF alleviate PMO symptoms in mouse model, while abundant exosomes involved in the Postmenopausal osteoporosis (PMO) pathogenesis and BSHXF treatment. Further exosomal microRNA sequencing showed that DEMs from exosomes involved in PMO-related signaling pathways, especially MAPK cascade. BSHXF significantly altered the expressions of 25 OP-related exo-miRNAs which performed hub functions in PMO pathogenesis, especially miR370. MiR370 could suppress the expressions of PMO-related genes NFIC and MAPK13 by directly binding to their coding sequence. Importantly, genistein was the hub compounds in BSHXF, and could suppress the abnormal upregulation of miR370 in the exosome by directly interacting with STAT3.These findings shed light on the importance of exo-miRNAs in PMO pathogenesis and the mechanisms of BSHXF treatment in improving PMO.
Astragalus Membranaceus: Exploring its Protective Role in Heat Stroke via Integrated Transcriptomic and Molecular Docking Approaches
Authors: Yin Defeng , Yao Yandong , Guo Qin , Jiang Hao , Hu Yonglan , Liu Lu , Jin Kaiyu , Hu Yingchun 
Published: December 2024

Abstract

Objective: This study aims to explore the therapeutic potential of Astrolus Membranaceus in treating heatstroke and its potential therapeutic targets.
Method: This study was conducted at the Affiliated Hospital of Southwest Medical University, and peripheral blood samples were collected from 10 heatstroke patients (HS=10) and 10 healthy individuals (NC=10) for RNA sequencing. Perform RNA differential analysis using the DESeq2 software package. In addition, the active ingredients and targets of Astragalus membranaceus were screened using the TCMSP database. Intersection the target and differential RNA to obtain the cross target. Then perform GO analysis and KEGG analysis on the intersection targets. Build a protein interaction network with cross targets using STRING website and Cytoscape software, and perform molecular docking between core targets and active molecules using AutoDock Tools.
Results: RNA sequencing results showed that compared with the NC group, the HS group had a total of 2042 differentially expressed RNAs. After taking the intersection of Astrolus Membranaceus targets and differentially expressed RNA, 23 intersecting targets were obtained. GO analysis found that the enrichment of cellular components of cross genes is mainly in the extracellular region. The molecular functional enrichment of cross genes mainly involves molecular function regulators. The biological processes related to cross factors mainly include regulation of molecular function, regulation of multicellular organic processes, and response to stress. KEGG analysis showed that the enriched pathways in the crossover genes mainly include the MAPK signaling pathway. The key targets TP53, BCL2, and MMP9 in the protein-protein interaction network were identified using cytoHubba. The molecular docking results indicate that quercetin forms hydrogen bonds with TP53, BCL2, and MMP9, with low binding energies.
Conclusion: This study reveals the potential molecular mechanism of Astrolus Membranaceus in treating heatstroke, providing a scientific basis for further drug development and clinical application.
Trajectory of lung ultrasound scores in preterm infants at risk for bronchopulmonary dysplasia: a prospective observational study
Authors: Weinstein Rachel , Montoya Cassandra , Horowitz Russell , Murthy Karna , Caldarelli Leslie , Marshall Stephaine 
Published: December 2024

Abstract

Objective: To quantify the trajectory of lung ultrasound scores (LUSSc) and estimate its association on inpatient respiratory trajectories in preterm infants with potentially evolving bronchopulmonary dysplasia (BPD)
Study Design: We measured LUSSc prospectively in infants < 32 weeks’ gestation weekly from 2 weeks of life through 44 weeks’ post-menstrual age (PMA) or discharge. The primary outcome was the age, in PMA, to achieve liberation of respiratory support (LRS) defined as room air or < 1 L/min (FiO2 = 100%).
Result: In 16 infants, 10 patients had Grade 2-3 BPD, and LUSSc declined over time. The time to achieve LRS was 43 weeks’ PMA (SD 12.5). Using the maximum LUSSc each infant had between 30-32 weeks’ PMA, each 1-point increase in the LUSSc was independently associated with a 12-day increase in the time to achieve LRS.
Conclusion: LUSSc may serve as a diagnostic marker for inpatient respiratory trajectories of preterm infants with evolving BPD.
MOAC-RT: Personalized Multi-Objective Radiotherapy using Actor-Critic Deep Reinforcement Learning
Authors: Khosravi Ava , Roayaei Mehdy 
Published: December 2024

