bluuebunny/crossref_metadata_2025 huggingface dataset:
Models of fibrolamellar carcinomas, tools for evaluation of a new era of treatments
Authors: Song Jinjia , Lu Mengqi , He Zhiying , Zhang Wencheng
Published: November 2024

Fibrolamellar carcinoma (FLC) is a rare but fatal cancer that occurs primarily in young people. There are currently no known effective treatments, although several promising treatments appear to be in development. Genetic studies have confirmed that almost all FLC tumors have a fusion protein marker (DNAJB1-PRKACA) encoded by a fusion gene (DNAJB1-PRKACA); It is currently accepted as a diagnostic criterion for FLCs. Several research teams have established patient-derived xenograft (PDX) FLC models using immunocompromised animals as hosts and patient tissue samples (tumors or ascites) as primary sources for PDX-derived organoids. These FLC organoids are composed of FLC epithelia, endothelial progenitor cells, and stellate cells. CRISPR/Cas9 was used as a gene editing technique to modify mature hepatocytes to obtain ex vivo FLC-like cells expressing the fusion gene and/or other mutated genes associated with FLCs. Although these models simulate some but not all FLC features. Drug screening using these models has not proven effective in identifying clinically useful treatments. Genetic studies comparing FLCs to normal maturing endodermal cell lineages have shown that FLCs share genetic signatures not with hepatocytes, but with subpopulations of biliary tree stem cells (BTSCs), hepato/pancreatic stem/progenitor cells that consistently reside in peribiliary glands (PBGs) located in the biliary tree and are sources of stem cells for the formation and postnatal regeneration of the liver and pancreas. Therefore, it is expected that models of BTSCs, instead of hepatocytes may prove more useful. In this review, we summarize the status of the various FLC models and their features, applications, and limitations. They provide opportunities to understand the cause and characteristics of this deadly disease and are models from which effective treatments can be identified.
Optimizing cancer treatment: the synergistic potential of CAR-T cell therapy and CRISPR/Cas9
Authors: Amiri Maryam , Moaveni Amir Kian , Majidi Zolbin Masoumeh , Shademan Behrouz , Nourazarian Alireza
Published: November 2024

Optimizing cancer treatment has become a pivotal goal in modern oncology, with advancements in immunotherapy and genetic engineering offering promising avenues. CAR-T cell therapy, a revolutionary approach that harnesses the body’s own immune cells to target and destroy cancer cells, has shown remarkable success, particularly in treating acute lymphoblastic leukemia (ALL), and in treating other hematologic malignancies. While CAR-T cell therapy has shown promise, challenges such as high cost and manufacturing complexity remain. However, its efficacy in solid tumors remains limited. The integration of CRISPR/Cas9 technology, a powerful and precise genome-editing tool, also raises safety concerns regarding unintended edits and off-target effects, offers a synergistic potential to overcome these limitations. CRISPR/Cas9 can enhance CAR-T cell therapy by improving the specificity and persistence of CAR-T cells, reducing off-target effects, and engineering resistance to tumor-induced immunosuppression. This combination can also facilitate the knockout of immune checkpoint inhibitors, boosting the anti-tumor activity of CAR-T cells. Recent studies have demonstrated that CRISPR/Cas9-edited CAR-T cells can target previously untreatable cancer types, offering new hope for patients with refractory cancers. This synergistic approach not only enhances the efficacy of cancer treatment but also paves the way for personalized therapies tailored to individual genetic profiles. This review highlights the ongoing research efforts to refine this approach and explores its potential to revolutionize cancer treatment across a broader range of malignancies. As research progresses, the integration of CAR-T cell therapy and CRISPR/Cas9 holds the promise of transforming cancer treatment, making it more effective and accessible. This review explores the current advancements, challenges, and future prospects of this innovative therapeutic strategy.
Branched-chain amino acid catabolism promotes M2 macrophage polarization
Authors: Lu Manxi , Luo Da , Zhang Zixuan , Ouyang Feng , Shi Yihong , Hu Changyong , Su Hang , Li Yining , Zhang Jiayi , Gui Qian , Yang Tian-Shu
Published: November 2024

Introduction

During an immune response, macrophages undergo systematic metabolic rewiring tailored to support their functions. Branched-chain amino acid (BCAA) metabolism has been reported to modulate macrophage function; however, its role in macrophage alternative activation remain unclear. We aimed to investigate the role of BCAA metabolism in macrophage alternative activation.

Method

The metabolomics of BMDM-derived M0 and M2 macrophages were analyzed using LC-MS. BCAAs were supplemented and genes involved in BCAA catabolism were inhibited during M2 macrophage polarization. The expression of M2 marker genes was assessed through RT-qPCR, immunofluorescence, and flow cytometry.

