bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigating Fundamental Interactions between Pectin and Cellulose Nanocrystals: A Molecular Dynamics Simulation
Authors: Wu Xiawa , Prasad Anamika 
Published: December 2024

Abstract

Pectin and cellulose nanocrystals are the main biopolymers in the plant's prime cell walls. Despite extensive studies on the structure of prime cell walls of plants, limited information is known about the interaction between pectin and cellulose due to previous models placing pectin as a matrix and cellulose nanocrystals as a separate reinforcement component. However, recent developments in prime cell wall structure have shifted, and pectin is considered a part of the reinforcement structure. This work aims to provide fundamental information on the interaction between pectin and cellulose nanocrystals using molecular dynamic simulations. Interphase models consisting of two cellulose nanocrystals and a homogalacturonan pectin molecule are created to simulate the interfacial structure, including binding energy and hydrogen bonds. Friction and adhesion responses are predicted by moving one cellulose nanocrystal against the other. The results show that a pectin molecule increases the friction at the interphase by 14 and 8 times between CNC (200) and (110) surfaces, respectively, which is correlated to the significantly increased binding energies and interfacial hydrogen bonds, regardless of pectin's charge density. On the other hand, adhesion rises by 1.1 times but reduces to 1/5 with a pectin molecule between the CNC (110) and (200) surfaces, respectively, which is attributed to disrupted π-π interaction. The simulation results reveal the atomistic level interaction between pectin and cellulose nanocrystals, which is essential for designing nanocomposites that mimic the natural biocomposites of the plant's primary cell walls.
An online self-management program for spinal cord injury: a pilot randomised controlled trial of the SCI&amp;U peer health coaching intervention
Authors: Jaglal Susan B , Allin Sonya J. , Craven B. Catherine , Guilcher Sara J.T. , Linassi A. Gary , McBride Christopher B. , Moineddin Rahim , Mortenson W. Ben , Munce Sarah , Salbach Nancy M. , Shepherd John D. , Sweet Shane N. , Thorson Teri , Tomasone Jennifer R. 
Published: December 2024

Abstract

Background: The spinal cord injury and you (SCI&U) intervention aims to improve self-management skills for persons living with SCI using a web-based, peer health-coaching model. This study assessed the feasibility of conducting a future definitive trial of SCI&U, specifically the feasibility of recruitment and retention, usability and quality of the program, and estimates of effect sizes for a variety of self-management outcomes.
Methods: A two-group, randomised, controlled, pilot trial with prospective recruitment, concealed group allocation, blinded outcome evaluation, and waitlist control was conducted in Canada. We aimed to recruit 60 participants who were 18 years and older living in the community at least six months post-injury, were able to speak and read English, and had a primary care physician. The intervention included online client-coach videoconferencing sessions, goal setting, action planning, and a sortable resource library. Data were collected at baseline, 2, 6 and 12 months post-randomisation. SCI&U was offered to the waitlist group at 12 months. Primary short-term self-management outcome was Skill and Technique Acquisition (STA), a subscale of the Health Education Impact Questionnaire. Primary long-term outcome was cumulative days rehospitalised.
Results: Of 65 eligible individuals, 34 were randomised to waitlist control and 31 to intervention. Mean time since injury was 25.6 years for intervention and 20.2 years for control. Outcome data were gathered for 86% of participants at 6 months and 89% at 12 months. The usability and quality of the program were highly rated. The difference in STA between intervention and control was 0.56 (95% CI -0.41, 1.52) at 6 months and 0.72 (95% CI -0.28, 1.72) at 12 months. Other subscales also had large effect sizes: Self-monitoring and insight 1.51 (95% CI 0.39, 2.69); and Emotional distress -1.40 (95% CI -3.04, 0.23). In the 12 months following recruitment, 5 intervention and 4 control participants spent median 11 (3-19) and 24 (5-95) nights in hospital, respectively.
Conclusions:The trial methodology and procedures were feasible; the SCI&U intervention was acceptable to participants. The program positively impacted an individual’s ability to self-manage. Further research is needed to confirm these findings and evaluate the program on those with recently acquired SCI.
Trial registration: ClinicalTrials.gov, NCT04474171, retrospectively registered 07/13/2020; https://clinicaltrials.gov/study/NCT04474171#study-record-dates
Geometry-encoded molecular dynamics enables deep learning insights into P450 regiospecificity control
Authors: POMPON Denis , GARCIA-ALLES Luis F. , URBAN Philippe 
Published: December 2024

