bluuebunny/crossref_metadata_2025 huggingface dataset:
A Fast Prediction Model of Supercritical Airfoils Based on Deep Operator Network and Variational Autoencoder Considering Physical Constraints
Authors: Liu Mengxin , Yang Yunjia , Wu Chenyu , Zhang Yufei
Published: December 2024

Flow field prediction is crucial for evaluating the performance of airfoils and aerodynamic optimization. Computational fluid dynamics (CFD) methods usually require a considerable amount of computational resources and time. In this study, a composite model based on deep learning is proposed for flow field prediction. The variational autoencoder (VAE) model is designed to extract representative features of flow fields. The VAE model is trained to determine the optimal latent variable dimension and Kullback-Leibler (KL) divergence weight. Several physical constraints based on mass conservation and pressure coefficient are introduced to reduce the reconstruction loss and improve the model generalization ability. A DeepONet-MLP model, which combines a deep operator network (DeepONet) and a multilayer perceptron (MLP), is trained to achieve the nonlinear mapping from airfoil shapes and lift coefficients to latent variables in the VAE with fewer parameters. Eventually, a DeepONet-MLP-VAE model, which connects the decoder in VAE with DeepONet-MLP, is applied for fast flow field prediction. The results show that the proposed model can accurately and efficiently predict the transonic flow field, with a mean absolute error of 0.0016 and an average processing time of 0.010 s per flow field, which significantly accelerates the CFD evaluation process.
Impact analysis of infant antibiotic exposure on the burden of asthma: a simulation modeling study
Authors: Lee Tae Yoon , Petkau John , Saatchi Ariana , Marra Fawziah , Turvey Stuart E. , Lishman Hannah , Patrick David M. , Cragg Jacquelyn J. , Johnson Kate M. , Sadatsafavi Mohsen
Published: December 2024

Background

Infant antibiotic use is associated with increased risk of asthma. We examined the population impact of antibiotic exposure in the first year of life on the burden of pediatric asthma in British Columbia, Canada, using simulation modeling.

Methods

We performed a Bayesian meta-analysis of empirical studies to construct dose-response equations between antibiotic exposure in the first year of life and pediatric (<19 years of age) asthma. We used administrative health data to document trends in infant (<1 year of age) antibiotic use in British Columbia during 2001 and 2018 (the study period). An independently developed microsimulation model of asthma was utilized to estimate asthma-related outcomes under three scenarios pertaining to the trends in antibiotic use during the study period: (1) observed trends, (2) flat trend in which the prescription rate remained at the 2001 value, and (3) intermediate trends midway between these two. We reported cumulative person-years with asthma, cumulative asthma incidence, and cumulative asthma exacerbations among the pediatric population during the study period.

Results

There were 773,160 live births during the study period, with an average antibiotic prescription rate of 523 per 1,000 infants in the first year of life. The prescription rate decreased by 71.5% during the study period. In Scenario 1, there were 1,982,861 person-years with asthma, 183,392 asthma incident cases, and 383,072 exacerbations. Had the antibiotic exposure remained at the 2001 values (Scenario 2), there would have been additional 37,213 person-years with asthma, 10,053 asthma incident cases, and 23,280 exacerbations. Had the decline been half of the observed trend (Scenario 3), there would have been additional 20,318 person-years with asthma, 5,486 asthma incident cases, and 12,728 exacerbations. At least 80% of the excess burden in each outcome was attributable to the younger pediatric population of <10 years of age.

Conclusions

The decline in infant antibiotic exposure has resulted in a substantial reduction in the burden of asthma in British Columbia. Such benefits should be considered when evaluating the value proposition of initiatives aimed at reducing unnecessary antibiotic exposure in early life.
The impact of ferroptosis and ferroptosis-related non-coding RNAs on breast cancer progression
Authors: Liu Wenhui , Jiang Chenjun , Ma Yun , Wang Wentao , Peng Jing , Ma Weiqing , Xu Shuxin , Wu Duoming
Published: December 2024

Ferroptosis, distinct from apoptosis, is primarily characterized by the accumulation of iron-dependent lipid peroxides (LPO) and reactive oxygen species (ROS). This process plays a pivotal role in the pathophysiology of various diseases and has recently emerged as a promising therapeutic strategy in oncology, garnering significant attention. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), serve as crucial regulators in numerous biological processes, particularly in cancer initiation and progression. Increasing research efforts are focused on targeting ferroptosis through modulation of these ncRNAs. This review provides an overview of the mechanisms underlying ferroptosis and explores the roles of ncRNAs in breast cancer (BC) and its regulation. Furthermore, we examine the interactions between ferroptosis and ncRNAs in BC, aiming to identify potential therapeutic targets for BC treatment.
Persistent microbial infections and idiopathic pulmonary fibrosis - an insight into non-typeable Haemophilus influenza pathogenesis
Authors: Shadid Anthony , Rich Haydn E. , DeVaughn Hunter , Domozhirov Aleksey , Doursout Marie- Françoise , Weng-Mills Tingting , Eckel-Mahan Kristin L. , Karmouty-Quintana Harry , Restrepo Marcos I. , Shivshankar Pooja
Published: December 2024

