bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of sedentary behaviour and long-term regular Tai Chi exercise on dynamic stability control during gait initiation in older women
Authors: Chen Yuxia , Jin Chunxia , Tang Hongyuan , Yu Jinglun , Wang Yuanxin , Chen Shaolun , Miao Wensheng , Zhang Shengnian , Wang Xiangdong
Published: May 2024

Background: Sedentary behaviour has been associated with an increased risk of falls among older adults. Although gait initiation (GI) is a promising tool used to assess fall risk, it has yet to be quantitatively evaluated for dynamic stability in sedentary populations. Tai Chi exercise is believed to be effective in preventing falls in older adults, but its effect on GI stability has not been quantified. This study aims to compare the stability of GI in sedentary older individuals versus those who are long-term Tai Chi exercisers by using a quantitative approach.

Methods: This study included 17 sedentary older women without exercise habits (age: 65.59 ± 3.66 years, average daily sitting time: 8.735 ± 1.847 h/day) and 19 older women who regularly engage in Tai Chi exercise (age: 65.58 ± 3.63 years, years of exercise: 9.84 ± 3.48 years). Every participant underwent five trials of self-paced GI walking tests. Eight cameras and four force plates were used to obtain kinematic and kinetic parameters. The trajectory of the centre of mass (CoM) and the position of the foot placement were recorded. The anterior–posterior (A-P) and medio–lateral (M-L) dynamic stability at the onset and end moments of the single-legged support was calculated using CoM and gait spatiotemporal parameters. The stepping dynamic stability and foot placement positions of both groups were compared.

Results: The Tai Chi group had greater stability in the M-L directions at the swing leg’s toe-off moment and in the M-L and A-P directions at the heel-strike moment, as well as significantly larger step length, step width and step speed during locomotion than sedentary older women. However, the stability in the A-P directions at the swing leg’s toe-off moment and the foot inclination angle was not statistically different between the two groups.

Conclusion: Long-term regular Tai Chi exercise can enhance the dynamic stability of GI in older women, and effectively improve their foot placement strategy during GI. The findings further confirm the negative effect of sedentary on the stability control of older women and the positive role of Tai Chi in enhancing their gait stability and reducing the risk of falls.
Advancing stroke therapy: the potential of MOF-based nanozymes in biomedical applications
Authors: Chen Meirong , Qin Yang , Peng Yongmei , Mai Ruyu , Teng Huanyao , Qi Zhongquan , Mo Jingxin
Published: May 2024

In this study, we explored the growing use of metal-organic framework (MOF)-based Nanozymes in biomedical research, with a specific emphasis on their applications in stroke therapy. We have discussed the complex nature of stroke pathophysiology, highlighting the crucial role of reactive oxygen species (ROS), and acknowledging the limitations of natural enzymes in addressing these challenges. We have also discussed the role of nanozymes, particularly those based on MOFs, their structural similarities to natural enzymes, and their potential to improve reactivity in various biomedical applications. The categorization of MOF nanozymes based on enzyme-mimicking activities is discussed, and their applications in stroke therapy are explored. We have reported the potential of MOF in treating stroke by regulating ROS levels, alleviation inflammation, and reducing neuron apoptosis. Additionally, we have addressed the challenges in developing efficient antioxidant nanozyme systems for stroke treatment. The review concludes with the promise of addressing these challenges and highlights the promising future of MOF nanozymes in diverse medical applications, particularly in the field of stroke treatment.
Construction of yeast microbial consortia for petroleum hydrocarbons degradation
Authors: Wang Minzhen , Zhou Mengyu , Li Hengchang , Cao Zhibei , Ding Mingzhu , Yuan Yingjin
Published: May 2024

Microbial degradation of petroleum hydrocarbons plays a vital role in mitigating petroleum contamination and heavy oil extraction. In this study, a Saccharomyces cerevisiae capable of degrading hexadecane has been successfully engineered, achieving a maximum degradation rate of up to 20.42%. However, the degradation ability of this strain decreased under various pressure conditions such as high temperature, high osmotic pressure, and acidity conditions. Therefore, a S. cerevisiae with high tolerance to these conditions has been constructed. And then, we constructed an “anti-stress hydrocarbon-degrading” consortium comprising engineered yeast strain SAH03, which degrades hexadecane, and glutathione synthetic yeast YGSH10, which provides stress resistance. This consortium was able to restore the degradation ability of SAH03 under various pressure conditions, particularly exhibiting a significant increase in degradation rate from 5.04% to 17.04% under high osmotic pressure. This study offers a novel approach for improving microbial degradation of petroleum hydrocarbons.
The impact of preanalytical variables on the analysis of cell-free DNA from blood and urine samples
Authors: Peng Hongwei , Pan Ming , Zhou Zongning , Chen Congbo , Xing Xing , Cheng Shaoping , Zhang Shanshan , Zheng Hang , Qian Kaiyu
Published: May 2024