Abstract

Cytochrome P450 1A2, as many isoenzymes, can generate multiple metabolites from a single substrate. A loose coupling between substrate binding and oxygen activation makes possible substrate reorientations at the active site prior to catalysis. In the present work, caffeine oxidation to alternative bioactive compounds was used to decipher this pluripotency. A model involving two interacting subsites capable of sequentially accommodating one or two caffeine molecules was considered. Molecular dynamics was used to characterize subsite interactions and feed a dedicated geometric encoding of trajectories that was coupled to dimensional reductions and differential machine learning. The two subsites differentially control caffeine orientations and can exchange substrate through a phenylalanine gated mechanism. This exchange can be locked by the presence of a second bound molecule. Complementary roles of subsites in progressively determining the caffeine orientation during its approach to active oxygen were examined. Interestingly, substrate face flipping becomes impaired upon entry into the rather flat active site. This makes the mechanisms that define the orientation of caffeine relative to active oxygen dependent on the substrate face oriented toward heme. Globally, this evidenced that P450 1A2 regioselectivity results from local determinants combined with subsite interactions and caffeine face preselection at a longer distance
The neutrophil to lymphocyte ratio as a predictor of major adverse cardiovascular events in patients with non-small cell lung cancer
Authors: Zheng Zhimin , Lin Xueqin , Pan Yuxiong 
Published: December 2024

Abstract

Background: Cancer patients are more susceptible to mortality from cardiovascular disease. This study sought to determine whether the neutrophil to lymphocyte ratio (NLR) could serve as a predictor for major adverse cardiovascular events (MACEs) in patients with non-small cell lung cancer (NSCLC) after surgery.
Methods: A retrospective analysis was conducted on clinicopathological data from 204 NSCLC patients who underwent radical surgery at Longyan First Hospital between January 2019 and December 2021. Follow-up for postoperative MACEs was performed until June 2024. The optimal NLR cut-off point was identified using the receiver operating characteristic (ROC) curve. Survival analysis, including Kaplan-Meier and Cox regression methods, was applied to assess the correlation between NLR and patient prognosis.
Results: The critical NLR value was determined to be 2.86. Univariate Cox regression analysis indicated that gender, tumor size, NLR, platelet to lymphocyte ratio (PLR), and advanced lung cancer inflammation index (ALI) were associated with MACEs (P-values: 0.011, <0.001, <0.001, 0.027, 0.001). Furthermore, multivariate Cox regression analysis demonstrated that NLR (HR: 1.104, 95% CI: 1.032-1.182, P= 0.004), tumor diameter (HR: 1.922, 95% CI: 1.160-3.185, P= 0.011), and gender (HR: 1.873, 95% CI: 1.037-3.378, P= 0.037) were independent predictors of MACEs.
Conclusions: The elevation of NLR is significantly associated with an increased risk of MACEs in patients with non-small cell lung cancer, making it a valuable tool for risk stratification.
Bioinformatics analyses and verification the promoting cancer role of RRM2 in cervical cancer
Authors: Abuduhailili Xieyidai , Lu Ruijiao , Li Yuxia , Feng Yangchun , Wang Senyu 
Published: December 2024

Abstract

Background: Cervical cancer is one of the most common malignant tumours in women, and is the seventh highest among cancers, cervical cancer main caused by HPV infection; Xinjiang is a high incidence of cervical cancer. Immunotherapy is a new type of tumour therapy based on immune checkpoints, which has made a big breakthrough in the treatment of cancer. Ribonucleotide reductase subunit M2 (RRM2) is expressed at increased levels in cervical cancer and is associated with apoptosis and proliferation of cancer cells. In this study we explore the mechanism of RRM2 regulates the high expression of PD-L1 in cervical cancer through ERK signaling pathway by Bioinformatics analyses and experiments, and also investigate the role of RRM2 in cervical cancer .
Methods: Bioinformatics analyses and experiments were carried out to revealed the promoting cancer role of RRM2 in cervical cancer and verify that RRM2 enhanced PD-L1 expression through activation of the ERK signaling pathway.
Results: RRM2 plays an crucial role in the occurrence and progression of cervical cancer and enhanced the expression of PD-L1 in cancer cells via activating the ERK signaling pathway.
Research on Electromagnetic Tomography Method for Imaging Reinforcement Structures in Concrete Utility Poles Based on an Improved VGG16 Deep Learning Network
Authors: Weng Jia , Wang Peifeng , Qiu Canshu , Wu Chaohang , Wang Juan 
Published: December 2024

