bluuebunny/crossref_metadata_2025_split huggingface dataset:
A high-performance metabolomic diagnostic panel for early-stage non-small cell lung cancer detection based on UPLC‒MS/MS
Authors: Wan Lingling , Liu Qingyi , Liang Di , Guo Yongdong , Liu Guangjie , Ren Jinxia , Gu Xuexiu , He Yutong , Shan Baoen 
Published: May 2024

Abstract

Lung cancer is the most common cancer in the world and has a consistently high mortality rate, with the majority of patients being diagnosed at an advanced stage. This study aimed to identify potential biomarkers through metabolomics to provide clues for the diagnosis and treatment of early-stage non-small cell lung cancer (NSCLC). We enrolled two prospective cohorts with a total of 180 patients (115 patients with I-II a NSCLC and 65 healthy controls) and tested serum samples for tumour markers, cytokines, and 306 metabolites by ultrahigh-performance liquid chromatography coupled with tandem mass spectrometry (UPLC‒MS/MS). In both the discovery and validation cohorts, there were 57 differentially abundant metabolites in the serum between patients with early-stage NSCLC and healthy controls, which were concentrated in the fatty acid metabolic pathway and amino acid metabolic pathway. Finally, three metabolites with significant differences were screened as isoleucine, 5Z-dodecenoic acid and 9E-tetradecenoic acid. The AUC of centralized combined diagnosis reached 0.95. This study provides new evidence that abnormalities in valine, leucine, and isoleucine metabolism and dysregulation of fatty acid synthesis may play important roles in the development of NSCLC.
Exploration of mitochondrial-related biomarkers and regulatory mechanisms in pulmonary hypertension
Authors: Hao Yu , Wu Peng , Zhao Wenli , Cheng Hua , Zhang Hui , Wu Hailiang , Chen Dapeng , Ma Xueping , Yan Ning 
Published: May 2024

Abstract

Multiple mechanisms of mitochondrial dysfunction have been implicated in the pathogenesis of pulmonary hypertension (PH). Thus, this study aims to identify biomarkers associated with mitochondrial-related genes (MRGs) in patients with PH. The GSE33463 (blood training set), GSE15197 (tissue training set), GSE113439 (external validation set) and MRGs were all acquired from public databases. Differential expression analysis was undertaken to selected differentially expressed genes (DEGs) from blood and tissue training set, respectively. Then, the DEGs were intersected with MRGs to identify potential candidate genes, followed by detecting their functions via enrichment analysis. Moreover, crucial genes were obtained by overlapping the signature genes from least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE). Based on the receiver operating characteristic (ROC) curves of crucial genes, the genes with area under curves (AUC) value ≥ 0.7 were deemed as biomarkers. Gene Set Enrichment Analysis (GSEA), multiple regulatory networks and drug prediction were applied to explore biomarkers’ molecular mechanism. A total of 144 DEGs (78 up-DEGs and 66 down-DEGs) were obtained by intersecting 751 DEGs1 in blood training set and 6,155 DEGs2 in tissue training set. Next, taking the intersection of 144 DEGs and 1,136 MRGs, 7 candidate genes (ALAS2, CPT2, TST, SLC25A39, COQ10B, MRPS30 and MCL1) were acquired and enriched in multiple mitochondria related pathways, like mitochondrial inner membrane. MRPS30, ALAS2 and TST were recognized as biomarkers depending on the 4 crucial genes (CPT2, MRPS30, ALAS2 and TST) through overlapping signature genes by two machine learning algorithms. The immune analysis showed that the percentage of 7 kinds of immune cells (e.g. B cells naive, monocytes, neutrophils) were differed markedly at control and PH groups, and monocytes were related to all three biomarkers. In 3 datasets, the expression of ALAS2 was up-regulated in PH, while MRPS30 was down-regulated in PH. And bisphenol A was predicted by ALAS2, MRPS30 and TST. Three biomarkers (ALAS2, MRPS30 and TST) associated with MRGs was identified and verified, which provided a new perspective to probe the mechanism of MRGs in PH.
Effectiveness of a Protocol with Antimicrobial Photodynamic Therapy for Treating Osteoradionecrosis: A Retrospective Study
Authors: Ferigatto Júlia Lopes , Coracin Fábio Luiz , Tanimoto Hélio Massaiochi , Viola Vivian Palata , Tieghi-Neto Victor , Prado Diogo Dias , Hirai Wellinton Yoshio , Teodoro Valiana Alves , Vazquez Fabiana Lima , Rios Simone Hassan Khatib 
Published: May 2024