Cell-free DNA (cfDNA), a burgeoning class of molecular biomarkers, has been extensively studied across a variety of biomedical fields. As a key component of liquid biopsy, cfDNA testing is gaining prominence in disease detection and management due to the convenience of sample collection and the abundant wealth of genetic information it provides. However, the broader clinical application of cfDNA is currently impeded by a lack of standardization in the preanalytical procedures for cfDNA analysis. A number of fundamental challenges, including the selection of appropriate preanalytical procedures, prevention of short cfDNA fragment loss, and the validation of various cfDNA measurement methods, remain unaddressed. These existing hurdles lead to difficulties in comparing results and ensuring repeatability, thereby undermining the reliability of cfDNA analysis in clinical settings. This review discusses the crucial preanalytical factors that influence cfDNA analysis outcomes, including sample collection, transportation, temporary storage, processing, extraction, quality control, and long-term storage. The review provides clarification on achievable consensus and offers an analysis of the current issues with the goal of standardizing preanalytical procedures for cfDNA analysis.
Factors influencing small holder farmers adoption of climate SMART agriculture practices in Welmera Woreda, Central Ethiopia
Authors: Gudina Mesay Hailu , Alemu Esubalew Abate
Published: May 2024

Adoption of climate-smart agriculture practices are believed to have significantly lessened the devastating impact of climate change on agriculture. However, in countries like Ethiopia, the adoption and use level of climate-smart agriculture practices remains low. The understanding of farmers’ levels of CSA practice adoption and influencing factors is therefore crucial. The goal of the study is to evaluate the degree to which various CSA practices were being used in the study area, as well as adoption determinants. The study was conducted in Welmera district, Oromia, Ethiopia. Three kebeles were chosen from the district, and a random sample of 306 farmers was picked. We used a cross-sectional household survey, a focus group discussion, and interviews with key informants. A multivariate probit model was employed to investigate the factors influencing the adoption of multiple climate-smart agriculture practices. According to the result, conservation agriculture, integrated soil fertility management, and crop diversification are the most often used CSA practices. The results also revealed that male farmers outperformed female farmers in terms of crop diversity and improved animal feed and feeding practice adoption. The age of farmers has a considerable and unfavorable impact on their likelihood of adopting improved soil fertility management and crop diversification practices. However, it has a positive and considerable impact on the adoption of agroforestry practices. With regards to economic factors, having a relatively big farmland area considerably enhances the adoption of conservation agriculture, enhances soil fertility management and crop diversity, and improves livestock feed and feeding methods and post-harvest technology practice. Improved livestock feed and feeding are more likely to be used with higher farm income. Having a significant number of animals strongly promotes the adoption of conservation agriculture, and access to financial services positively impacts agroforestry, diversification of crops, and postharvest technology practice adoption. Furthermore, institutional factors including access to agricultural extension services and training were discovered to be important and beneficial for crop diversification; similarly, access to field day participation was discovered to have a significant and positive impact on the adoption of conservation agriculture and improved soil fertility management practices. It is critical to raise awareness about climate change among farmers and experts, as well as to incorporate location-specific CSA practices into agricultural programs.
Relationship of physical activity and cognitive functioning among breast cancer survivors: a cross-sectional analysis
Authors: Hartman Sheri J. , Zablocki Rong W. , Tam Rowena M. , Palmer Barton W. , Parker Barbara A. , Sears Dorothy D. , Ahles Tim A. , Natarajan Loki
Published: May 2024

Introduction

Cancer related cognitive decline is a common long-term side effect of cancer and its treatments among breast cancer survivors. Physical activity is a modifiable risk factor related to cognitive decline. However, existing research lacks consensus regarding the relationship between cognition and exercise as well as the impact of cancer treatments on this relationship. Baseline data from an ongoing randomized clinical trial was utilized to examine the relationship between self-reported and objectively measured cognition with physical activity. Exploratory analyses examined cancer treatments as potential moderators.

Methods

Breast cancer survivors (N = 253) completed a battery of neurocognitive tests, the PROMIS Cognitive abilities questionnaire, medical charts abstracted for treatment information, and wore an ActiGraph accelerometer at the waist for 7 days. Data were analyzed using multiple linear regression models.

Results

Participants were on average 58.5 (SD = 8.88) years old, diagnosed 3 years prior to enrollment (SD = 1.27) with 57% treated with chemotherapy and 80% receiving hormone therapy at baseline. Better self-reported cognitive ability was significantly associated with greater min of moderate to vigorous physical activity (MVPA; β = 0.070, se = 0.028, p = 0.012). There were no significant associations with any objectively measured cognitive domains. Time since diagnosis (years) was a significant moderator of MVPA and Processing Speed (β = −0.103, se = 0.043, p = 0.017). Treatment with chemotherapy and/or hormones did not significantly moderate the relationship between MVPA and any of the cognitive measures or domains.