Abstract

Concrete utility poles are extensively utilized in the load-bearing structures of low-voltage distribution lines, where the quality of the internal reinforcement directly impacts their reliability and supports the stable operation of the distribution network. Non-destructive testing of these poles aids maintenance personnel in understanding the internal structure of the reinforcements, evaluating the performance of the poles, and ensuring their reliable operation. Addressing this issue, this paper introduces a method for imaging the reinforcement structure of concrete utility poles using electromagnetic tomography. This method involves evenly dis-tributing 32 threaded coils on the surface of the pole, employing adjacent excitation methods to stimulate the coils and measure their voltage. The measurement data from the poles are inputted into an enhanced VGG16 neural network, trained with finite element data, to reconstruct the reinforcement structure. The effectiveness of this method was confirmed through simulation experiments, which demonstrated its ability to accurately image reinforcement structures with varying numbers of rebars, burial depths, diameters, and missing rebars, exhibiting strong generalization capabilities. While the generalizability of the model decreases when the rebar count is fixed during dataset construction, imaging performance improves for specific pole models. The reinforcement imaging method proposed in this paper enhances the efficiency of maintenance operations and offers new perspectives for the inspection of reinforcement structures in concrete utility poles.
The Effect of Selective Decontamination on Antimicrobial Resistance in Intensive Care Patients: A Systematic Review and Meta-analysis
Authors: Eerten Frederique van , Plate Joost , Groenwold Rolf , Schweitzer Valentijn , Kluytmans Jan , Hietbrink Falco 
Published: December 2024

Abstract

Background Selective Digestive Decontamination (SDD) and Selective Oropharyngeal Decontamination (SOD) are applied to prevent infections amongst Intensive Care Unit (ICU) patients and have proven to reduce mortality and infection rates. However, concerns about development of antimicrobial resistance persists, specifically after ICU discharge. The aim of this study was to assess the occurrence of antimicrobial resistance during ICU stay and after ICU discharge in patients who received SDD, or SOD compared to control.Methods A previous systematic review, which included studies on antimicrobial resistance after SDD or SOD from before 01-02-2012, was updated. All studies analyzing antimicrobial resistance during and after ICU stay, were included. Pooled odds ratios and 95% confidence intervals were calculated using the Mantel-Haenszel method with random effects. Analyses were done separately for SDD and SOD.Results Twenty-seven studies were included in the meta-analysis on the occurrence of antimicrobial resistance during ICU stay, yielding a protective association in patients receiving SDD; OR 0.73 (95%-CI 0.54;0.98, I2 75%), less resistance to fluoroquinolones in patients receiving SDD OR 0.29 (95%-CI 0.12;0.68, I2 30%) and less multi-resistant bacteria; OR 0.53 (95%-CI 0.33; 0.87, I2 0%), compared to control treatment. Four studies investigated antimicrobial resistance after ICU discharge of which two were eligible for pooling, which yielded no significant effect; OR 1.20 (95%-CI 0.23;6.36, I2 90%).Conclusion During ICU stay, SDD is associated with reduced antimicrobial resistance to specific antibiotics, in line with a previous review. More specifically combined with intravenous (IV) component, in settings with low prevalence of resistance and in a cluster design. This current review emphasizes the limited amount of data on the long-term effect of antimicrobial decontamination strategies to antimicrobial resistance. Understanding this long-term effect is essential when deciding whether to implement preventative antibiotics in specific subgroups. This could be done by means of a prospective long-term follow-up study.
Active learning algorithm for alleviating the user cold start problem of recommender systems
Authors: De Pessemier Toon , Willems Bruno , Martens Luc 
Published: December 2024