Abstract

Objective: To compare the treatment of ORN using a protocol containing antimicrobial photodynamic therapy with a conventional protocol.
Methodology: A retrospective study of 55 patients who had presented with ORN at a reference hospital between 2002 and 2021 and received treatment by two clinical protocols was conducted. Clinical treatment success was defined as the epithelialization of the ORN lesion and absence of painful symptoms and local infection.
Results: The study included 53 ORN lesions with a median ORN development time of 30 months; 83.02% were men, with a median age of 58 years. The main etiologies of ORN included prosthetic trauma (28.30%) and dental extractions caused by infection (32.07%). Satisfactory oral hygiene and lesion hygiene, when compared with the outcome of lesion epithelialization, were found to be protective factors for achieving clinical success (p ≤ 0.0001). ORN developed more rapidly in oral cavity tumors (median of 8 months) than in oropharyngeal tumors (39 months) (p = 0.01).
Conclusion: Compared with the conventional protocol, the proposed protocol demonstrated effectiveness, achieving clinical success in a shorter time in 75% of the analyzed lesions (p ≤ 0.0001). Maintaining oral and lesion hygiene is a protective factor for achieving clinical success. ORN develops more rapidly in oral cavity tumors.
Effectiveness of a dynamic seat cushion on recovery and recurrence of neck and low back pain in office workers: a secondary analysis of a randomized controlled trial
Authors: Channak Sirinant , Speklé Erwin M. , Beek Allard J. , Janwantanakul Prawit 
Published: May 2024

Abstract

Background: Neck and low back pain are prevalent issues among office workers due to prolonged sitting, necessitating effective interventions. Dynamic seat cushion, designed to promote postural shifts have emerged as promising solutions to address these concern. This study aims to evaluate the effectiveness of a dynamic seat cushion on recovery and recurrence of neck and low back pain in office workers.
Methods: This study used 6-month follow-up data of a randomized controlled trial, involving 66 office workers who reported pain in the trial. At baseline, participants were cluster-randomized into an intervention group, which received a dynamic seat cushion designed to encourage postural shifts, or a control group, which received a placebo seat pad. Health outcomes included recovery duration and recurrence of pain. Analyses utilized log rank test and Cox proportional hazard models.
Results: In the intervention group, the recovery rate from neck and low back pain was 100%, which was 86% for the control group. The median recovery duration in the intervention group (1 month) was two months shorter than in the control group (3 months). The intervention group had a higher probability of recovery compared to the control group (HRadj 4.35, 95% CI 1.87 – 10.11; p < 0.01). The recurrence rate of neck and low back pain was 27% in the intervention group, which was 75% in the control group. The Hazard Ratio, after adjustment, for the intervention group compared to the control group was 0.50 (95% CI = 0.11 – 2.12).
Conclusions: A dynamic seat cushion that encourages postural shifts shortened recovery duration of neck and low back pain among office workers. Due to small numbers, however, a potentially relevant reduction of recurrence of neck and low back pain could not be statistically confirmed.
Thai Clinical Trials Registry: TCTR20230623002 (23/06/2023).
Employing randomized controlled clinical settings, research explores the impact of strain-counter-strain on the management of lower back myofascial pain syndrome
Authors: Koura Ghada Rashad , Selim Mohamed Naeem , Elshiwi Ahmed Mohamed Fathi , Asiri Amani Abdu Mohammed , Alqahtani Reem Hadi Jowaied , Elimy Doaa Ayoub , Alshehri Mohammed Abdullah , Alnakhi Hani Hassan , Ahmad Fuzail , Ahmad Irshad 
Published: May 2024