Interstitial lung disease (ILD) is characterized by chronic inflammation and scarring of the lungs, of which idiopathic pulmonary fibrosis (IPF) is the most devastating pathologic form. Idiopathic pulmonary fibrosis pathogenesis leads to loss of lung function and eventual death in 50% of patients, making it the leading cause of ILD-associated mortality worldwide. Persistent and subclinical microbial infections are implicated in the acute exacerbation of chronic lung diseases. However, while epidemiological studies have highlighted pollutants, gastric aspirate, and microbial infections as major causes for the progression and exacerbation of IPF, the role of persistent microbial infections in the pathogenesis of IPF remains unclear. In this review, we have focused on the role of persistent microbial infections, including viral, bacterial, and fungal infections, and their mechanisms of action in the pathogenesis of IPF. In particular, the mechanisms and pathogenesis of the Gram-negative bacteria Non-typeable Haemophilus influenzae (NTHi) in ILDs are discussed, along with growing evidence of its role in IPF, given its unique ability to establish persistent intracellular infections by leveraging its non-capsulated nature to evade host defenses. While antibiotic treatments are presumably beneficial to target the extracellular, interstitial, and systemic burden of pathogens, their effects are significantly reduced in combating pathogens that reside in the intracellular compartments. The review also includes recent clinical trials, which center on combinatorial treatments involving antimicrobials and immunosuppressants, along with antifibrotic drugs that help mitigate disease progression in IPF patients. Finally, future directions focus on mRNA-based therapeutics, given their demonstrated effectiveness across a wide range of clinical applications and feasibility in targeting intracellular pathogens.
Preparticipation screening in young female elite ice hockey players
Authors: Mohl Alexander , Pongratz Janis , Muxel Selina , Berger Manuel , Berr Michael , Schneider Bastian , Schlichting-Knoob Anna , Platz Ulrich , Dorwarth Uwe , Rogowski Sebastian , Hoffmann Ellen , Straube Florian
Published: December 2024

Objectives

The occurrence of sudden cardiac death (SCD) in competitive athletes has led to a discussion about appropriate preparticipation screening models. The role of an electrocardiogram (ECG) in routine testing remains controversial in current guidelines. Furthermore, data on cardiac findings and the prognostic utility of screening strategies in young female elite ice hockey is scarce.

Methods

Female elite ice hockey players were enrolled in the open prospective “General Evaluation Program for Arrhythmia-Related Death in Athletes” (GEPARD) registry from 2008 to 2018. A staged preparticipation screening was performed. The main goal was to determine the prevalence of SCD conditions and identify effective screening tools. The secondary aim was to study baseline results and follow-ups on a unique subgroup of young female ice hockey players.

Results

A total of 88 female ice hockey players, mean age 16 ± 1 years, were prospectively enrolled. The prevalence of conditions potentially leading to SCD during competition was 3.4% (3/88). The 12-lead ECG led to the diagnosis of one congenital long QT and one acute myocarditis and showed a number needed to screen of 44, with a specificity of 98%. One athlete demonstrated a relevant pericardial effusion on echocardiography, which was related to acute toxoplasmosis. No cases of SCD occurred during long-term follow-up.

Conclusion

The subgroup of young female ice hockey players showed a notable prevalence of athletes “at risk” of 3.4%, which indicates the importance of preparticipation screening that features a 12-lead ECG as the most important component.
The association between cardiovascular health and obstructive sleep apnea symptoms: findings from NHANES
Authors: Guo Qian , Dong Dong , Zhou Qiang , Huang Shuman , Qiao Xinjie , Dang Zihan , Wang Xiaowu , Zhao Yulin
Published: December 2024

Objective

To investigate the association between cardiovascular health (CVH) and obstructive sleep apnea (OSA) within the U.S. population.

Methods

This study enrolled 12,540 participants aged 20 years and older from the 2007–2008 and 2015–2018 cycles of the National Health and Nutrition Examination Surveys (NHANES). Weighted univariate and multivariate logistic regression were utilized to examine the relationship between CVH and OSA symptoms. Life's Essential 8 (LE 8) metrics was employed to evaluate the CVH status of participants. Identification of OSA symptoms was determined based on a sleep questionnaire. They include (1) how often you snore; (2) how often you snort/stop breathing; or (3) how often you feel overly sleepy during day. Individuals who answered that they snore 3 or more per week; snort/stop breathing 3 or more per week and feel overly sleepy during day 16–30 times per month were classified as having OSA symptoms.

Results

Significant inverse associations were observed between LE8 scores and symptoms of OSA after adjusting for covariates. The 95% CI was 0.750 (0.630,0.893) for the moderate CVH group and 0.573 (0.454,0.723) for the high CVH group. Subgroup analyses, stratified by age and gender, highlighted a significant interaction between LE8 scores and OSA symptoms with age (P < 0.0001). Participants under 60 years old in the high CVH group exhibited a reduced likelihood OSA symptoms (OR: 0.470; 95% CI: 0.345,0.641). Restricted cubic splines (RCS) in a multivariate regression analysis showed a non-linear relationship between LE8 score and OSA. Our finding demonstrates a substantial decrease in OSA symptom prevalence with increased LE 8 scores.