Conclusion

Findings suggest that physical activity is related to self-reported cognition but not objectively measured cognition. Greater physical activity was associated with faster processing speed in participants closer in time to their cancer diagnosis. These results emphasize the need for more research to understand when cancer survivors may benefit from physical activity and what aspects of cognition may be improved.
Branding countries through multicultural events: a quantitative analysis of the impact of the FIFA World Cup 2022 on Qatar’s brand
Authors: Kerry Lucyann , Aguerrebere Pablo Medina , Burgess Scott , Chadli Lakhdar
Published: May 2024

Private and public companies, as well as public authorities and governments, resort to corporate communication to build trust relationships with their stakeholders and, in this way, reinforce their corporate brands. However, they face different challenges including social transformations and cultural changes. This study evaluates how the FIFA World Cup 2022 impacted Qatar’s brand. To do that, we conducted a review of the literature about corporate communication and nation branding, and then, we carried out a quantitative content analysis of how the leading newspapers in the world’s most influential countries (United States, China, United Kingdom, France, and Germany) covered this event from a corporate communication perspective. These newspapers were selected based on highest circulation. The results from the analysis showed that media companies from France were the ones making more references to Qatar’s History (59); journalists from the United States were the most interested in the Qatar Brand (14); and British newspapers were the ones who published more content about the FIFA World Cup 2022 brand (53).
Exercise improves cardiac fibrosis by stimulating the release of endothelial progenitor cell-derived exosomes and upregulating miR-126 expression
Authors: Fu Genzhuo , Wang Zhao , Hu Siyuan
Published: May 2024

Cardiac fibrosis is an important pathological manifestation of various cardiac diseases such as hypertension, coronary heart disease, and cardiomyopathy, and it is also a key link in heart failure. Previous studies have confirmed that exercise can enhance cardiac function and improve cardiac fibrosis, but the molecular target is still unclear. In this review, we introduce the important role of miR-126 in cardiac protection, and find that it can regulate TGF-β/Smad3 signaling pathway, inhibit cardiac fibroblasts transdifferentiation, and reduce the production of collagen fibers. Recent studies have shown that exosomes secreted by cells can play a specific role through intercellular communication through the microRNAs carried by exosomes. Cardiac endothelial progenitor cell-derived exosomes (EPC-Exos) carry miR-126, and exercise training can not only enhance the release of exosomes, but also up-regulate the expression of miR-126. Therefore, through derivation and analysis, it is believed that exercise can inhibit TGF-β/Smad3 signaling pathway by up-regulating the expression of miR-126 in EPC-Exos, thereby weakening the transdifferentiation of cardiac fibroblasts into myofibroblasts. This review summarizes the specific pathways of exercise to improve cardiac fibrosis by regulating exosomes, which provides new ideas for exercise to promote cardiovascular health.
Multi-modal recommender system for predicting project manager performance within a competency-based framework
Authors: Jemal Imene , Naoussi Sijou Wilfried Armand , Chikhaoui Belkacem
Published: May 2024

The evaluation of performance using competencies within a structured framework holds significant importance across various professional domains, particularly in roles like project manager. Typically, this assessment process, overseen by senior evaluators, involves scoring competencies based on data gathered from interviews, completed forms, and evaluation programs. However, this task is tedious and time-consuming, and requires the expertise of qualified professionals. Moreover, it is compounded by the inconsistent scoring biases introduced by different evaluators. In this paper, we propose a novel approach to automatically predict competency scores, thereby facilitating the assessment of project managers' performance. Initially, we performed data fusion to compile a comprehensive dataset from various sources and modalities, including demographic data, profile-related data, and historical competency assessments. Subsequently, NLP techniques were used to pre-process text data. Finally, recommender systems were explored to predict competency scores. We compared four different recommender system approaches: content-based filtering, demographic filtering, collaborative filtering, and hybrid filtering. Using assessment data collected from 38 project managers, encompassing scores across 67 different competencies, we evaluated the performance of each approach. Notably, the content-based approach yielded promising results, achieving a precision rate of 81.03%. Furthermore, we addressed the challenge of cold-starting, which in our context involves predicting scores for either a new project manager lacking competency data or a newly introduced competency without historical records. Our analysis revealed that demographic filtering achieved an average precision of 54.05% when dealing with new project managers. In contrast, content-based filtering exhibited remarkable performance, achieving a precision of 85.79% in predicting scores for new competencies. These findings underscore the potential of recommender systems in competency assessment, thereby facilitating more effective performance evaluation process.
Forecasting cryptocurrency's buy signal with a bagged tree learning approach to enhance purchase decisions
Authors: Alsini Raed , Abu Al-Haija Qasem , Alsulami Abdulaziz A. , Alturki Badraddin , Alqurashi Abdulaziz A. , Mashat Mouhamad D. , Alqahtani Ali , Alhebaishi Nawaf
Published: May 2024

Introduction

The cryptocurrency market is captivating the attention of both retail and institutional investors. While this highly volatile market offers investors substantial profit opportunities, it also entails risks due to its sensitivity to speculative news and the erratic behavior of major investors, both of which can provoke unexpected price fluctuations.

Methods

In this study, we contend that extreme and sudden price changes and atypical patterns might compromise the performance of technical signals utilized as the basis for feature extraction in a machine learning-based trading system by either augmenting or diminishing the model's generalization capability. To address this issue, this research uses a bagged tree (BT) model to forecast the buy signal for the cryptocurrency market. To achieve this, traders must acquire knowledge about the cryptocurrency market and modify their strategies accordingly.