Abstract

The purpose of this study is to analyse the impact of incorporating the strain-counter-strain (SCS) approach into physical therapy exercises for patients with lower back myofascial pain syndrome (MPS) on pain levels, ROM, and functional impairment.
Methods:The experimental group consisted of thirty individuals with lower back MPS, while the control group included forty patients. When it came to physical treatment, one group used the SCS method and exercised four days a week, whereas the other group only exercised three days a week. There was a pre- and post-test lasting four weeks for each and every outcome measure.
Results:After treatment, the study group outperformed the control group in most metrics (VAS, lumber ROM, and ODI) (p 0.001), except for left-side bending ROM (p > 0.05).
Conclusion: Lower back MPS patients may benefit more from a combination of physical therapy exercises and the SCS approach when it comes to pain, range of motion (ROM), and functional impairment than from individual physical therapy treatments.
Impact of dental pulp stromal cells-derived small extracellular vesicles on the properties and behavior of dental pulp stromal cells: An invitro-study
Authors: Hammouda Dina A. , Mansour Alaa M , Zaher Ahmed R. , Grawish Mohammed E. 
Published: May 2024

Abstract

Background
Dental pulp stromal cells-derived small extracellular vesicles (DPSCs-sEVs) had shown immunomodulatory, anti-inflammatory, and tissue function restorative abilities. Therefore, DPSCs-sEVs should be considered as a promising regenerative tool for dentin-pulp complex or whole pulp regeneration. This study aimed to evaluate the effect of DPSCs-sEVs on the proliferation rate, migration capability and expression pattern of DPSCs, in comparison with mineral trioxide aggregate (MTA).
Methods
DPSCs-sEVs were isolated from rats’ incisors by ultracentrifugation technique. Morphology, size and protein concentration of DPSCs-sEVs were monitored and analyzed using transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA) and bicinchoninic acid assay (BCA). In addition, the tetraspanin proteins CD81, CD63 and the cytosolic protein syntenin of sEVs markers were immunodetected using Western blotting. Cell cultures of DPSCs from the third passage were left untreated and considered as a control (group I), whereas other cultured cells were treated with 50 µg/mL DPSCs-sEVs (group II), 0.2 mg/mL MTA-conditioned medium (group III), or their combination (50 µg/mL DPSCs-sEVs + 0.2 mg/mL MTA-conditioned media (group IV). MTT assay, transwell migration assay, and real-time polymerase chain reaction were used for assessing proliferation, migration and expression patterns.
Results
The DPSCs-sEVs increased DPSCs proliferation and MTA enhanced their effects. The proliferative capacity of DPSCs treated with 50 µg/mL DPSCs-sEVs + 0.2 mg/mL MTA-conditioned medium was significantly higher when compared with the other groups. The cell migration was more prominent in the group treated with 0.2 mg/mL MTA-conditioned medium than in the group treated with 50 µg/mL DPSCs-sEVs. DPSCs treated with 50 µg/mL DPSCs-sEVs + 0.2 mg/mL MTA-conditioned medium showed a significant increase in the migration ability of DPSCs, in comparison with other ones. Moreover, the combination group showed the greatest expression of dentin sialophosphoprotein, osteocalcin, collagen type I and Runt-related transcription factor 2.
Conclusion
MTA and sEVs together could be a powerful combination for regenerative endodontics.
Multi-omics integration analysis and association study reveal the potential of ADIPOQ function in gestational diabetes mellitus
Authors: Litao Sun , Li Xiaoying , Jia Tianshuang , Wu Yingnan , Peng Yanqing , Feng Yanan , Gong Liping , Dong Shuang 
Published: May 2024

Abstract

AimTo investigate the role of ADIPOQ gene in gestational diabetes mellitus (GDM).
Methods
We genotyped SNPs rs266729 and rs1501299 of ADIPOQ gene in1157 pregnant women of north Chinese Han population. Additionally, we used conventional bioinformatics analysis methods to conduct multi-omics analysis (transcriptome, epigenome, and single cell level) of ADIPOQ regulated GDM.
Results
The fetal umbilical artery doppler systolic blood flow velocity/diastolic blood flow velocity (S/D) ratio of umbilical artery in GDM patients with CC genotype of rs266729 and GG genotype of rs1501299 was higher than control. Single cell analysis suggested that ADIPOQ was expressed in extravillous trophoblast (EVT), T cell, monocytes, myelocyte, NK cell and syncytiotrophoblast (SCT). Functional enrichment analysis showed ADIPOQ gene was associated with response to nutrient levels, fat cell differentiation.
Conclusion
The findings of our study indicate a correlation between SNPs of ADIPOQ in GDM patients, and ADIPOQ is involved in the transcriptional regulation of GDM.
Natural resource pulses influence social-network dynamics: experimental evidence from a tree cavity-dependent bird community
Authors: Norris Andrea Rose , Martin Kathy 
Published: May 2024