Results and discussion

Metabolomic analysis identified increased BCAA metabolism as one of the most significantly rewired pathways upon alternative activation. M2 macrophages had significantly lower BCAA levels compared to controls. BCAA supplementation promoted M2 macrophage polarization both in vitro and in vivo and increased oxidative phosphorylation in M2 macrophages. Blocking BCAA entry into mitochondria by knockdown of SLC25A44 inhibited M2 macrophage polarization. Furthermore, M2 macrophages polarization was suppressed by knockdown of Branched-chain amino-acid transaminase 2 (BCAT2) and branched chain keto acid dehydrogenase E1 subunit alpha (BCKDHA), both of which are key enzymes involved in BCAA oxidation. Overall, our findings suggest that BCAA catabolism plays an important role in polarization toward M2 macrophages.
Mesenchymal stem cell application in pulmonary disease treatment with emphasis on their interaction with lung-resident immune cells
Authors: Hazrati Ali , Mirarefin Seyed Mohamad Javad , Malekpour Kosar , Rahimi Arezou , Khosrojerdi Arezou , Rasouli Ashkan , Akrami Susan , Soudi Sara
Published: November 2024

Due to the vital importance of the lungs, lung-related diseases and their control are very important. Severe inflammatory responses mediated by immune cells were among the leading causes of lung tissue pathology and damage during the COVID-19 pandemic. In addition, uncontrolled immune cell responses can lead to lung tissue damage in other infectious and non-infectious diseases. It is essential to control immune responses in a way that leads to homeostasis. Immunosuppressive drugs only suppress inflammatory responses and do not affect the homeostasis of reactions. The therapeutic application of mesenchymal stem cells (MSCs), in addition to restoring immune homeostasis, can promote the regeneration of lung tissue through the production of growth factors and differentiation into lung-related cells. However, the communication between MSCs and immune cells after treatment of pulmonary diseases is essential, and investigating this can help develop a clinical perspective. Different studies in the clinical phase showed that MSCs can reverse fibrosis, increase regeneration, promote airway remodeling, and reduce damage to lung tissue. The proliferation and differentiation potential of MSCs is one of the mechanisms of their therapeutic effects. Furthermore, they can secrete exosomes that affect the function of lung cells and immune cells and change their function. Another important mechanism is that MSCs reduce harmful inflammatory responses through communication with innate and adaptive immune cells, which leads to a shift of the immune system toward regulatory and hemostatic responses.
Case report: Successful remission with upadacitinib in a young patient with anti-TNF-refractory intestinal Behçet’s disease
Authors: Sha Sumei , Xu Bin , Wang Kairuo , Qiao Chenyang , Shi Haitao , Jiang Jiong , Quan Xiaojing , Liu Xin
Published: November 2024

Background

The limited therapeutic options and inconsistent treatment efficacy of Intestinal Behçet’s disease complicate its management, with the absence of standardized guidelines further exacerbating the challenges faced by clinicians.

Case Presentation

In this case report, we present a patient with refractory intestinal Behçet’s disease who experienced treatment failure with prior biologic agents. This case sheds light on managing this complex scenario with Janus kinase (JAK) inhibitors, the patient achieved mucosal healing after switching to Upadacitinib.

Conclusion

This case underscores the potential of Upadacitinib as an effective alternative for managing difficult cases of intestinal Behçet’s disease.
Comprehensive comparative analysis of reconstructed sea level datasets in the China Seas: insights from tide gauge and satellite altimetry
Authors: Zhang Shuwei , Li Yanxiao , Feng Jianlong , Jin Yiyang , Zhang Jing , Zhao Liang
Published: November 2024

At present, there are many reconstructed datasets at the global scale. To test the applicability of these datasets in the China seas, the study comprehensively analyzes the reliability and accuracy of reconstructed sea level datasets in capturing nuanced temporal patterns of sea level changes in the China Seas. This study applied analysis methods or indicators such as time series, Taylor plots, correlation coefficients, growth rates, and standard deviations. Ocean Data Assimilations (ODAs) outperform Tide Gauge Reconstructions (TGRs) in terms of correlation with measured data in the nearshore, while TGRs exhibit superior capability in capturing oceanic sea level variability. Although the ODAs and TGRs both suffer from the underestimation of sea level variability in China as well as in neighboring seas, the TGRs perform better than the former. ODAs show inconsistency in reflecting the rate of sea level rise, but they, particularly the China Ocean Reanalysis (CORA), demonstrate a better correlation with satellite altimetry datasets. Meanwhile, both of them can reflect the Pacific Decadal Oscillation (PDO) well. TGRs, relying on oceanic tide gauge stations, suffer from poor correlation with tide gauge stations due to limited coverage. Reconstruction discrepancies are attributed to methodological differences and data assimilation techniques. Future studies should explore alternative variables like sea surface temperature and so on to enhance sea-level reconstruction, especially in regions with sparse tide gauge coverage.
The research on the applicability of different typhoon wind fields in the simulation of typhoon waves in China’s coastal waters
Authors: Chen Xiangyu , Ni Yunlin , Shen Yuan , Ying Yue , Wang Jinbao
Published: November 2024