Abstract

A key challenge in recommender systems is how to profile new users. A popular solution for this problem is to use active learning strategies. These strategies request ratings for a small set of carefully selected items to reveal the preferences of new users. In this paper, we propose a new decision tree-based algorithm for selecting these items. Treating the recommender system as a black box, the ratings collected from interviewing new users are passed on to the recommender system with the intention of improving its performance. Extensive offline evaluation with two data sets and various recommender algorithms shows that our algorithm does indeed improve the performance of the underlying recommender algorithm if users are able to rate most of the items that are presented to them during the interview. However, online evaluation with 50 real users could not prove that our algorithm does indeed have a positive impact on the performance of the underlying recommender algorithm. This reveals the discrepancy between offline and online evaluations of active learning techniques applied in the context of recommender systems. This is due to the fact that real users are not always able to rate the item selected by the active learning algorithm and therefore cannot provide the requested information, in contrast to many machine learning scenarios were the labeling of all samples is possible. Hence, further research is required to provide more certainty regarding the impact of active learning strategies on recommender algorithms.
Predicting Lung Health with High-Performance Machine Learning: Insights from Upper Respiratory Microbiome Biomarkers
Authors: Yaqin Muhammad A , Singgih Euginia L , Utama Revata , Irmayanti Evita , Khanza Shafira M , Intan Novia S , Pramono Ajeng K , Puspitasari Iva , Rahardjo Sofyan B , Farhanah Nur , Handoyo Thomas , Kholis Fathur N , Hapsari Rebriarina , Pramudo Setyo G , Kandowangko Jenny W , Susetyo Rosreri 
Published: December 2024

Abstract

BACKGROUND The major importance of upper respiratory tract (URT) microbiome diversity to the overall aerodigestive tract made it an ideal hotspot to determine lung health. However, the current sampling methods pose a bottleneck for large scale lung examination, as they are either invasive such as bronchoalveolar lavage (BAL), or inconsistent like sputum. As COVID-19 pushes innovation for mass surveillance, the self-collected gargle sampling method gained popularity as it is non-invasive, convenient, and requires minimum sampling skill. Combined by the power of sequencing technology and machine learning (ML) algorithms, gargle specimen analysis could be the novel approach for lung health surveillance. Here, we carried out shotgun metagenomics study to compare microbiome diversity between sputum and gargle specimens from 3 subject’s lung health groups, namely healthy, acute, and chronic. We also discovered biomarkers driving microbiome differences in healthy-chronic subjects and used that insight to develop ML based predictive models.RESULTS We found that influence of specimen types on microbiome diversity is significantly inconsequential compared to that of subjects’ health. Our biomarker analysis revealed higher commensals abundance in healthy samples, as well as pathogens predominance in chronic subjects. By using this insight, our prediction models achieve an excellent discriminatory power to distinguish healthy subjects from chronic patients.CONCLUSION Findings in our study demonstrated feasibility of ML-based gargle analysis as an alternative lung health surveillance approach.
Tumour-derived secreted phosphoprotein 1/SPP1 via activation of microglia contributes to the formation of the breast cancer brain metastatic niche
Authors: Wojnicki Kamil , Poleszak Katarzyna , Kochalska-Les Agata , Roura Adria-Jaume , Matyja Ewa , Czernicki Tomasz , Grajkowska Wiesława , Waśniewski Kacper , Vymolova Barbora , Kaminska Bozena 
Published: December 2024