Abstract

Radiotherapy (RT) stands as on the common approaches in the treatment of cancer patients, delivering a specified radiation dosage across multiple sessions, progressively targeting the tumor for gradual eradication. Traditional RT uses fixed schedules and constant dose fractions. However, different patients may respond differently to radiation treatment based on different reasons. Effective treatment planning is crucial in RT to maximize treatment quality, balancing tumor irradiation and healthy tissue preservation, making it a multi-objective problem. Also, since this treatment is conducted over several sessions, it is inherently a sequential decision-making problem. This paper models RT treatment planning as a multi-objective reinforcement learning problem, using a 2D tumor growth simulation incorporating factors like oxygen levels, glucose distribution, and cell status. We propose an actor-critic deep reinforcement learning approach base on MobileNetV2 pretrained network, called MOAC-RT, to optimize the RT treatment plan (dosage and schedule) for radiotherapy. The results show that personalized RT treatment plan, where a dose between 1 to 2 Gy is delivered to the tumor based on its status, and the rest time is chosen considering the effect of radiation on the tumor and the status of healthy cell, can outperform standard approach and previous works as it accomplishes the treatment in less time and with fewer prescribed doses, requiring a reduced number of sessions.
The BREATHE project: An observational prospective cohort integrating clinical data, blood samples and tumor tissue from newly diagnosed patients with lung cancer
Authors: Pons-Tostivint Elvire , Denis Marc Grégoire , Corvaisier-Chiron Murielle , Sauzay Chloé , Lacoste Philippe , Sagan Christine , Chene Anne-Laure , Chen Jeanne , Hulo Pauline , Samarut Edouard , Salaud Céline , Goronflot Thomas , Blanquart Christophe , Fradin Delphine 
Published: December 2024

Abstract

Background: Lung cancer treatment is a constantly evolving field, with an acceleration of innovative therapies over the last decade. Patients included in clinical trials are highly selected, thus efficacy of therapies in all comers are still scarce. Despite significant progress, mortality remains high, disease progression occurs in most patients, and the mechanisms underlying resistance to therapies remain poorly understood. The BREATHE project (Biocollection for Research in Thoracic Cancer) is a prospective cohort including all newly diagnosed patients with lung cancer at the University Hospital of Nantes. We herein describe the study background, design and methods used for this cohort.
Methods: This is a single-center, prospective, observational study of an exposure-defined cohort of patients newly diagnosed with lung cancer. Data included sociodemographic characteristics, medical status, tumour characteristics, lines of therapy throughout patient follow-up, and delay intervals. For the follow-up, information regarding recurrences and mortality is continually updated. Systematic plasma, PBMC and circulating tumor DNA samples are collected at diagnosis, during follow-up and at relapse, and also tumor tissue at diagnosis and at relapse when available. We plan to enrol a minimum of 700 patients in 5 years, with a follow-up period of 5 years.
Discussion: This cohort will provide insights into the real use, efficacy, and toxicities of anti-cancer treatments administered administered to a representative, unselected population of patients with newly diagnosed lung cancer. Additionally, we aim to gain a better understanding of complex therapeutic sequences including multimodal treatment, and also to collect information on patients with rare genomic alterations. Finally, several translational studies will be conducted to characterize the mechanisms of resistance to therapeutic interventions.
Clinical Trial Number: NCT06481813 (Registration dates 2024-07-01)
Deep learning-based skin lesion classification for cancer detection
Authors: K Premnath , P Sundaravadivel , R Augustian Isaac , K Srimathi , M Vaishnavi , N Sathya 
Published: December 2024

Abstract

Early detection is crucial for a successful remedy of skin cancer and an upsurge of longevity, as it is one of the most ubiquitous kinds of cancer globally. This project introduces a skin cancer detection system that employs Convolutional Neural Networks (CNN) to autonomously classify skin lesions into distinct categories based on image inputs. The system employs deep learning techniques to analyse images and forecast the presence of several types of malignancy for the skin, including malignancies of basal cells and melanoma. The algorithm was honed using a dataset of tagged skin lesion pictures, incorporating advanced techniques such as Batch Normalization and Max Pooling to prevent overfitting and improve accuracy. In order to minimize overfitting, dropout layers were included, and the architecture was improved to optimize the model's functionality. The prediction findings are later displayed through a web-based interface that was constructed using Flask. Users are able to submit skin pictures and receive thorough findings, which include information about the expected cancer type. The objective of this system is to facilitate the diagnosis of skin cancer more efficiently for dermatologists and healthcare professionals by offering automated, high-accuracy predictions. The system may be expanded to include a mobile application in the future, which would provide a wider range of accessibility for the rapid identification of malignancy.
WITHDRAWN: Integrative transcriptomic and proteomic analysis reveals that SERPING1 inhibits neuronal proliferation via the CaMKII-CREB-BDNF pathway in schizophrenia
Authors: Li Xing , Ti Wang , Li Wang , Wei Biao 
Published: December 2024