Typhoon waves possess significant destructive potential, and their numerical simulation relies on accurate sea surface wind fields. An evaluation of different combinations of the radial air pressure distribution coefficient B and the radius of maximum wind speed (Rmax) in the Holland wind field (HWF) model was conducted to determine the optimal configuration. The HWF and the ERA5 wind field (EWF) were used as input wind fields to drive the typhoon wave model for China’s coastal waters. Validation results indicated that neither wind field accurately reflected real conditions; therefore, a hybrid wind field (HBWF) was created by combining HWF and EWF using weighting coefficients that vary with the radius of wind speed to enhance accuracy. Simulation results showed that the HBWF improved the accuracy of significant wave heights (SWHs), with a mean relative error of 25.29%, compared to 32.48% for HWF and 27.94% for EWF. Additionally, HBWF also demonstrated the best performance in terms of root mean square error (RMSE) and consistency index. Overall, the HBWF enhances the simulation accuracy of typhoon waves in China's coastal waters.
Analysis of factors influencing bronchiectasis patients with active pulmonary tuberculosis and development of a nomogram prediction model
Authors: Yang Yitian , Du Lianfang , Ye Weilong , Liao Weifeng , Zheng Zhenzhen , Lin Xiaoxi , Chen Feiju , Pan Jingjing , Chen Bainian , Chen Riken , Yao Weimin
Published: November 2024

Background

To identify the risk factors for bronchiectasis patients with active pulmonary tuberculosis (APTB) and to develop a predictive nomogram model for estimating the risk of APTB in bronchiectasis patients.

Methods

A retrospective cohort study was conducted on 16,750 bronchiectasis patients hospitalized at the Affiliated Hospital of Guangdong Medical University and the Second Affiliated Hospital of Guangdong Medical University between January 2019 and December 2023. The 390 patients with APTB were classified as the case group, while 818 patients were randomly sampled by computer at a 1:20 ratio from the 16,360 patients with other infections to serve as the control group. Relevant indicators potentially leading to APTB in bronchiectasis patients were collected. Patients were categorized into APTB and inactive pulmonary tuberculosis (IPTB) groups based on the presence of tuberculosis. The general characteristics of both groups were compared. Variables were screened using the least absolute shrinkage and selection operator (LASSO) analysis, followed by multivariate logistic regression analysis. A nomogram model was established based on the analysis results. The model’s predictive performance was evaluated using calibration curves, C-index, and ROC curves, and internal validation was performed using the bootstrap method.

Results

LASSO analysis identified 28 potential risk factors. Multivariate analysis showed that age, gender, TC, ALB, MCV, FIB, PDW, LYM, hemoptysis, and hypertension are independent risk factors for bronchiectasis patients with APTB (p < 0.05). The nomogram demonstrated strong calibration and discrimination, with a C-index of 0.745 (95% CI: 0.715–0.775) and an AUC of 0.744 for the ROC curve. Internal validation using the bootstrap method produced a C-index of 0.738, further confirming the model’s robustness.

Conclusion

The nomogram model, developed using common clinical serological characteristics, holds significant clinical value for assessing the risk of APTB in bronchiectasis patients.
Multiscale attention-over-attention network for retinal disease recognition in OCT radiology images
Authors: Alenezi Abdulmajeed M. , Aloqalaa Daniyah A. , Singh Sushil Kumar , Alrabiah Raqinah , Habib Shabana , Islam Muhammad , Daradkeh Yousef Ibrahim
Published: November 2024

Retinal disease recognition using Optical Coherence Tomography (OCT) images plays a pivotal role in the early diagnosis and treatment of conditions. However, the previous attempts relied on extracting single-scale features often refined by stacked layered attentions. This paper presents a novel deep learning-based Multiscale Feature Enhancement via a Dual Attention Network specifically designed for retinal disease recognition in OCT images. Our approach leverages the EfficientNetB7 backbone to extract multiscale features from OCT images, ensuring a comprehensive representation of global and local retinal structures. To further refine feature extraction, we propose a Pyramidal Attention mechanism that integrates Multi-Head Self-Attention (MHSA) with Dense Atrous Spatial Pyramid Pooling (DASPP), effectively capturing long-range dependencies and contextual information at multiple scales. Additionally, Efficient Channel Attention (ECA) and Spatial Refinement modules are introduced to enhance channel-wise and spatial feature representations, enabling precise localization of retinal abnormalities. A comprehensive ablation study confirms the progressive impact of integrated blocks and attention mechanisms that enhance overall performance. Our findings underscore the potential of advanced attention mechanisms and multiscale processing, highlighting the effectiveness of the network. Extensive experiments on two benchmark datasets demonstrate the superiority of the proposed network over existing state-of-the-art methods.
Effect of nanoemulsion loaded with macela (Achyrocline satureioides) on the ultrastructure of Staphylococcus aureus and the modulating activity of antibiotics
Authors: Ribeiro Rayanne , Rentes Bruna Rodrigues , Honorato Luciana Aparecida , Kuhnen Shirley
Published: November 2024