Abstract

To explore how social networks might respond to ecological change we investigated the impact of two natural resource pulses at the foraging and nidic levels on intra- and inter-specific territorial behaviour of two species that co-occur year-round in multi-species groups. We simulated conspecific and heterospecific territorial intrusions in two insectivorous cavity-nesting species using 974 model presentations with territorial song playbacks during and after a dual resource pulse of insect (bark beetle) prey and nest cavities across 5 years in British Columbia, Canada. As beetle abundance increased, both species increased aggression toward conspecific intruders, but at peak beetle abundance, the (typically) subordinate generalist insectivore, mountain chickadee (Poecile gambeli), attacked model intruders more frequently than did the dominant bark insectivore, red-breasted nuthatch (Sitta canadensis). Surprisingly, chickadees shifted to an inter-specific resource defense strategy, responding more aggressively to nuthatch intruders than to conspecifics. Thus, obligate secondary cavity nesting chickadees dominated facultative excavating nuthatches, providing evidence of a dominance reversal at the nesting guild level. Both insectivores increased defense of high-quality territories, with increasing availability of food resources. The reversal in the interspecific dominance hierarchy suggests that behavioural mechanisms governing social networks and community structure may change during resource pulses. Overall, we suggest that social networks of chickadees and nuthatches are dynamic with high complexity and flexibility to major ecological disruptions. Future work that examines the fitness consequences of temporal variation in social network dynamics and resiliency could help to reveal evolutionary mechanisms by which these species co-exist.
Formation Mechanism and Physical Properties of Particle Ejection during Laser Cutting of Metal Alloys
Authors: Nie Yi , Low Kenny W Q , Liu Zhongkui , Yang Lihang , Wang Yuxuan , Li Tianqi , Li Haonan , He Yinfeng 
Published: May 2024

Abstract

Micro-scale particle ejection, an inevitable second emission during laser cutting of metal alloys, leads to significant hazards to operators’ lung and workpiece’s surface quality. This study established a Multiphysics numerical model to investigate the formation mechanism and physical properties of the ejected particles. An incompressible Newtonian laminar non-isothermal multiphase fluid flow was modelled for the laser-metal interaction process by implementing the governing equations, sources terms representing the laser energy and dynamic assist gas pressure, and melting and solidification effect. The volume of fluid (VOF) method, together with dynamic mesh adaption, was employed to track the metal-air interface of the two-phase fluid model. The physical formation phenomena of particles ejected from the kerf front were illustrated by the temperature and morphology evolution history. The dynamic behaviour of the ejected particles was revealed by their shape, size and velocity distribution over time using VOF-to-DPM technique. The effect of laser power and assist gas pressure on the equivalent diameter and velocity of the ejected particles were further studied quantitively to assist the development of subsequent exhaustion systems for secondary emissions. The developed numerical model takes a step forward in understanding the mechanics at the kerf regions and assisting the development of subsequent exhaustion systems for secondary emissions during laser cutting of high-end components.
Spatial Single-Cell Transcriptomic Analysis in Breast Cancer Reveals Potential Biomarkers for PD-1 Blockade Therapy
Authors: Wang Nan , Song Yan , Hong Weifeng , Mo Hongnan , Song Zhentao , Dai Wenshuang , Wang Lianshui , Zhang Haiyang , Zhang Yuyan , Zhang Qi , Zhang Hui , Zhang Tao , Wang Yuyi , Li Yeyu , Ma Jiafei , Shao Changchao , Yu Min , Qian Haili , Ma Fei , Ding Zhiyong 
Published: May 2024