Results and discussion

To make an informed decision, we depended on the most prevalently utilized oscillators, namely, the buy signal in the cryptocurrency market, comprising the Relative Strength Index (RSI), Bollinger Bands (BB), and the Moving Average Convergence/Divergence (MACD) indicator. Also, the research evaluates how accurately a model can predict the performance of different cryptocurrencies such as Bitcoin (BTC), Ethereum (ETH), Cardano (ADA), and Binance Coin (BNB). Furthermore, the efficacy of the most popular machine learning model in precisely forecasting outcomes within the cryptocurrency market is examined. Notably, predicting buy signal values using a BT model provides promising results.
Quantifying uncertainty in graph neural network explanations
Authors: Jiang Junji , Ling Chen , Li Hongyi , Bai Guangji , Zhao Xujiang , Zhao Liang
Published: May 2024

In recent years, analyzing the explanation for the prediction of Graph Neural Networks (GNNs) has attracted increasing attention. Despite this progress, most existing methods do not adequately consider the inherent uncertainties stemming from the randomness of model parameters and graph data, which may lead to overconfidence and misguiding explanations. However, it is challenging for most of GNN explanation methods to quantify these uncertainties since they obtain the prediction explanation in a post-hoc and model-agnostic manner without considering the randomness of graph data and model parameters. To address the above problems, this paper proposes a novel uncertainty quantification framework for GNN explanations. For mitigating the randomness of graph data in the explanation, our framework accounts for two distinct data uncertainties, allowing for a direct assessment of the uncertainty in GNN explanations. For mitigating the randomness of learned model parameters, our method learns the parameter distribution directly from the data, obviating the need for assumptions about specific distributions. Moreover, the explanation uncertainty within model parameters is also quantified based on the learned parameter distributions. This holistic approach can integrate with any post-hoc GNN explanation methods. Empirical results from our study show that our proposed method sets a new standard for GNN explanation performance across diverse real-world graph benchmarks.
I think therefore I learn: metacognition is a better predictor of school readiness than executive functions
Authors: Dutemple Elizabeth , Brokl Carlye , Poulin-Dubois Diane
Published: May 2024

Previous research suggests that metacognition (the knowledge and skills related to knowledge acquisition) and executive functions (skills needed to plan and execute goals) are possible predictors of academic performance, including math and reading abilities. This study sought to clarify the relationship between school readiness and these abilities. A visual identification task was used to measure preschool children's metacognitive skills, specifically their ability to monitor their confidence on their answers (explicit) and ability to ask for a clue only when necessary (implicit). Response time to answering was also measured to obtain a non-verbal implicit measure of metacognition. Executive functions were measured using the Flanker and Dimensional Change Card Sorting (DCCS) tasks from the NIH toolbox. It was hypothesized that both metacognition and executive functions would predict school readiness and that implicit metacognitive skills would be more highly related to school readiness than explicit skills. A hierarchical linear regression was run with age and sex as control variables, and with executive function and metacognition (implicit and explicit) as predictors. Results indicated that both implicit and explicit metacognition remained significant predictors of school readiness scores beyond age and sex. In addition, we found correlations between explicit metacognition and executive functions and a relationship between response time and explicit metacognitive skill. Results highlight the importance of early metacognitive abilities beyond other cognitive skills and the importance of being able to effectively use metacognitive strategies from a young age. The implications relating to academic abilities are discussed.
Neanderthal resilience and adaptability: insights from the Abric Pizarro faunal assemblage during the MIS 4
Authors: Westbury Eboni , Samper Carro Sofía , Vega Bolivar Susana , Pizarro Jezabel , Martínez-Moreno Jorge , Mora Rafael
Published: May 2024

The examination of faunal assemblages through zooarchaeological analyses constitutes a fundamental approach for gaining insight into the intricate behaviours of Neanderthals. Previous investigations have primarily focused on periods of relative environmental stability, and this has provided a wealth of relevant archaeological data. However, our understanding of Neanderthal resilience during the MIS 4, a period presumably characterised by harsh environmental conditions, remains limited. This study presents the first comprehensive analysis of the faunal assemblages from Levels M and P at Abric Pizarro. The geographic location of Abric Pizarro in the southeast Pre-Pyrenees, combined with chronometric dating, offers a unique opportunity to explore Neanderthal behaviours during a poorly known chronological period. The detailed zooarchaeological analysis comprised taxonomic identification, taphonomic analysis and age-at-death profiling to explore the adaptability and flexibility in the Neanderthal diet. The findings indicate that Neanderthal groups incorporated a diverse range of protein resources from small herbivores (e.g., caprids) to very large herbivores (e.g., Bos/Bison). These results not only demonstrate an adaptability to changing environments in an area traditionally deemed unsuitable for long-term occupation, but also contributes significantly to our understanding of the complex behaviours exhibited by Neanderthals.
Mechanism of stress transmission and feasibility of mining the lower coal seam under repeated mining in close-multiple coal seams
Authors: Yang Dapeng , Li Tiezheng , Li Yang , Ren Yuqi
Published: May 2024