Nanoformulations with herbal actives for treating bovine mastitis present an alternative for controlling bacterial infections in the emerging scenario of antimicrobial resistance. In this study, we investigated macela (Achyrocline satureioides) nanoemulsion (NE-ML), a formulation developed for the treatment of bovine mastitis (registered under Brazilian patent application BR 10 2021 008630 0), in the context of its bactericidal mechanism(s) of action and potential synergism with commercial antimicrobials. The effect of NE-ML on the integrity and cell permeability of Staphylococcus aureus was evaluated by measuring the electrical conductivity of bacterial suspensions exposed to different concentrations of NE-ML and by assessing the release of cellular constituents. Damage to bacterial ultrastructures was analyzed by transmission electron micrographs. The synergism of NE-ML with beta-lactam antibiotics and aminoglycosides was evaluated by the checkerboard test method against S. aureus (n = 6). The relative electrical conductivity of the bacterial solution gradually increased over time, reaching high values after exposure to 1xMIC (52.3%) and 2xMIC (75.34%) of NE-ML. Total proteins were detected in the bacterial suspensions exposed to NE-ML, increasing in concentration over exposure time (p < 0.05). Through bacterial micrographs, we observed that exposure to NE-ML (1xMIC) affected the integrity of the plasma membrane with invaginations in the cytosolic region and alterations in the cell wall. The increase in NE-ML concentration resulted in greater damage to the ultrastructure of S. aureus with changes in bacterial cell division patterns. When NE-ML was combined with the beta-lactam antimicrobials, the interaction was indifferent, indicating no modulation of antimicrobial resistance. In contrast, when combined with the aminoglycoside, a synergistic interaction did occur. These general findings suggest that the bactericidal action of NE-ML begins in the plasma membrane, causing alterations in its permeability and integrity, and extends to the cell wall, cytoplasm, and cell division. Although synergy was restricted to the aminoglycoside by destabilizing the bacterial cell membrane, this suggests that NE-ML can induce the entry of other actives, potentially reducing their therapeutic doses. Understanding the mechanism of action of this new nanoformulation is certain to drive pharmacological advances, broaden the perspective of its in vivo use, and improve the treatment of bovine mastitis.
Multi-gate Weighted Fusion Network for neuronal morphology classification
Authors: Sun Chunli , Zhao Feng
Published: November 2024

Analyzing the types of neurons based on morphological characteristics is pivotal for understanding brain function and human development. Existing analysis approaches based on 2D view images fully use complementary information across images. However, these methods ignore the redundant information caused by similar images and the effects of different views on the analysis results during the fusion process. Considering these factors, this paper proposes a Multi-gate Weighted Fusion Network (MWFNet) to characterize neuronal morphology in a hierarchical manner. MWFNet mainly consists of a Gated View Enhancement Module (GVEM) and a Gated View Measurement Module (GVMM). GVEM enhances view-level descriptors and eliminates redundant information by mining the relationships among different views. GVMM calculates the weights of view images based on the salient activated regions to assess their influence on the analysis results. Furthermore, the enhanced view-level features are fused differentially according to the view weight to generate a more discriminative instance-level descriptor. In this way, the proposed MWFNet not only eliminates unnecessary features but also maps the representation differences of views into decision-making. This can improve the accuracy and robustness of MWFNet for the identification of neuron type. Experimental results show that our method achieves accuracies of 91.73 and 98.18% on classifying 10 types and five types of neurons, respectively, outperforming other state-of-the-art methods.
The impact of appendicular skeletal muscle index and trunk muscle index on stress urinary incontinence risk in female adults: a retrospective study
Authors: Wang Junwei , Zhang Cunming , Zhang Aiwei
Published: November 2024

Objective

This study sought to examine the effect of the appendicular skeletal muscle index (ASMI) and trunk muscle index (TMI) on the likelihood of stress urinary incontinence (SUI) among female adults.

Methods

This investigation utilized data from the National Health and Nutrition Examination Survey from 2001 to 2006 and 2011–2018. To evaluate the impact of ASMI and TMI on the likelihood of SUI, the study utilized restricted cubic splines (RCS) and weighted multivariable logistic regression models. Subgroup and interaction analyses were conducted to investigate how other covariates influenced their relationship.

Results

In total, 11,168 female adults participated in the analysis. Multivariable logistic regression analysis revealed that high TMI was associated with a decreased likelihood of SUI (OR = 0.34; 95% CI: 0.16–0.75; p = 0.013). ASMI was not correlated with the likelihood of SUI. RCS analysis demonstrated a linear correlation between TMI and SUI risk, showing a decreasing trend in SUI risk as TMI increases (p for overall <0.001, p for nonlinearity = 0.73).

Conclusion

Our study results showed that there was no association between ASMI and the risk of SUI, while a high TMI reduced the risk of SUI. This suggested that the ratio of muscle mass and BMI in different body regions has varying effects on SUI.
Deep learning radiomics based on contrast enhanced MRI for preoperatively predicting early recurrence in hepatocellular carcinoma after curative resection
Authors: Zhao Ying , Wang Sen , Wang Yue , Li Jun , Liu Jinghong , Liu Yuhui , Ji Haitong , Su Wenhan , Zhang Qinhe , Song Qingwei , Yao Yu , Liu Ailian
Published: November 2024

Purpose

To explore the role of deep learning (DL) and radiomics-based integrated approach based on contrast enhanced magnetic resonance imaging (CEMRI) for predicting early recurrence (ER) in hepatocellular carcinoma (HCC) patients after curative resection.