Abstract

Introduction:
Spatially defined cellular interaction and crosstalk are eminently important in deciphering key molecular messages driving oncogenesis and disease progression. To date, methods enabling high-plex true single-cell resolution profiling under spatial settings are gradually becoming available and those majorly include the expansion of spatial transcriptomics (ST) being utilized.
Results:
Through in-depth spatial single-cell profiling on four breast cancer (BC) tissue samples bearing distinct biological characteristics, we evaluated the analytical performance benchmarked against conventional pathology and by selecting pre-defined region-of-interests (ROIs), we consolidated the technical robustness of this method in defining different molecular subtypes at the transcript level matching with canonical immunohistochemistry. Moreover, we demonstrated that high-dimensional ST data is capable of identifying a major cellular network inter-wired via macrophage and cytotoxic T cells interaction in tumor adjacent cellular neighborhood via PD-L1/CD80 and CD86/CTLA4 axis, a phenomenon reflecting an improved PD-1 mediated drug response observed clinically. By incorporating open-source computational methods (Tangram and SpaGE), we found compatible inference tools for in-situ expression imputation, an approach generalizable to enable deeper spatial profiling using Xenium in-situ or other parallel approaches.
Discussion:
Our spatial single-cell ST sets as a technical and analytical prototype for those using similar approaches for high-dimensional in-situ profiling work.
Materials:
We applied a newly developed spatial single-cell technology (Xenium in-situ) to interrogate the spatial single-cell architecture of the complex tumor microenvironment on a set of breast cancer patient tissues (luminal-type, HER2 2+/HR- and triple negative breast cancer, TNBC) and benchmarked against multiple clinicopathological features using bioinformatic tools.
Mango Fruit Diseases Severity Estimation based on Image Segmentation and Deep Learning
Authors: FAYE Demba , DIOP Idy , MBAYE Nalla , DIONE Doudou , DIEDHIOU Marius Mintu 
Published: May 2024

Abstract

Plant disease severity is the ratio between the surface area of disease symptoms and the total surface area of the plant unit (e.g. fruit, leaf). It is related to plant disease diagnosis and has several advantages for farmers. It is therefore a key element in the protection and management of plant diseases. In the literature, there are three proposed categories of plant disease severity determination solutions: those based on segmentation algorithms, those based on classical ML algorithms and those based on DL algorgorithms. Despite their many advantages, these solutions have a number of limitations, including i) subjectivity in data labeling, ii) loss of information on disease lesion contours during (manual) data labeling, and iii) the proposed solutions have focused on estimating plant disease severity from leaves, although diseases can also affect other parts of the plant, such as fruits. In this paper, we present a solution for estimating the severity of four mango fruit diseases, namely alternaria, anthracnose, aspergillus rot and stem rot. This solution is based on ResNet50 CNN and uses a dataset automatically labeled by a proposed algorithm based on two segmentation algorithms such as image color space segmentation and image thresholding. The solution has achieved an accuracy and a F1_score of 97.82% and 97.79%, respectively, on test data. It is then deployed in a mobile application with a diagnostic solution we previously proposed. This mobile application will help mango growers, particularly those in Sahelian countries like Senegal, to manage their mango diseases earlier.
A Real-Time Common Rust Maize Leaf Disease Severity Identifications and Pesticide Dose Recommendation Using Deep Neural Network
Authors: Megersa Zemzem Mohammed , Adege Abebe Belay , Rashid Faizur 
Published: May 2024

Abstract

Maize is one of the most widely grown crops in Ethiopia, although common rust maize disease (CRMD) is becoming a serious problem. Conventional CRMD detection and treatment methods are time-consuming, expensive and ineffective. To solve these problems, we propose a real-time deep learning model that provides disease detection and pesticide dosing recommendations. In the model development process, we collect 8000 maize-leaf images experimentally with permission obtained from Haramaya University and apply image pre-processing such as image equalization, augmentation, noise removal, and image enhancement to improve the performance of the proposed model. We then jointly apply batch normalization, dropout, and early stopping during training the proposed algorithm to reduce the overfitting problem. Next, we generate an optimal model that recognizes CRMD and classifies it accurately based on its severity levels. To evaluate the proposed techniques, we compare Resnet50 with other state-of-the-art algorithms, such as VGG19, VGG16, and AlexNet algorithms with similar parameters. The performance of ResNet50 is more than 2% better than that of other algorithms in terms of accuracy. The proposed technique provides promising results for the classification of CRMD and pesticide dosage recommendations based on the severity of the disease type. This study also demonstrates the potential of Resnet50 models for improving maize disease management.