Conclusion

The results demonstrate a strong inverse correlation between LE8 scores and OSA symptoms. Participants with higher LE8 scores showed a reduced likelihood of experiencing OSA symptoms.
Fostering Improvement: a reflection on equity-centered improvement across three initiatives
Authors: Eubanks Segun , Neumerski Christine M. , Callahan Pamela Catherine , Anthony Douglas , Snell Jean , Blondonville Damaries , Viviani William , Liccione Laura
Published: December 2024

In this conceptual piece, we explore the emerging definition of equity-centered improvement in education. We describe how the Center for Educational Improvement and Innovation, a partnership center at the University of Maryland College Park, both conceptualizes and operationalizes equity across three initiatives: (1) a district-embedded networked improvement community focused on math achievement and social/emotional learning; (2) a school improvement leadership academy which offers evidence-based professional learning to principals and assistant principals serving in high need schools in Maryland and New Jersey; and (3) a racial and social justice collaborative utilizing a research-practice partnership to address issues of equity within Maryland school districts. We present this article as a type of “reflective practice” as we consider how equity-focused continuous improvement plays out across these three initiatives. In focusing on how each initiative embeds and develops equity-focused improvement practices, we investigate the connection between our shared understanding of equity and its implementation.
Studying targeted oxidation in diabetic cognitive dysfunction based on scientometrics analysis: research progress of natural product approaches
Authors: Tu Wenling , Xu Fuhang , Li Jieying , Tian Xiangfeng , Cao Lingyong , Wang Lei , Qu Yiqian
Published: December 2024

Purpose

The aim is to provide new insights for researchers studying the pathogenesis of diabetic cognitive dysfunction and promoting the wider use of natural products in their treatment.

Method

First, the Web of Science Core Collection was selected as the data source for a computerized literature search on oxidative stress and diabetic cognitive dysfunction (DCD). Next, Biblimetrix and VOSviewer performed statistical analysis focusing on publication countries, institutions, authors, research hotspots, and emerging directions in the field. Then, through the analysis of keywords and key articles, the forefront of the field is identified. Finally, we discussed the pathogenesis of DCD, the influence of oxidative stress on DCD and the antioxidant effect of natural products on DCD.

Result

293 valid papers were obtained. Bibliometrics showed that oxidative stress, diabetes, Alzheimer’s disease (AD), cognitive decline, insulin resistance and quercetin were the key words of the symbiotic network.

Conclusion

The antioxidant effects of natural products in improving DCD have been extensively studied in preclinical studies, providing potential for their treatment in DCD, but their evaluation in clinical trials is currently uncommon.
A stress paradox: the dual role of the unfolded protein response in the placenta
Authors: Chowdhury Diba , Jang Chloe E. , Lajoie Patrick , Renaud Stephen J.
Published: December 2024

The placenta is a temporary organ that forms during pregnancy and is essential for fetal development and maternal health. As an endocrine organ, proper placental function requires continual production, folding, and transport of proteins and lipids. Central to these processes is the endoplasmic reticulum (ER), a dynamic organelle responsible for maintaining cellular protein and lipid synthesis and processing. ER stress occurs when there is an accumulation of unfolded or misfolded proteins, which triggers the activation of cellular pathways collectively called the unfolded protein response. Unfolded protein response pathways act to alleviate the misfolded protein burden and restore ER homeostasis, or if unresolved, initiate cell death. While prolonged ER stress has been linked to deficient placental function and adverse pregnancy outcomes, basal activation of unfolded protein response pathways is required for placental development and function. This review explores the importance of ER homeostasis in placental development and function, examining how disruptions in ER stress responses may contribute to adverse pregnancy outcomes.
Learning-driven load frequency control for islanded microgrid using graph networks-based deep reinforcement learning
Authors: Guo Wangyong , Du Hongwei , Han Tao , Li Shuang , Lu Chao , Huang Xiaoming
Published: December 2024

As the complexity of microgrid systems, the randomness of load disturbances, and the data dimensionality increase, traditional load frequency control methods for microgrids are no longer capable of handling such highly complex and nonlinear control systems. This can result in this can result in significant frequency fluctuations and oscillations, potentially leading to blackouts in microgrids. To address the random power disturbances introduced by a large amount of renewable energy, this paper proposes a Learning-Driven Load Frequency Control (LD-LFC) method. Additionally, a Graph Convolution Neural Networks -Proximal Policy Optimization (GCNN -PPO) algorithm is introduced, which enhances the random power disturbances introduced by a large amount of renewable energy. Algorithm is introduced, which enhances the perception ability of the reinforcement learning agent regarding grid state data by embedding a graph convolutional network. The effectiveness of this approach is validated through simulations on the isolated microgrid Load Frequency Control (LFC) model of China Southern Grid (CSG).
Prevalence of meconium-stained amniotic fluid and factors associated with emergency cesarean section: multicenter cross-sectional study in south central Ethiopia
Authors: Tantu Temesgen , Melkamu Biruk , Gunta Muluken , Tantu Tayech , Aregawi Yohanna , Gashaw Dereje
Published: December 2024

Background

Meconium is thick black-green fetal intestinal content starting from the early first trimester of gestation. Unfortunately, if it is released into the amniotic cavity due to any cause, it can be associated with neonatal mortality and morbidity.