Methods

Total 165 HCC patients (ER, n = 96 vs. non-early recurrence (NER), n = 69) were retrospectively collected and divided into a training cohort (n = 132) and a validation cohort (n = 33). From pretreatment CEMR images, a total of 3111 radiomics features were extracted, and radiomics models were constructed using five machine learning classifiers (logistic regression, support vector machine, k-nearest neighbor, extreme gradient Boosting, and multilayer perceptron). DL models were established via three variations of ResNet architecture. The clinical-radiological (CR), radiomics combined with clinical-radiological (RCR), and deep learning combined with RCR (DLRCR) models were constructed. Model discrimination, calibration, and clinical utilities were evaluated by receiver operating characteristic curve, calibration curve, and decision curve analysis, respectively. The best-performing model was compared with the widely used staging systems and preoperative prognostic indexes.

Results

The RCR model (area under the curve (AUC): 0.841 and 0.811) and the optimal radiomics model (AUC: 0.839 and 0.804) achieved better performance than the CR model (AUC: 0.662 and 0.752) in the training and validation cohorts, respectively. The optimal DL model (AUC: 0.870 and 0.826) outperformed the radiomics model in the both cohorts. The DL, radiomics, and CR predictors (aspartate aminotransferase (AST) and tumor diameter) were combined to construct the DLRCR model. The DLRCR model presented the best performance over any model, yielding an AUC, an accuracy, a sensitivity, a specificity of 0.917, 0.886, 0.889, and 0.882 in the training cohort and of 0.844, 0.818, 0.800, and 0.846 in the validation cohort, respectively. The DLRCR model achieved better clinical utility compared to the clinical staging systems and prognostic indexes.

Conclusion

Both radiomics and DL models derived from CEMRI can predict HCC recurrence, and DL and radiomics-based integrated approach can provide a more effective tool for the precise prediction of ER for HCC patients undergoing resection.
The impact of skin-to-skin contact upon stress in preterm infants in a neonatal intensive care unit
Authors: Pavlyshyn Halyna , Sarapuk Iryna , Saturska Uliana
Published: November 2024

Introduction

Neonatal stress significantly affects the early adaptation, maturation and long-term development of preterm infants.

The objective of the study

To investigate the effect of skin-to-skin contact (SSC) on stress level in preterm infants.

Materials and methods

The research was a prospective study. Stress indicators (cortisol, melatonin) were measured before the SSC began (pre-intervention level) and after this intervention (post-intervention).

Results

The study included 150 preterm infants in the NICU with gestational age (GA) ≤36 weeks. Pre-intervention salivary cortisol level was higher in extremely and very preterm neonates compared to moderate and late preterm newborns (p = 0.028), in children with low Apgar scores (p = 0.041), in those who were on mechanical ventilation (p = 0.005), and suffered neonatal sepsis (p = 0.005). Pre-intervention melatonin level was lower in children with low Apgar scores (p = 0.032). Salivary cortisol levels were significantly decreased after SSC in preterm infants [pre-intervention: 0.294 (0.111; 0.854) μg/dL vs. post-intervention: 0.127 (0.070; 0.229) μg/dL, p < 0.001], and urinary melatonin levels were significantly increased after SSC [pre-intervention: 4.01 (2.48; 6.34) ng/mL vs. post-intervention: 5.48 (3.39; 9.17) ng/mL, p < 0.001]. A greater reduction in cortisol levels after skin-to-skin contact was revealed in infants with a lower gestational age (p = 0.022), in boys compared to girls (p = 0.012), in infants with respiratory distress syndrome (p = 0.048), in those who had mechanical ventilation compared to non-ventilated neonates (p = 0.008), and in infants with seizures (p = 0.036). The melatonin levels increased more intensively in infants with low Apgar scores (p = 0.002), and in those with late-onset sepsis (p = 0.006).

Conclusion

The reduction in cortisol levels and the increase in melatonin levels provided strong evidence that SSC ameliorated the NICU-related stress in preterm infants. We found higher indicators of stress and more dramatic responses to SSC in reducing indicators of stress in infants with lower GA than in infants with higher GA, indicating that SSC may be even more important for lower GA infants. The infants who need SSC the most should not be denied the care they need to reduce the stress they experience from being born too soon and continuing their gestational development in the stressful environment of the NICU.
Bacteria and fungi of the lung: allies or enemies?
Authors: Garaci Enrico , Pariano Marilena , Nunzi Emilia , Costantini Claudio , Bellet Marina Maria , Antognelli Cinzia , Russo Matteo Antonio , Romani Luigina
Published: November 2024

Moving from the earlier periods in which the lungs were believed to represent sterile environments, our knowledge on the lung microbiota has dramatically increased, from the first descriptions of the microbial communities inhabiting the healthy lungs and the definition of the ecological rules that regulate its composition, to the identification of the changes that occur in pathological conditions. Despite the limitations of lung as a microbiome reservoir due to the low microbial biomass and abundance, defining its microbial composition and function in the upper and lower airways may help understanding the impact on local homeostasis and its disruption in lung diseases. In particular, the understanding of the metabolic and immune significance of microbes, their presence or lack thereof, in health and disease states could be valuable in development of novel druggable targets in disease treatments. Next-generation sequencing has identified intricate inter-microbe association networks that comprise true mutualistic or antagonistic direct or indirect relationships in the respiratory tract. In this review, the tripartite interaction of bacteria, fungi and the mammalian host is addressed to provide an integrated view of the microbial-host cross-talk in lung health and diseases from an immune and metabolic perspective.
Pattern phase transition of spin particle lattice system
Authors: Wu Yue , Yan Jingnan , Xu Bowen , Zheng Yili , Chen Duxin
Published: November 2024