Abstract

30 December, 2024. Research Square has withdrawn this preprint due to overlap with unpublished work by different authors.
The impact of multilingual science popularization videos based on the transtheoretical model and whole-cycle management concepts on the self-management behavior capacity of liver cancer patients from ethnic minorities
Authors: Jiang Yangyue , Liu Chunhong , He Bingrong , Feng Lijuan , Yu Shizhu , Du Jing , Lin Ying , Bei Jia , Wei Shanshan , Tang Xiaoli , Huang Guiyu 
Published: December 2024

Abstract

Objective To evaluate the impact of "Prevention-Treatment-Rehabilitation" multilingual popular science videos on the self-management behavioral abilities of ethnic minority patients with liver cancer.Methods A self-controlled before-and-after study design was adopted. Ethnic minority liver cancer patients hospitalized in two tertiary hospitals from September 2024 to November 2024 were conveniently selected as the study participants. By integrating the Transtheoretical Model (TTM) and the concept of comprehensive liver cancer management, multilingual science popularization videos in Mandarin, Yi, and Tibetan languages were developed. These videos were promoted both online and offline. After watching the videos, their self-management levels were assessed using the Liver Cancer Patient Self-Management Behavior Scale before and after the intervention.Results After the intervention, significant improvements were observed in all four dimensions of patients' self-management abilities, with statistically significant differences (P < 0.001). The total self-management behavior score increased from 113.53 ± 17.26 to 131.38 ± 9.783, showing a statistically significant difference (P < 0.001). Male patients, older individuals, those with lower education levels, private enterprise employees, patients with urban-rural resident medical insurance or without insurance, and patients with smoking or drinking habits exhibited more significant improvements after the intervention (P < 0.05).Conclusion Health education based on "Prevention-Treatment-Rehabilitation" multilingual popular science videos helps improve the self-management behavioral abilities of ethnic minority patients with liver cancer.
Constant Ovulation During Oral Contraceptive Treatment: Follicle-Stimulating Hormone-Secreting Pituitary Adenoma Case Report and Literature Review
Authors: Yang Yang , Qiao Lin , Zhang Jing 
Published: December 2024

Abstract

Introduction
FSH-producing pituitary neuroendocrine tumor is very rare and usually present with menstrual disorders, ovarian cysts, polycystic ovary morphology, etc. It’s often confused with polycystic ovary syndrome and is difficult to diagnose. Missed or misdiagnosis may lead to unnecessary surgical injury or severe neurologic damage.
Case presentation
We describe the case of a 37-year-old woman with persistent menstrual disturbances and ovarian cysts. Because of unceasing ovulation after usage of combined oral contraceptive she was suspected of having endogenous uncontrolled FSH and eventually a pituitary adenoma was found. In addition, we review the features of onset, diagnostic history, treatment and prognosis of previous similar reports.
Conclusion
We find the symptoms of FSH-secreting pituitary adenomas puzzling. Mild cases are easily overlooked, and severe cases are easily misdiagnosed as ovarian hyperstimulation syndrome and ovarian tumors and receive unnecessary pharmacological and surgical interventions. Attention to abnormal sex hormones is key to diagnosis, and prompt surgical tumor removal is important.
Designing a T cell multi-epitope vaccine against hRSV with reverse vaccinology: an immunoinformatics approach
Authors: Guan Peibin , Qi Congyan , Xu Guojin , Sheng Can , Sun Siqi , Zhou Zhicheng , Jia Shulei L. 
Published: December 2024

Abstract

As an infectious viral pathogen, human respiratory syncytial virus (hRSV) can cause severe respiratory infections and is recognized as one of the highest priority pathogens by the World Health Organization (WHO). Although vaccines play an important role in disease prevention and transmission, the wild-type virus is usually prone to immune escape due to the relatively high mutation rate of biological proteins. Therefore, designing a broad-spectrum hRSV vaccine is essential to provide extensive protection against multiple viral variants. Using a consensus sequence approach, we designed a broad-spectrum T-cell epitope vaccine composed of 382 amino acids, consisting of 12 CTLs and 5 HTLs from the fusion protein and glycoprotein. The designed multi-epitope vaccine was expected to have non-allergenicity, high population coverage, strong antigenicity and immunogenicity, appropriate physical and chemical properties, and high solubility. Meanwhile, the structure of the vaccine had a high similarity to that of the natural virus. In addition, through structural biology analysis, the constructed vaccine achieved robust structural compactness and binding stability. Computer-generated immunological simulations indicated that the vaccine could elicit realistic immune responses in humans. In conclusion, the broad-spectrum hRSV vaccine could be an excellent candidate for preventing hRSV infection. The employed prediction pipeline proved to be an efficient method for screening immunogenic epitopes of additional pathogens.