Mining in an upper coal seam results in the redistribution of vertical stress within a lower coal seam until a new equilibrium state is attained. Close-multiple coal seams mining faces the occurrence of multi-goafs and a complex stress environment. Based on a case study of close-multiple coal seams with repeated mining in the Qianjiaying coal mine, a stress distribution model of the floor in the coal seam striking range was established by optimizing the load form of the abutment pressure. The floor stress state after primary and repeated mining of upper coal seams was analyzed in a visual and quantitative manner. The concentrations of vertical stress, horizontal stress, and shear stress are all located in the floor under the coal rib after primary and repeated mining. The curve of stresses gradually levels off as the depth of the floor increases, indicating a diminishing influence of mining-induced stress from the upper coal seam. Based on the stress analysis by numerical simulations, the overall lower coal seam remains in a state of large-scale stress relief. Stress relief occurred twice under repeated mining, which indicates that the lower coal seam has favorable mining feasibility. The results of the study can provide scientific guidance to prevent mining accidents.
An evaluation method for integrating EVs in distribution networks with clustering algorithms
Authors: Chao Lu , Yu Lu , Yihua Liu , Menghua Deng , Yanjun Chen , Ruochen Duan
Published: May 2024

Introduction: With the installation of advanced metering infrastructures, the operation data of EVs in the distribution networks can be obtained with time intervals of seconds and minutes. Based on these operation data, the impacts of integrating EVs into the distribution networks can be calculated and discussed.

Methods: In this paper, an improved clustering algorithm with a new distance index for the daily curves of different types of EVs was proposed. The different types of EVs can be classified into several typical groups and the required number of operation scenarios can be reduced. After reducing the large-scale database to typical clusters, research can be conducted on the characteristics of EVs specific to certain scenarios.

Results and discussion: In this way, the capability of integrating different types of EVs into the distribution network, such as fast EV charging stations, slow EV charging stations, and EV bus charging stations, is assessed from the perspective of load capacity size. The proposed clustering algorithm was verified with practical operation data.
Bipartite networks represent causality better than simple networks: evidence, algorithms, and applications
Authors: Shen Bingran , Coruzzi Gloria M. , Shasha Dennis
Published: May 2024

A network, whose nodes are genes and whose directed edges represent positive or negative influences of a regulatory gene and its targets, is often used as a representation of causality. To infer a network, researchers often develop a machine learning model and then evaluate the model based on its match with experimentally verified “gold standard” edges. The desired result of such a model is a network that may extend the gold standard edges. Since networks are a form of visual representation, one can compare their utility with architectural or machine blueprints. Blueprints are clearly useful because they provide precise guidance to builders in construction. If the primary role of gene regulatory networks is to characterize causality, then such networks should be good tools of prediction because prediction is the actionable benefit of knowing causality. But are they? In this paper, we compare prediction quality based on “gold standard” regulatory edges from previous experimental work with non-linear models inferred from time series data across four different species. We show that the same non-linear machine learning models have better predictive performance, with improvements from 5.3% to 25.3% in terms of the reduction in the root mean square error (RMSE) compared with the same models based on the gold standard edges. Having established that networks fail to characterize causality properly, we suggest that causality research should focus on four goals: (i) predictive accuracy; (ii) a parsimonious enumeration of predictive regulatory genes for each target gene g; (iii) the identification of disjoint sets of predictive regulatory genes for each target g of roughly equal accuracy; and (iv) the construction of a bipartite network (whose node types are genes and models) representation of causality. We provide algorithms for all goals.
Transcriptomic point of departure determination: a comparison of distribution-based and gene set-based approaches
Authors: Costa Eduardo , Johnson Kamin J. , Walker Carl A. , O’Brien Jason M.
Published: May 2024

A key step in assessing the potential human and environmental health risks of industrial and agricultural chemicals is to determine the toxicity point of departure (POD), which is the highest dose level that causes no adverse effect. Transcriptomic POD (tPOD) values have been suggested to accurately estimate toxicity POD values. One step in the most common approach for tPOD determination involves mapping genes to annotated gene sets, a process that might lead to substantial information loss particularly in species with poor gene annotation. Alternatively, methods that calculate tPOD values directly from the distribution of individual gene POD values omit this mapping step. Using rat transcriptome data for 79 molecules obtained from Open TG-GATEs (Toxicogenomics Project Genomics Assisted Toxicity Evaluation System), the hypothesis was tested that methods based on the distribution of all individual gene POD values will give a similar tPOD value to that obtained via the gene set-based method. Gene set-based tPOD values using four different gene set structures were compared to tPOD values from five different individual gene distribution methods. Results revealed a high tPOD concordance for all methods tested, especially for molecules with at least 300 dose-responsive probesets: for 90% of those molecules, the tPOD values from all methods were within 4-fold of each other. In addition, random gene sets based upon the structure of biological knowledge-derived gene sets produced tPOD values with a median absolute fold change of 1.3–1.4 when compared to the original biological knowledge-derived gene set counterparts, suggesting that little biological information is used in the gene set-based tPOD generation approach. These findings indicate using individual gene distributions to calculate a tPOD is a viable and parsimonious alternative to using gene sets. Importantly, individual gene distribution-based tPOD methods do not require knowledge of biological organization and can be applied to any species including those with poorly annotated gene sets.
Identification and analysis of chemokine-related and NETosis-related genes in acute pancreatitis to develop a predictive model
Authors: Mo Shuangyang , Wu Wenhong , Luo Kai , Huang Cheng , Wang Yingwei , Qin Heping , Cai Huaiyang
Published: May 2024