To better understand the pattern phase transition of both physical and biological systems, we investigate a two-dimensional spin particle lattice system using statistical mechanics methods together with XY model governed by Hamiltonian equations of motion. By tweaking the coupling strength and the intensity of the generalization field, we observe phase transitions among four patterns of spin particles, i.e., vortex, ferromagnet, worm and anti-ferromagnet. In addition, we analyze the effect of space boundaries on the formations of vortex and worm. Considering the inherent dynamics of individual particles, we revealed the forming mechanism of such phase transitions, which provides a new perspective for understanding the emergence of phase transition of spin particles systems.
Effects of chitosan on plant growth under stress conditions: similarities with plant growth promoting bacteria
Authors: Rojas-Pirela Maura , Carillo Petronia , Lárez-Velásquez Cristóbal , Romanazzi Gianfranco
Published: November 2024

The agricultural use of synthetic pesticides, fertilizers, and growth regulators may represent a serious public health and environmental problem worldwide. All this has prompted the exploration of alternative chemical compounds, leading to exploring the potential of chitosan and PGPB in agricultural systems as a potential biotechnological solution to establish novel agricultural production practices that not only result in fewer adverse impacts on health and the environment but also improve the resilience and growth of the plants. In this work, an analysis of the impact of plant growth-promoting bacteria (PGPB) and chitosan on plant growth and protection has been conducted, emphasizing the crucial bioactivities of the resistance of the plants to both biotic and abiotic stressors. These include inducing phytohormone production, mobilization of insoluble soil nutrients, biological nitrogen fixation, ethylene level regulation, controlling soil phytopathogens, etc. Moreover, some relevant aspects of chitin and chitosan are discussed, including their chemical structures, sources, and how their physical properties are related to beneficial effects on agricultural applications and mechanisms of action. The effects of PGPB and chitosan on photosynthesis, germination, root development, and protection against plant diseases have been compared, emphasizing the intriguing similarities and synergistic effects observed in some of these aspects. Although currently there are limited studies focused on the combined application of PGPB and chitosan, it would be important to consider the similarities highlighted in this work, and those that may emerge in future studies or through well-designed investigations, because these could permit advancing towards a greater knowledge of these systems and to obtain better formulations by combining these bioproducts, especially for use in the new contexts of sustainable agriculture. Thus, it seems feasible to augur a promising near future for these combinations, considering the wide range of possibilities offered by chitinous biomaterials for the development of innovative formulations, as well as allowing different application methods. Likewise, the studies related to the PGPB effects on plant growth appear to be expanding due to ongoing research to test on plants the impacts of microorganisms derived from different environments, whether known or recently discovered, making it a very exciting field of research.
Impacts of increased temperatures on floral rewards and pollinator interactions: a meta-analysis
Authors: Alquichire-Rojas Shirley , Escobedo Víctor M. , González-Teuber Marcia
Published: November 2024

Flowering plants produce pollinator rewards such as nectar and pollen, whose quantity and quality usually depend on the whole-plant state under specific environmental conditions. Increasing aridity and temperature linked to climate change may force plants to allocate fewer resources to these traits, potentially disrupting plant-pollinator interactions. In this study, for the first time, both quantitative review (vote-counting procedure) and meta-analytic approach were used to assess the implications of increased temperatures linked to global warming on floral rewards, including nectar (sugar concentration, content, and volume) and pollen (germination and viability), as well as on pollinator visits. Furthermore, we explored whether observed effects of warming are related either to temperature range, plant type (wild vs crop), or study approach (greenhouse vs field experiments). We also assessed the correlations between elevated temperatures and the characteristics that were affected by the temperature range. The results of the vote-counting technique showed that higher temperatures led to a decrease in floral rewards but did not affect the number of pollinator visits. Concurrently, meta-analysis detected adverse effects of warming on pollen germination and viability. Warming effects depended on the plant type for pollen germination and viability, on study approach for nectar sugar concentration and pollen germination, and on temperature range for pollen germination and pollinator visits. Additionally, we found that pollen germination and pollinator visits significantly decreased as temperature range increased. Our results showed that global warming affects floral rewards in both wild and crop plants, providing insights into the effects of changing climatic conditions on plant-pollinator interactions and pollination services.
A newly identified photosystem II Subunit P gene TaPsbP4A-1 in Triticeae species negatively regulates wheat powdery mildew resistance
Authors: Xu Jun , Wang Mengfei , Ren Yueming , Luo Wanglong , Zhang Lu , Liu Shuangwei , Hu Ping
Published: November 2024