Objective

To identify the factors associated with meconium-stained amniotic fluid among mothers undergoing emergency cesarean section in specialized hospitals cross-sectional study in south central Ethiopia from August 1, 2022, to 30, October 2022

Method

Institution based multicenter cross-sectional study was done prospectively through meticulous chart review and interview on 875 mothers who gave birth with emergency cesarean section. Data were entered using Epi data 7 and analyzed with SPSS 26. The association between independent variables and meconium-stained amniotic fluid was estimated using an odds ratio with 95% confidence intervals. The statistical significance of the association was declared at P-value < 0.05

Result

The prevalence of meconium-stained amniotic fluid is 31.4%. Gravidity (AOR 3.643; 95% CI:1.215,10.921), time interval between decision to delivery (AOR 1.361; 95% CI: 0.424,4.365),eclampsia(AOR 8.022; 95% CI: 1.634,39.372), time taken from referring institution to managing institution (AOR 15.258; 95% CI: 1.591,146.328), obstructed labor (AOR 24.614; 95% CI: 6.073,99.766), cephalopelvic disproportion (AOR 2.640; 95% CI:1.002,6.950), fetal heart beat abnormality (fetal bradycardia AOR 2.068; 95%CI 0.997,4.292) (fetal tachycardia AOR 3.513; 95% CI:1.633,7.556) duration of labor(AOR 5.44; 95% CI: 1.355,9.782) and referral from health center(AOR 5.41; 95% CI: 2.053,14.272) are associated with MSAF whereas obstetric complications(AOR 6.820; 95% CI: 2.870,16.202), cesarean section scar (AOR 3.010; 95% CI: 1.344,6.740) are negatively associated.

Conclusion

Prevalence of meconium-stained amniotic fluid is relatively high for which intrapartum, obstetric and institution related factors are incriminated. Therefore, an improvement in the quality of antenatal and intrapartum care is strongly recommended; professional development at the health center, building the infrastructure, and strengthening the referral system is also suggested.
Endostatin as a biomarker of systemic sclerosis: insights from a systematic review and meta-analysis
Authors: Mangoni Arduino A. , Zinellu Angelo
Published: December 2024

Introduction

The critical role played by vascular dysfunction and ineffective angiogenesis in the pathophysiology of systemic sclerosis (SSc) suggests that circulating biomarkers reflecting these alterations may be useful in the clinical evaluation of this patient group. We sought to address this issue by conducting a systematic review and meta-analysis of studies investigating a such candidate biomarker, endostatin, an endogenous glycoprotein exerting anti-angiogenic effects, in SSc patients and healthy controls.

Methods

A literature search was conducted in the electronic databases Web of Science, PubMed, and Scopus from inception to 27 May 2024. Risk of bias and certainty of evidence were assessed using the JBI checklist for analytical studies and GRADE, respectively.

Results

In 19 eligible studies, circulating endostatin concentrations were significantly higher in SSc patients than controls (standard mean difference, SMD=0.90, 95% CI 0.56 to 1.23, p<0.001; low certainty of evidence). Endostatin concentrations were also significantly higher in SSc patients with digital ulcers than those without (SMD=0.43, 95% CI 0.24 to 0.62, p<0.001; very low certainty of evidence) and in patients with pulmonary arterial hypertension than those without (SMD=1.21, 95% CI 0.67 to 1.76, p<0.001; very low certainty of evidence). By contrast, no significant differences were observed between SSc patients with limited vs. diffuse disease and those with different video capillaroscopy patterns. There was limited evidence regarding endostatin concentrations in SSc patients with interstitial lung disease, telangiectasias, and gastrointestinal manifestations. There were no significant associations in meta-regression and subgroup analysis of studies investigating endostatin in SSc patients and controls between the effect size and various patient and study characteristics.

Discussion

Therefore, the results of this systematic review and meta-analysis suggest that measuring endostatin can be useful in assessing the presence of SSc and specific complications, i.e., digital ulcers and pulmonary arterial hypertension, in these patients.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42024558174.
Efficacy and safety of immune checkpoint inhibitors for EGFR mutated non-small cell lung cancer: a network meta-analysis
Authors: Zhu Lin , He Wenjuan , Xie Cunlei , Shu Yang , Zhang Chunxia , Zhu Yawen
Published: December 2024

Introduction

Non-small cell lung cancer (NSCLC) constitutes approximately 80–85% of cancer-related fatalities globally, and direct and indirect comparisons of various therapies for NSCLC are lacking. In this study, we aimed to compare the efficacy and safety of immune checkpoint inhibitors (ICIs) in patients with epidermal growth factor receptor (EGFR)-mutated NSCLC.