Abstract

Brain metastases (BrMets) occur in 20%-40% of patients with breast cancer and contribute significantly to morbidity and/or mortality. BrMets are more common in certain breast cancer subtypes, such as human epidermal growth factor receptor 2–positive breast cancer, which has a higher incidence of BrMets. The molecular mechanisms that drive and permit the progression of metastasis in the brain are poorly understood. Identifying components of the metastatic niches and propensities of primary tumors towards the brain microenvironment are essential to improve our understanding of BrMet development, patient management and outcomes. SPP1, a secreted phosphoglycoprotein 1, is a potent activator of microglia (brain resident myeloid cells) in malignant gliomas. SPP1 is elevated in breast cancer and breast cancer brain metastasis. Exploration of public bulk and scRNAseq datasets shows high SPP1 overexpression in breast malignant cells, as well as in the immune cells in BrMets. We found that breast cancer cells with high expression of SPP1 strongly activate microglia in co-cultures, which in turn increases cancer cell invasion. Blocking SPP1-mediated cancer-microglia communication with the 7aaRGD interfering peptide or shRNA mediated knockdown of SPP1 in cancer cells, abolished microglia-dependent cancer cell invasion. Notably, we found that an antibiotic minocycline efficiently reduces the expression of SPP1 in several breast cancer cell lines, and decreases both the basal and microglia-induced invasion of breast cancer cells. The results highlight the important role of breast cancer-derived SPP1 in shaping the permissive microenvironment of BrMet, and indicate a potential of the 7aaRGD peptide or minocycline to be new therapeutics in breast cancer brain metastasis treatment.
Global Warming Exacerbates the Risk of Habitat Loss for Regional Mangrove Species
Authors: Liao Jian , Li Gaocong , Zhang Shuiyuan , Yang Yuanfeng , Li Yiyang , Dong Zhongdian , Guo Yusong , Wang Zhongduo 
Published: December 2024

Abstract

Mangroves, as a salt-tolerant evergreen broad-leaved vegetation ecosystem, are widely distributed along the coastlines of tropical and subtropical regions. In the field of ecology, scholars generally agree that climatic drivers, particularly temperature and precipitation patterns, play a crucial role in regulating the global distribution, structure, and functions of mangroves. However, significant gaps and challenges remain in the research quantifying the direct relationship between climate and mangroves. This study focused on two dominant mangrove species in the northern margin of the South China Sea: Kandelia obovata and Avicennia Marina. By compiling reported data, utilizing database information, and integrating our field observations, we employed species distribution models to simulate the distribution areas of these two species and their habitat changes under global warming scenarios. Our results indicate that bio18 serves as the primary climatic factor shaping their distribution patterns. Specifically, K. obovata is primarily distributed in the Northern Hemisphere, while A. Marina exhibits a much broader distribution range, encompassing over 40 times the area of K. obovata. The niche overlap between these two species is relatively low, and global warming is further promoting the separation of their niches. Notably, the continued warming of the climate in the future is not expected to pose a significant threat to K. obovata. However, it significantly increases the risk of habitat loss for A. Marina. This study underscores the urgent need to implement conservation measures for mangrove ecosystems, with particular priority given to those species that are currently experiencing or are vulnerable to habitat loss.
Local Anesthesia with Monitored Anesthesia Care for Cephalomedullary Nailing of Proximal Femur Fractures: A Minimally Invasive Approach for High-Risk Surgical Candidates
Authors: Hajializade Mikaiel 
Published: December 2024

Abstract

Background
Proximal femur fractures are common orthopedic injuries, particularly in the elderly population, and present significant challenges due to high comorbidity and elevated risk of anesthesia. Traditional management often involves general or spinal anesthesia, which carries a considerable risk of morbidity and mortality in these high-risk patients. This study aimed to evaluate the safety and efficacy of local anesthesia combined with monitored anesthesia care (MAC) as an alternative to general anesthesia in elderly patients with intertrochanteric fractures.
Methods
In this retrospective study, we included patients aged ≥ 65 years with displaced intertrochanteric fractures who underwent cephalomedullary nailing under local anesthetic infiltration with MAC. Data on demographics, safety outcomes (complications and mortality), and efficacy measures (blood loss, surgical time, anesthesia induction-to-incision time, and length of stay) were collected.
Results
A total of 35 patients were included, with a mean age of 76.6 years. Major complications occurred in 6 patients (17.1%), with a 90-day mortality rate of 2.8%. The mean blood loss was 108 cc, surgical time averaged 33.6 minutes, anesthesia induction-to-incision time was 6.4 minutes, and the mean length of hospital stay was 2 days.
Conclusion
Local anesthesia combined with MAC is a safe alternative to general or spinal anesthesia for managing high-risk patients with proximal femur fractures. This approach reduces morbidity and mortality rates while effectively decreasing surgical time and length of hospital stay.