The photosystem II (PSII) Subunit P (PsbP) protein is a component of its oxygen-evolving complex, which can oxidize water to produce oxygen using light energy and is critical to the core components and stability of PSII. Using the whole-genome information, the PsbP genes of 10 plant species were comprehensively identified. The expression patterns of wheat PsbPs under Blumeria graminis f. sp. tritici (Bgt) infection were assessed using qRT-PCR, and the functions of TaPsbPs in wheat powdery mildew resistance were studied using barley stripe mosaic virus-induced gene silencing. In total, 122 PsbP genes were divided into 8 classes with similar gene structures. No tandem repeat events were identified in wheat PsbP, suggesting that the PsbP genes in common wheat were donated by its diploid progenitor species. The expression levels of TaPsbP2A-1, TaPsbP3A-1, TaPsbP4A-1, TaPsbP4A-2, and TaPsbP7A-2 were induced by Bgt. The silencing of TaPsbP4A-1 increased the resistance of common wheat ‘Bainong AK58’ to Bgt. This study provides valuable information for functional and evolutionary research on the PsbP gene family.
Emergy-based evaluation of production efficiency and sustainability of diversified multi-cropping systems in the Yangtze River Basin
Authors: Lei Xinhui , Liang Bing , Feng Liang , Zhao Xuyang , Pu Tian , Yu Changbing , Wang Shubin , Wei Yafeng , Ma Shumei , Wang Xiaochun , Yang Wenyu
Published: November 2024

Excessive agricultural investment brought about by increased multiple-cropping index may compromise environmental sustainability. There are few studies on the sustainability of diversified multi-cropping systems in the Yangtze River Basin (YRB). Therefore, this study selected five representative locations in the YRB. According to the local climate characteristics and food demand, diversified multi-cropping systems were designed, and the main local winter crops were selected as the previous crops of the corn–soybean strip compound cropping system, with the local traditional double-cropping model as the control (CK). The emergy evaluation method was introduced to quantitatively compare the efficiency and sustainability of diversified multi-cropping systems in the YRB. The results showed that by incorporating soybean by intercropping with corn, compared with the CK, the total energy input, annual energy output, and annual economic output increased by 15.80%, 9.78%, and 33.12% on average, respectively. The unit emergy value (UEV) and unit non-renewable value (UNV) increased by 6.03% and 5.98%, respectively; the emergy yield ratio (EYR) and environmental loading ratio (ELR) decreased by 0.91% and 0.44%, respectively; the emergy sustainability index (ESI) was the same. In the third mature crop selection, compared with that of corn, the ELR of soybean decreased by 14.32%, and the ESI increased by 18.55%. In addition, the choice of winter crops plays a vital role in the system’s efficiency and sustainability. Compared with those of other winter crops, the annual economic outputs of potato (upper reaches of the YRB), potato or forage rape (middle reaches of the YRB), and wheat (lower reaches of the YRB) increased by 51.02%, 32.27%, and 0.94%, respectively; their ESI increased by 71.21%, 47.72%, and 12.07%, respectively. Potato–corn/soybean or potato/corn/soybean (upper reaches of the YRB), forage rape–corn/soybean or potato/corn/soybean (middle reaches of the YRB), and wheat–corn/soybean (lower reaches of the YRB) were chosen to facilitate the coexistence of high economic benefits and environmental sustainability. Additionally, promoting mechanization and reducing labor input were essential to improve the efficiency and sustainability of multi-cropping systems. This study would provide a scientific basis and theoretical support for the development of efficient and sustainable multiple-cropping systems in the dryland of the YRB.
Using single-sample networks and genetic algorithms to identify radiation-responsive genes in rice affected by heavy ions of the galactic cosmic radiation with different LET values
Authors: Zhang Yan , Wang Wei , Zhang Meng , Zhang Binquan , Gao Shuai , Hao Meng , Zhou Dazhuang , Zhao Lei , Reitz Guenther , Sun Yeqing
Published: November 2024

Introduction

Heavy ions of the galactic cosmic radiation dominate the radiation risks and biological effects for plants under spaceflight conditions. However, the biological effects and sensitive genes caused by heavy ions with different linear energy transfer (LET) values have not been thoroughly studied.

Methods

To comprehensively analyze the biological effects of heavy ions with different LET values on rice under spaceflight conditions, we utilized the Shijian-10 recoverable satellite (SJ-10) to transport the dehydrated rice seeds on a 12.5-day mission in a 252 km low Earth orbit (LEO), and obtained rice plants hit by individual heavy ions with LET values ranging from 18 keV/μm to 213 keV/μm. The transcriptome and methylation sequencing were conducted on above plants, and a bioinformatics pipeline based on single-sample networks (SSNs) and genetic algorithms (GA) was developed to analyze the multi-omics expression profiles in this work. Note that SSNs can depict the gene interaction patterns within a single sample. The LET regression models were constructed from both gene expression and interaction pattern perspectives respectively, and the radiation response genes that played significant roles in the models were identified. We designed a gene selection algorithm based on GA to enhance the performance of LET regression models.

Results

The experimental results demonstrate that all our models exhibit excellent regression performance (R2 values close to 1), which indicates that both gene expressions and interaction patterns can reflect the molecular changes caused by heavy ions with different LET values. LET-related genes (genes exhibiting strong correlation with LET values) and radiation-responsive genes were identified, primarily involved in DNA damage and repair, oxidative stress, photosynthesis, nucleic acid metabolism, energy metabolism, amino acid/protein metabolism, and lipid metabolism, etc. DNA methylation plays a crucial role in responding to heavy ions stressors and regulates the aforementioned processes.