Methods

The electronic databases were systematically searched from inception until March 18, 2024. Studies comparing two or more treatments involving ICIs in patients with EGFR-mutated NSCLC were included. The primary endpoints were overall survival (OS) and progression-free survival (PFS), and the secondary endpoints were overall response rate (ORR), any grade adverse events (AEs), grade ≥3 AEs, and AEs requiring treatment discontinuation. The R software with the gemtc package was used to compare the outcomes of the different treatments.

Results

In 11 eligible studies involving 1462 patients and 5 regimens (chemotherapy [chemo], ICI, ICI+chemo, antiangiogenesis+chemo, and ICI+antiangiogenesis+chemo), ICI+antiangiogenesis+chemo achieved the most favorable OS compared to chemo (HR=0.74, 95% CI 0.41–1.23), ICI+chemo (HR=0.94, 95% CI 0.57–1.46), and ICI (HR=0.58, 95% CI 0.27–1.08) and a nearly equivalent effect to antiangiogenesis+chemo (HR=1.01, 95% CI 0.52–1.92). The PFS and ORR results were similar to those of OS. ICI monotherapy exhibited the lowest toxicity profile.

Conclusions

These findings indicate that ICI+antiangiogenesis+chemo may be potentially beneficial for patients with EGFR-mutated NSCLC. However, the observed difference was not significant; thus, more studies are needed to confirm the efficacy and safety of the combined ICI treatment strategy.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023424781.
Pathogenic mechanisms and potential applications of extracellular vesicles from periodontal pathogens in periodontitis
Authors: Zhang Ruiqing , Li Guoliang , Wu Yingtao , Wang Xiaoxuan , Luan Qingxian
Published: December 2024

Periodontitis is a multifactorial disease characterized by chronic destruction of the periodontal supporting tissues and is closely associated with the dysbiosis of the plaque biofilm. It is the leading cause of tooth loss in adults. Bacterial extracellular vesicles (BEVs) are released from bacteria, which range in size from 20 to 400 nm. These vesicles contain various components derived from their parent bacteria, including nucleic acids, proteins, lipids, and other molecules, which facilitate functions such as molecular transfer, metabolic regulation, bacterial interactions, biofilm formation, and immune modulation. BEVs participated in the pathophysiological process of periodontitis. Recently emerging evidence also showed that the contents of EVs in saliva and gingival crevicular fluid (miRNAs, mRNAs, and proteins) could be used as potential biomarkers for periodontitis. While most current research focuses on human-derived components, much less is known about BEVs. Therefore, this review introduces the formation mechanisms and components of BEVs related to periodontitis. Then, this review summarizes the current information about the mechanism, the diagnostic and theraputic value of periodontal pathogen-derived extracellular vesicles in the development of periodontitis. Furthermore, the future challenges of exploring the role of BEVs in periodontitis are also discussed.
Pseudomonas plecoglossicida infection induces neutrophil autophagy-driven NETosis in large yellow croaker Larimichthys crocea
Authors: Cao Jia-Feng , Chen Jiong
Published: December 2024

Neutrophil extracellular traps (NETs) are crucial for the immune defense of many organisms, serving as a potent mechanism for neutrophils to capture and eliminate extracellular pathogens. While NETosis and its antimicrobial mechanisms have been well studied in mammals, research on NETs formation in teleost fish remains limited. In this study, we used the large yellow croaker (Larimichthys crocea) as the study model to investigate NETosis and its role in pathogen defense. Our results showed that infection with Pseudomonas plecoglossicida could induce NETosis. To further explore the underlying mechanism, we performed transcriptome analysis and western blotting, which revealed that P. plecoglossicida triggers NETosis through activation of the autophagy pathway. Inhibition of autophagy significantly reduced NET production, highlighting its critical role in this process. Furthermore, our studies demonstrated that NETs exert a bacteriostatic effect, significantly suppressing the growth of P. plecoglossicida. Taken together, our findings reveal that autophagy regulates NETosis in large yellow croaker and underscore the essential role of NETs in bacterial defense, providing new insights into immune responses in teleost fish.
A systematic review on the use of food web models for addressing the social and economic consequences of fisheries policies and environmental change
Authors: Chakravorty Diya , Armelloni Enrico Nicola , de la Puente Santiago
Published: December 2024