Background: Chemokines and NETosis are significant contributors to the inflammatory response, yet there still needs to be a more comprehensive understanding regarding the specific molecular characteristics and interactions of NETosis and chemokines in the context of acute pancreatitis (AP) and severe AP (SAP).

Methods: To address this gap, the mRNA expression profile dataset GSE194331 was utilized for analysis, comprising 87 AP samples (77 non-SAP and 10 SAP) and 32 healthy control samples. Enrichment analyses were conducted for differentially expressed chemokine-related genes (DECRGs) and NETosis-related genes (DENRGs). Three machine-learning algorithms were used for the identification of signature genes, which were subsequently utilized in the development and validation of nomogram diagnostic models for the prediction of AP and SAP. Furthermore, single-gene Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were performed. Lastly, an interaction network for the identified signature genes was constructed.

Results: We identified 12 DECRGs and 7 DENRGs, and enrichment analyses indicated they were primarily enriched in cytokine-cytokine receptor interaction, chemokine signaling pathway, TNF signaling pathway, and T cell receptor signaling pathway. Moreover, these machine learning algorithms finally recognized three signature genes (S100A8, AIF1, and IL18). Utilizing the identified signature genes, we developed nomogram models with high predictive accuracy for AP and differentiation of SAP from non-SAP, as demonstrated by area under the curve (AUC) values of 0.968 (95% CI 0.937–0.990) and 0.862 (95% CI 0.742–0.955), respectively, in receiver operating characteristic (ROC) curve analysis. Subsequent single-gene GESA and GSVA indicated a significant positive correlation between these signature genes and the proteasome complex. At the same time, a negative association was observed with the Th1 and Th2 cell differentiation signaling pathways.

Conclusion: We have identified three genes (S100A8, AIF1, and IL18) related to chemokines and NETosis, and have developed accurate diagnostic models that might provide a novel method for diagnosing AP and differentiating between severe and non-severe cases.
SIRT1, resveratrol and aging
Authors: Rogina Blanka , Tissenbaum Heidi A.
Published: May 2024

Aging is linked to a time-associated decline in both cellular function and repair capacity leading to malfunction on an organismal level, increased frailty, higher incidence of diseases, and death. As the population grows older, there is a need to reveal mechanisms associated with aging that could spearhead treatments to postpone the onset of age-associated decline, extend both healthspan and lifespan. One possibility is targeting the sirtuin SIRT1, the founding member of the sirtuin family, a highly conserved family of histone deacetylases that have been linked to metabolism, stress response, protein synthesis, genomic instability, neurodegeneration, DNA damage repair, and inflammation. Importantly, sirtuins have also been implicated to promote health and lifespan extension, while their dysregulation has been linked to cancer, neurological processes, and heart disorders. SIRT1 is one of seven members of sirtuin family; each requiring nicotinamide adenine dinucleotide (NAD+) as co-substrate for their catalytic activity. Overexpression of yeast, worm, fly, and mice SIRT1 homologs extend lifespan in each animal, respectively. Moreover, lifespan extension due to calorie restriction are associated with increased sirtuin activity. These findings led to the search for a calorie restriction mimetic, which revealed the compound resveratrol; (3, 5, 4′-trihydroxy-trans-stilbene) belonging to the stilbenoids group of polyphenols. Following this finding, resveratrol and other sirtuin-activating compounds have been extensively studied for their ability to affect health and lifespan in a variety of species, including humans via clinical studies.
PEARR tool training and implementation: building awareness of violence and human trafficking in a hospital system
Authors: Roe-Sepowitz Dominique , Bracy Kristen , Gibbs Holly , Stafford Rae Lynn , Bernardin Brooke , Stoklosa Hanni
Published: May 2024

Introduction

Health professionals have an opportunity to assist patients who are experiencing many types of violence, including human trafficking; however, current approaches are often not person-centered. The Provide privacy, Educate, Ask, Respect and Respond (PEARR) Tool, a recognized screening tool in the U.S., is a structured conversation guide for health professionals on how to provide trauma-sensitive assistance to patients who may be experiencing such violence, including human trafficking. This is the first study to evaluate the PEARR Tool and its use in hospital settings.

Methods

A U.S.-based health system adopted the PEARR Tool as part of its Abuse, Neglect, and Violence policy and procedure. To support successful adoption, the health system also developed educational modules on human trafficking and trauma-informed approaches to patient care, including a module on the PEARR steps. In October 2020 and June 2021, a voluntary “PEARR Tool Training and Implementation Survey” was distributed to emergency department staff in three hospitals. The survey consisted of 22 questions: eight demographic and occupation related questions; five questions related to the education provided to staff; and, nine questions related to the use of the PEARR Tool in identifying and assisting patients.