Discussion

To the best of our knowledge, this is the first study to report the multi-omics changes in plants after exposure to heavy ions with different LET values under spaceflight conditions.
Mothers of children with disabilities: exploring lived experiences, challenges, and divorce risk
Authors: Alsamiri Yasir A. , Alaghdaf Ayesha A. , Alsawalem Ibraheem M. , Allouash Basheer A. , Alfaidi Seham D.
Published: November 2024

This qualitative study explores the psychological challenges faced by divorced Saudi mothers who are raising children with disabilities. The study highlights the impact of having a child with a disability on marital stability and family issues, and the psychological challenges experienced by single mothers. Using semi-structured in-depth interviews, data were collected from five divorced mothers recruited from a private daycare center. Participants ranged in age from 34 to 53, each with one child with a disability, and an average divorce period of four years. The thematic analysis revealed that single/divorced Saudi mothers of children with disabilities experienced significant psychological strain characterized by fear, shock and attempts at religious acceptance to cope with their child’s condition. Additionally, these mothers reported facing substantial social challenges, including societal ridicule and limited remarriage prospects, highlighting the broader impact of having a child with a disability on their lives. The study underscores the need for tailored psychological support and interventions for families of children with disabilities, especially for mothers who are significantly impacted by the challenges associated with their child’s condition. Additionally, the study emphasizes the negative impact of societal attitudes towards disability, which can contribute to social problems and psychological distress for families. The study’s findings suggest the need for specialized clinics and support groups to help families cope with the unique challenges they face.
A scaffolding intervention to improve self-efficacy in source-based argumentative writing
Authors: Allagui Besma
Published: November 2024

This study examined the role of scaffolding as temporary support offered by an educator to help students complete a learning task that would be challenging to accomplish without this support. Although there is a great deal of research in (L2) second language writing on the effect of scaffolding on improving students’ writing outcome variables (e.g., organization, coherence, content, and overall writing performance), few studies have explored the contributions of scaffolding to learners’ emotions and psychological variables. Using a double pre-test post-test design, this quasi-experimental study investigated the effect of a scaffolded writing intervention on students’ self-efficacy beliefs (i.e., confidence in their ability) in source-based argumentative writing. We analyzed the students’ (N = 50) source-self-efficacy beliefs 3 weeks before the intervention, immediately before the intervention, and immediately after the intervention. At the end of the intervention, students’ performance was measured using a scoring rubric containing key criteria in source-based argumentative writing. A post-study semi-structured interview was conducted with participating students (N = 13) to further understand their experience with the scaffolding intervention. The analyses demonstrated that the intervention had a positive and significant impact on students’ self-efficacy beliefs of their abilities to organize ideas, summarize different sources, and revise their essays. There were no significant changes in the participants’ beliefs about skills related to deciding if the evidence from different sources is strong, finding weaknesses in the arguments presented in different sources, and writing a counterargument. Furthermore, correlational analysis using post-test self-efficacy overall score and students’ writing performance scores on four major aspects (idea development, organization, source use, and language use) revealed a positive relationship between self-efficacy and two aspects of writing (source use and organization). Students’ interview results further confirmed the effectiveness of the intervention in enhancing the participants’ self-efficacy beliefs and performance in source-based argumentative writing. These findings highlight the importance of scaffolding strategies targeting self-efficacy to improve confidence in source-based writing and hence writing performance.
Good stress or bad stress? An empirical study on the impact of time pressure on doctoral students’ innovative behavior
Authors: Zhang Xin , Zhao Zhixing , Sun Jie , Ren Jiajia
Published: November 2024

In recent years, with rapid societal advancement and profound transformations in knowledge production, doctoral students are increasingly facing significant time pressures. These pressures not only stem from an escalation in research tasks but also from urgent demands for innovative outputs. Grounded in Affective Events Theory, this study explores the dual impact of time pressure on the innovative behaviors of doctoral students in China. It specifically examines how challenge and hindrance time pressures affect doctoral students’ innovative behavior through the mediating role of research self-efficacy and the moderating role of supervisor support. This research employed SPSS 26.0 and Mplus 8.3 for statistical analysis, analyzing multi-time point data collected from 452 Chinese doctoral students between May and August 2023. The results reveal that challenge time pressure significantly positively impacts doctoral students’ innovative behavior, while hindrance time pressure has a significant negative impact. Furthermore, research self-efficacy partially mediates the relationship between both challenge and hindrance time pressures and innovative behavior. In this process, the moderating role of supervisor support is significant, enhancing the positive effects of challenge time pressure and mitigating the negative impacts of hindrance time pressure, highlighting the importance of supervisor support in optimizing the impact of time pressure and promoting doctoral students’ innovative behavior. These findings not only enrich the theoretical framework in the field of time pressure research but also provide practical guidance for universities and supervisors on how to support doctoral students in effectively managing time pressure and fostering their innovation.