Fisheries are complex systems. Food web models are increasingly being used to study the ecological consequences of fisheries policies and environmental change on such systems around the world. Nonetheless, these consequences extend well into the social, economic, cultural, and political domains of such systems. The main goal of this contribution is to characterize how food web models are being used to study the socioeconomic consequences of management actions and environmental change. We conducted a systematic literature review covering research published between January 2010 and July 2023. Only 47 papers (out of an initial pool of 506 publications) met our research criteria. Based on this, it is evident that the body of literature has been increasing slowly and at a constant rate – a condition not shared with other emerging research fields. Modeled systems were mostly marine (87%), covering the waters of 38 countries across 19 Large Marine Ecosystems; albeit mostly in the Global North. The ecological components of the reviewed models (e.g., functional groups) were represented at a much finer scale than their socioeconomic counterparts. Most models were developed using Ecopath with Ecosim (68%) or Atlantis (21%) modeling software suites. Four key research foci were identified across the selected literature. These shaped the methodological approaches followed, as well as the models’ capabilities, the simulation drivers, the way food webs were integrated with bioeconomic models, and the performance metrics they used and reported. Nonetheless, less than half captured social concerns, only one-third addressed trade-offs among management objectives, and only a handful explicitly addressed uncertainty. The implications of these findings are discussed in detail with respect to resource managers needs for ecosystem-based fisheries management and ecosystem-based management. Our collective understanding of the interlinkages between the biophysical and socioeconomic components of aquatic systems is still limited. We hope this review is seen as a call for action and that the food web modeling community rises to the challenge of embracing interdisciplinarity to bridge existing knowledge silos and improve our ability to model aquatic systems across all their domains and components.
Microplastics pollution in Indian marine environment: sources, effects and solutions
Authors: Anthony Josephine , Varalakshmi Sureka , Kumar Sekar Ashok , Thalavai Sivasankarasubbiah Kumar , Harikrishnan Thilagam , Rangamaran Vijaya Raghavan , Gopal Dharani , Ramalingam Kirubagaran
Published: December 2024

Microplastic pollution has emerged as a significant environmental challenge globally, posing threats to biodiversity, marine life, and human health. Studies indicate that marine organisms, from plankton to larger fish species, and ultimately humans are ingesting microplastics, leading to physiological harm such as inflammation, digestive blockages, tissue injury, hormonal imbalance, reproductive failure and biomagnification through the food chain. Therefore, there arises an urgent need and demand for implementing effective and sustainable remediation solutions. Though, various mitigation technologies are developed, less information is available on the advantages and disadvantages of the technological advancements. The present review highlights the significant information available on the sources, types, transport of microplastics along with the analytical methods to detect the microplastic pollutions. The global perspective of microplastic pollutions with respect to Indian Marine scenario was highlighted. The recent and advanced mitigation technologies and solutions in preventing, reducing and recycling these microplastic pollutions were also addressed. This review further underscores the need for comprehensive strategies to monitor, manage and mitigate microplastic pollution, including policy interventions, public awareness campaigns, and sustainable waste management practices. Addressing this issue is essential for preserving the health of India’s marine ecosystems and safeguarding the livelihoods of mankind.
Perspectives of old-age and dementia researchers on communication with policymakers and public research funding decision-makers: an international cross-sectional survey
Authors: Fusdahl Peter , Borda Miguel Germán , Baldera Jonathan Patricio , Aarsland Dag , Khachaturian Ara , Braut Geir Sverre
Published: December 2024

Introduction

Society commonly believes that research knowledge is complementary to public decision-making. This study aimed to understand the perspectives and implications of dementia researchers communicating with policymakers and public research decision-makers (public officials).

Methods

This study uses 24 questions from an anonymous, online survey, which was received by 392 members of nine European, Latin American, and United States medical researcher associations/networks in the fields of age-related neurological degeneration and dementia medicine. The data were analyzed via crosstab analysis, two group comparison analyses, and a logistic regression model.

Results

In total, 91 (23.2%) respondents completed the questionnaire. Eight independent variables were related to researchers’ research discipline, research remuneration, experience, authorship, H-index, and research grants. The statistically significant variables determining whether the respondents had contact with public officials were “Years of research experience” (p = 0.004), “Number of articles first-authored in the last 5 years” (p = 0.007), and “Average H-index in the last 5 years” (p = 0.048) [median (IQR)]; 47% of the surveyed researchers had been in contact with public officials in the last 12 months. The most frequently communicated topics were the importance of their own research to society (61%) and their own funding (60%); 87% (n = 79) of the researchers did not believe that public officials had a very good understanding of their dementia research.

Conclusion

Less than half (47%) of dementia researchers communicate with public officials, and they communicate mostly about the importance of their own research and funding their own research. Nine of 10 researchers do not believe that public officials understand their research well.
Disease burden and trends of lung cancer attributable to nickel among Chinese and global population: a cross-sectional study
Authors: Lu Huaye , Han Lei , Wu Peihong , Liu Xin , Jiang Qingtao
Published: December 2024

Background

Nickel is a well-established carcinogen, and China stands as a significant producer of nickel compounds. Nickel-associated lung cancer is increasingly acknowledged as a pressing public health concern. This study presents a comprehensive analysis at temporal, spatial, and population levels utilizing the most recent data from GBD 2019 to estimate the disease burden of nickel-associated lung cancer from 1990 to 2019, and make predictions to 2035.