Results

The overall findings demonstrate a general increase in awareness about the prevalence of human trafficking, as well as a significant increase in awareness about the implementation of the PEARR Tool. However, the findings demonstrate that most respondents were not utilizing the PEARR Tool between October 2020 and June 2021. Most reported that the reason for this was because they had not suspected any of their patients to be victims of abuse, neglect, or violence, including human trafficking. Of those that had utilized the PEARR Tool, there was a marked increase in staff that reported its usefulness and ease of access when caring for patients.

Discussion

The COVID-19 pandemic posed many challenges during this study, including delays in staff education, changes in education format and delivery, and strains on staff. Initial data regarding the use of the PEARR Tool is promising; and additional research is recommended.
Response of microbial diversity and function to the degradation of Barkol Saline Lake
Authors: Liu Yong-Hong , Gao Lei , Jiang Hong-Chen , Fang Bao-Zhu , Huang Yin , Li Li , Li Shuai , Abdugheni Rashidin , Lian Wen-Hui , Zhang Jing-Yi , Yang Zhen-Dong , Mohamad Osama Abdalla Abdelshafy , Li Wen-Jun
Published: May 2024

Barkol Lake, a shrinking hypersaline lake situated in the northeast of Xinjiang, China, has experienced the exposure of its riverbed and the gradual drying up of its original sediment due to climate change and human activities, resulting in the formation of alkaline soils. These changes have correspondingly altered the physicochemical characteristics of the surrounding environment. Microorganisms play a crucial role, with special functioning involved in various nutrient cycling and energy transfer in saline lake environments. However, little is known about how the microbial community dynamics and metabolic functions in this shrinking saline lake relate to the degradation process. To address this knowledge gap, a cultivation-independent method of amplicon sequencing was used to identify and analyze the microbial community and its potential ecological functions in the sediment and degraded area. The microbial community diversity was found to be significantly lower in the degraded areas than in the sediment samples. The Pseudomonadota was dominant in Barkol Saline Lake. The abundance of Desulfobacterota and Bacillota in the degraded areas was lower than in the lake sediment, while Pseudomonadota, Acidobacteriota, and Actinobacteriota showed an opposite trend. The βNTI showed that microbial community assembly was primarily associated with deterministic processes in Barkol Saline Lake ecosystems and stochastic processes at the boundary between sediment and degraded areas. Functional predictions showed that sulfur metabolism, particularly sulfate respiration, was much higher in sediment samples than in the degraded areas. Overall, these findings provided a possible perspective for us to understand how microorganisms adapt to extreme environments and their role in saline lakes under environmental change.
Heat-killed Akkermansia muciniphila ameliorates allergic airway inflammation in mice
Authors: Yoon Seol Ah , Lim Younggap , Byeon Hye Rim , Jung Jiyeon , Ma Seongho , Hong Moon-Gi , Kim Dohak , Song Eun-Ji , Nam Young-Do , Seo Jae-Gu , Lee Sang-Nam
Published: May 2024

Allergic asthma (AA) is a common inflammatory airway disease characterized by increased airway hyper-responsiveness (AHR), inflammation, and remodeling. Akkermansia muciniphila is a strictly anaerobic bacterium residing in the gut and is a promising next-generation probiotic to improve metabolic inflammatory syndrome. A recent study suggested the beneficial effect of live A. muciniphila on allergic airway inflammation (AAI) in mice. However, whether the heat-killed form can improve AAI requires further investigation. Mice sensitized and challenged with house dust mites (HDM) develop AA hallmarks including inflammatory cell infiltration, goblet cell hyperplasia, and subepithelial collagen deposition in the lungs. These phenomena were reversed by oral administration of the heat-killed A. muciniphila strain EB-AMDK19 (AMDK19-HK) isolated from the feces of healthy Koreans. Furthermore, AMDK19-HK diminished the HDM-induced AHR to inhaled methacholine, lung mast cell accumulation, and serum HDM-specific IgE levels. It also led to the overall suppression of IL-4, IL-13, and eotaxin production in bronchoalveolar lavage fluids, and Il4, Il5, Il13, and Ccl17 gene expression in lung tissues. Moreover, AMDK19-HK suppressed Th2-associated cytokine production in the splenocytes of HDM-sensitized mice in vitro. Additionally, a combination of 16S rRNA gene sequencing and short-chain fatty acid (SCFA) analysis in cecal samples revealed that AMDK19-HK modulated the relative abundance of circulating SCFA-associated gut genera, including a positive correlation with Lachnospiraceae_ NK4A136_group and a negative correlation with Lachnoclostridium and significantly increased cecal SCFA concentrations. Finally, AMDK19-HK improved intestinal mucosal barrier function. These results suggest that the oral administration of AMDK19-HK ameliorates HDM-induced AAI in mice by suppressing Th2-mediated immune responses and could have a protective effect against AA development.
Next generation single-domain antibodies against respiratory zoonotic RNA viruses
Authors: Swart Iris C. , Van Gelder Willem , De Haan Cornelis A. M. , Bosch Berend-Jan , Oliveira Sabrina
Published: May 2024