Methods

We delineated data on nickel-associated lung cancer concerning mortality, disability-adjusted life years (DALY), and age-standardized rates (ASRs) over a 30-year period based on the global burden of disease (GBD) 2019. Joinpoint regression analysis was utilized to identify temporal changes and to estimate the annual percentage change (APC) as well as the average annual percentage change (AAPC) for each trend segment. The Nordpred model was employed to elaborate on ASRs trends from 1990 to 2019, along with projections for the subsequent 15 years.

Results

In both China and globally, the mortality rate from nickel-associated lung cancer and the associated DALYs have increased by 145.8, 77.8, 120.2, and 64.6%, respectively. ASRs within Chinese and global populations exhibit a pattern characterized by an initial increase followed by a decrease as age progresses, with males higher than females. The trend for DALY indicates an initial rise followed by a decline, peaking in the year 2027.

Conclusion

The age structure of nickel-associated lung cancer patients shows an aging trend, and the ASDR in the Chinese population indicates a potential upward trend when projecting the disease burden of nickel-associated lung cancer over the next 15 years. We should place greater emphasis on the implementation of preventive strategies and the enhancement of the quality of life for current sufferers.
Deciphering dengue: novel RNA barcoding segments for enhanced serotype-specific identification and global surveillance of dengue viruses
Authors: Jiang Shuai , Zhao Gaili , Ding Yunyun , Ye Shunxing , Li Zeqi , You Changqiao , Yin Yan , Guo Xinhong
Published: December 2024

Introduction

Dengue viruses (DENVs), the causative agents of dengue hemorrhagic fever and dengue shock syndrome, undergo genetic mutations that result in new strains and lead to ongoing global re-infections.

Objectives

To address the growing complexity of identifying and tracking biological samples, this study screened RNA barcode segments for the four DENV serotypes, ensuring high specificity and recall rates for DENV identification using segments.

Results

Through analyzing complete genome sequences of DENVs, we screened eight barcode segments for DENV, DENV-1, DENV-2, DENV-3, and DENV-4 identification. Comparing the screened barcode segments to sequences of known strains and determining the proportion of correctly or incorrectly identified nucleotides, these segments demonstrated an average recall rate at nucleotide level of 91.34% for four DENV serotypes, a specificity of 99.50% at species level within the Flaviviridae family, and a precision rate of 100% for identifying DENVs. For arboviruses, the nucleotide-level specificity was 63.58%. We designed and used the “Barcoding” software to streamline segment design, integrating automated sequence preprocessing, evaluation of barcode segments, and primer design, significantly reducing manual intervention and enhancing overall efficiency. We also established an online database called “Barcodes” for storing and preparing barcode segments.

Conclusion

This work established a standard framework for DENV identification and barcode segment selection, promising significant advancements in the real-time management and control of DENVs, thereby enhancing surveillance capabilities and facilitating targeted interventions in dengue outbreak-prone regions.
Clinical review and drug sensitivity test of Corynebacterium kroppenstedtii complex isolates in non-lactating patients with severe mastitis
Authors: Liang Zuxin , Zeng Zhujun , Liao Yanqiang , Cao Yaxin , Li Dongmei , Deng Ningbo , Lei Yeyan , Long Xuanhui , Shen Chenguang , Xu Rui
Published: December 2024

Background

Previous microbiological investigations have demonstrated a significant correlation between Corynebacterium kroppenstedtii complex (CKC) infection and mastitis. Recent studies have confirmed the existence of the CKC, with Corynebacterium parakroppenstedtii (C. parakroppenstedtii) identified as the primary infectious agent. Examining the incidence of CKC in cases of severe non-lactational mastitis, alongside the clinical characteristics of infected patients, as well as evaluating the drug sensitivity testing protocols for CKC, can provide a more robust foundation for the diagnosis and treatment of CKC infections.

Methods

Data regarding the diagnosis and treatment of non-nursing patients with severe mastitis who underwent surgical intervention were extracted from the hospital’s electronic medical record system. Additionally, drug susceptibility tests were conducted on 15 strains of CKC isolated from mammary abscesses as well as DSM 44385 model strains. The effects of β-NAD and Tween80 (TW80) on the antibiotic susceptibility test by AGAR dilution and micro broth dilution were analyzed.

Results

In this study, C. parakroppenstedtii accounted for 80% (12/15) of the isolates, while Corynebacterium pseudokroppenstedtii made up 13.3% (2/15), and Corynebacterium kroppenstedtii was identified in only 6.7% (1/15) of the cases. There were significant differences in age at first delivery (p < 0.001), prolactin (p < 0.001), CRP (p < 0.05), WBC (p < 0.05), and NEUT (p < 0.05) between CKC positive group and CKC negative group. In the AGAR dilution test, the addition of β-NAD only caused acceptable differences in penicillin G and ciprofloxacin but did not affect 12 antibiotics. There are 14 drugs with good coincidence rates (92.9%) in the micro broth dilution method and agar dilution method without the addition of β-NAD. The addition of 0.05% (v/v) TW80 resulted in all strains being resistant to penicillin G. Daptomycin is not suitable for the micro broth dilution method.