The global impact of zoonotic viral outbreaks underscores the pressing need for innovative antiviral strategies, particularly against respiratory zoonotic RNA viruses. These viruses possess a high potential to trigger future epidemics and pandemics due to their high mutation rate, broad host range and efficient spread through airborne transmission. Recent pandemics caused by coronaviruses and influenza A viruses underscore the importance of developing targeted antiviral strategies. Single-domain antibodies (sdAbs), originating from camelids, also known as nanobodies or VHHs (Variable Heavy domain of Heavy chain antibodies), have emerged as promising tools to combat current and impending zoonotic viral threats. Their unique structure, coupled with attributes like robustness, compact size, and cost-effectiveness, positions them as strong alternatives to traditional monoclonal antibodies. This review describes the pivotal role of sdAbs in combating respiratory zoonotic viruses, with a primary focus on enhancing sdAb antiviral potency through optimization techniques and diverse administration strategies. We discuss both the promises and challenges within this dynamically growing field.
Reactive spinal glia convert 2-AG to prostaglandins to drive aberrant astroglial calcium signaling
Authors: Dócs Klaudia , Balázs Anita , Papp Ildikó , Szücs Peter , Hegyi Zoltán
Published: May 2024

The endogenous cannabinoid 2-arachidonoylglycerol (2-AG) influences neurotransmission in the central nervous system mainly by activating type 1 cannabinoid receptor (CB1). Following its release, 2-AG is broken down by hydrolases to yield arachidonic acid, which may subsequently be metabolized by cyclooxygenase-2 (COX-2). COX-2 converts arachidonic acid and also 2-AG into prostanoids, well-known inflammatory and pro-nociceptive mediators. Here, using immunohistochemical and biochemical methods and pharmacological manipulations, we found that reactive spinal astrocytes and microglia increase the expression of COX-2 and the production of prostaglandin E2 when exposed to 2-AG. Both 2-AG and PGE2 evoke calcium transients in spinal astrocytes, but PGE2 showed 30% more efficacy and 55 times more potency than 2-AG. Unstimulated spinal dorsal horn astrocytes responded to 2-AG with calcium transients mainly through the activation of CB1. 2-AG induced exaggerated calcium transients in reactive astrocytes, but this increase in the frequency and area under the curve of calcium signals was only partially dependent on CB1. Instead, aberrant calcium transients were almost completely abolished by COX-2 inhibition. Our results suggest that both reactive spinal astrocytes and microglia perform an endocannabinoid-prostanoid switch to produce PGE2 at the expense of 2-AG. PGE2 in turn is responsible for the induction of aberrant astroglial calcium signals which, together with PGE2 production may play role in the development and maintenance of spinal neuroinflammation-associated disturbances such as central sensitization.
A simulation study: comparing independent component analysis and signal-space projection – source-informed reconstruction for rejecting muscle artifacts evoked by transcranial magnetic stimulation
Authors: Mutanen Tuomas Petteri , Ilmoniemi Ida , Atti Iiris , Metsomaa Johanna , Ilmoniemi Risto Juhani
Published: May 2024

Introduction

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) allows researchers to explore cortico-cortical connections. To study effective connections, the first few tens of milliseconds of the TMS-evoked potentials are the most critical. Yet, TMS-evoked artifacts complicate the interpretation of early-latency data. Data-processing strategies like independent component analysis (ICA) and the combined signal-space projection–source-informed reconstruction approach (SSP–SIR) are designed to mitigate artifacts, but their objective assessment is challenging because the true neuronal EEG responses under large-amplitude artifacts are generally unknown. Through simulations, we quantified how the spatiotemporal properties of the artifacts affect the cleaning performances of ICA and SSP–SIR.

Methods

We simulated TMS-induced muscle artifacts and superposed them on pre-processed TMS–EEG data, serving as the ground truth. The simulated muscle artifacts were varied both in terms of their topography and temporal profiles. The signals were then cleaned using ICA and SSP–SIR, and subsequent comparisons were made with the ground truth data.

Results

ICA performed better when the artifact time courses were highly variable across the trials, whereas the effectiveness of SSP–SIR depended on the congruence between the artifact and neuronal topographies, with the performance of SSP–SIR being better when difference between topographies was larger. Overall, SSP–SIR performed better than ICA across the tested conditions. Based on these simulations, SSP–SIR appears to be more effective in suppressing TMS-evoked muscle artifacts. These artifacts are shown to be highly time-locked to the TMS pulse and manifest in topographies that differ substantially from the patterns of neuronal potentials.

Discussion

Selecting between ICA and SSP–SIR should be guided by the characteristics of the artifacts. SSP–SIR might be better equipped for suppressing time-locked artifacts, provided that their topographies are sufficiently different from the neuronal potential patterns of interest, and that the SSP–SIR algorithm can successfully find those artifact topographies from the high-pass-filtered data. ICA remains a powerful tool for rejecting artifacts that are not strongly time locked to the TMS pulse.