Conclusion

Elderly primiparas with high prolactin levels have a higher risk of CKC infection. The micro broth dilution method is not applicable for EUCAST drug susceptibility testing for CKC and there is no suitable drug susceptibility evaluation procedure for daptomycin against CKC.
Harnessing electroosmotic hybrid nanofluid dynamics in curved arteries: insights into biomedical flow enhancement
Authors: El Kot M. A. , Alsharif Abdullah Madhi , Abd Elmaboud Y. , Abdelsalam Sara I.
Published: December 2024

In this study, we investigated the dynamics of unsteady electroosmotic pulsatile flow involving a hybrid nanofluid within a curved artery, influenced by both stenosis and an embedded catheter. The hybrid nanofluid, a mixture of silver (Ag) and aluminum oxide (Al2O3) nanoparticles dispersed in blood, was modeled via the Carreau non-Newtonian framework to more accurately represent the intricate nature of blood flow. The electroosmotic forces introduced simulated the effect of an external electric field, while the catheter served as an additional structural constraint within the artery. To account for both the curvature of the vessel and the overlapping stenosis, we derived the governing equations for this model. Using numerical methods, particularly the finite-difference approach, we solved the nonlinear partial differential equations that govern the flow, temperature, and concentration distributions. Our findings suggest that the hybrid nanofluid demonstrates enhanced thermal and flow properties compared to standard fluids. The results showed significant influences from electroosmotic forces, curvature, and pulsatility on the velocity, temperature, and concentration profiles. Furthermore, an increase in the electroosmotic and Weissenberg parameters substantially accelerated fluid velocity by reducing viscous drag while improving mass transport. These results offer valuable insights into the behavior of blood flow in catheterized arteries and may inform future advancements in cardiovascular treatment technologies.
EEG-powered cerebral transformer for athletic performance
Authors: Sun Qikai
Published: December 2024

Introduction

In recent years, with advancements in wearable devices and biosignal analysis technologies, sports performance analysis has become an increasingly popular research field, particularly due to the growing demand for real-time monitoring of athletes' conditions in sports training and competitive events. Traditional methods of sports performance analysis typically rely on video data or sensor data for motion recognition. However, unimodal data often fails to fully capture the neural state of athletes, leading to limitations in accuracy and real-time performance when dealing with complex movement patterns. Moreover, these methods struggle with multimodal data fusion, making it difficult to fully leverage the deep information from electroencephalogram (EEG) signals.

Methods

To address these challenges, this paper proposes a "Cerebral Transformer" model based on EEG signals and video data. By employing an adaptive attention mechanism and cross-modal fusion, the model effectively combines EEG signals and video streams to achieve precise recognition and analysis of athletes' movements. The model's effectiveness was validated through experiments on four datasets: SEED, DEAP, eSports Sensors, and MODA. The results show that the proposed model outperforms existing mainstream methods in terms of accuracy, recall, and F1 score, while also demonstrating high computational efficiency.

Results and discussion

The significance of this study lies in providing a more comprehensive and efficient solution for sports performance analysis. Through cross-modal data fusion, it not only improves the accuracy of complex movement recognition but also provides technical support for monitoring athletes' neural states, offering important applications in sports training and medical rehabilitation.
Classification of ROI-based fMRI data in short-term memory tasks using discriminant analysis and neural networks
Authors: Fafrowicz Magdalena , Tutajewski Marcin , Sieradzki Igor , Ochab Jeremi K. , Ceglarek-Sroka Anna , Lewandowska Koryna , Marek Tadeusz , Sikora-Wachowicz Barbara , Podolak Igor T. , Oświęcimka Paweł
Published: December 2024

Understanding brain function relies on identifying spatiotemporal patterns in brain activity. In recent years, machine learning methods have been widely used to detect connections between regions of interest (ROIs) involved in cognitive functions, as measured by the fMRI technique. However, it's essential to match the type of learning method to the problem type, and extracting the information about the most important ROI connections might be challenging. In this contribution, we used machine learning techniques to classify tasks in a working memory experiment and identify the brain areas involved in processing information. We employed classical discriminators and neural networks (convolutional and residual) to differentiate between brain responses to distinct types of visual stimuli (visuospatial and verbal) and different phases of the experiment (information encoding and retrieval). The best performance was achieved by the LGBM classifier with 1-time point input data during memory retrieval and a convolutional neural network during the encoding phase. Additionally, we developed an algorithm that took into account feature correlations to estimate the most important brain regions for the model's accuracy. Our findings suggest that from the perspective of considered models, brain signals related to the resting state have a similar degree of complexity to those related to the encoding phase, which does not improve the model's accuracy. However, during the retrieval phase, the signals were easily distinguished from the resting state, indicating their different structure. The study identified brain regions that are crucial for processing information in working memory, as well as the differences in the dynamics of encoding and retrieval processes. Furthermore, our findings indicate spatiotemporal distinctions related to these processes. The analysis confirmed the importance of the basal ganglia in processing information during the retrieval phase. The presented results reveal the benefits of applying machine learning algorithms to investigate working memory dynamics.