bluuebunny/crossref_metadata_2025 huggingface dataset:
Potential effects of Polar Silk Road on the global foreland evolution of China’s coastal container ports
Authors: Peng Yan , Du Debin , Zhang Xinfang , Wang Xue
Published: September 2024

The white paper on China’s Arctic Policy, which proposed the joint construction of the Polar Silk Road (PSR), was officially published in January 2018. As a short and economically feasible sea route, the PSR will inevitably affect the carrier’s market choice behaviour, thereby affecting the foreland network structure and foreland pattern of China’s coastal container ports (CCCP). Grasping the evolution trend of CCCP foreland under the PSR will help predict the development trend of the port and shipping market in advance and enable measures to be taken to adapt to the changing market environment. This paper constructs the port foreland network evolution (PFNE) model and presents a complex network delineation method of port foreland to simulate the effects of PSR on CCCP foreland evolution in different scenarios. Results show that the PSR’s addition to the CCCP foreland network will improve shipping connectivity, increase the connection between long-distance ports, reshape the clustering groups, promote the orderliness of the network and help the development of small and medium-sized ports. China’s global maritime transport pattern will change, which is mainly reflected in the enhanced shipping links between CCCP and Asia, Europe and Africa, while the importance of the Americas for CCCP weaken. PSR has a more obvious role in promoting the establishment of maritime links between China’s northern ports and the world ports. In the discussion, we propose the development policy of CCCP under the PSR.
Propagation and dissipation of typhoon-induced surface waves along the Pearl River Estuary
Authors: Liang Mingen , Zhu Suijie , Qiu Heyong , Jia Liangwen
Published: September 2024

The propagation and dissipation of typhoon-induced surface waves are vital to morphological evolution and related engineering within coastal and estuarine regions. An observation system was operated during Typhoon Higos, and TELEMAC–TOMAWAC numerical modeling was performed for Typhoons Hagupit, Hato, and Higos along the central coast of Guangdong and the Pearl River Estuary in China to explore variations in wave propagation and dissipation during typhoons. The results showed that wind waves were dominant before typhoon landfall, and the intense wind waves dissipated rapidly during typhoon decay, while they could stay longer within the estuarine regions. Landward wave propagation had a tendency to convert from being convergence-dominated to being dissipation-dominated with the morphological change and tended to converge at the mouth-bar region. Within the estuarine regions, waves dissipated more rapidly at the prismatic estuary than at the bell-shaped bays due to the limited width and rapid contraction of the outlet. Moreover, the track and scale of typhoons had critical effects on the generated wave field, and they dominated the intensity, propagation, and dissipation of the overall wave field. Specifically, typhoons with broader scales and longer moving tracks within the coastal regions of Guangdong Province enhanced the wind–wave interaction and induced a stronger and wider wave field, despite that their typhoon intensities were comparable (i.e., Hagupit vs. Hato). Furthermore, waves generated by compact and regular cyclone structures dissipated more strongly along the moving track of typhoons (i.e., Hato and Higos). Except for typhoons directly attacking the Pearl River Estuary, waves within the estuarine regions tended to dissipate/converge when located on the right/left side of the moving track of typhoons.
Chronic kidney diseases and inflammation research: a bibliometric analysis
Authors: Wang Heyong , Chen Yang , Gou Yujuan , Yang Dianxing , Xiong Lanyue
Published: September 2024

Background

Chronic kidney diseases (CKD) is a severe public health problem. This study aimed to explore the field of inflammation-related research in CKD from a bibliometric perspective.

Methods

Relevant literature published between 2004 and 2023 were searched from the Web of Science database. The bibliometric analysis were performed to summarize countries, institutions, authors, journals and keywords using VOSviewer and CiteSpace.

Results

A total of 9,287 publications on CKD and inflammation were included. Publications were mainly from the United States, China, Italy, Germany, and Japan. The findings revealed that the United States had the highest number of publications in this field, followed by China. There is strong collaboration between the two countries. The most productive institutions included the University of California system and the US Department of Veterans Affairs. Research hotspots primarily focused on inflammation mechanisms, biomarkers, and interventions.

Conclusion

This study revealed the basic knowledge structure and provided a comprehensive insight into the research field of CKD and inflammation through bibliometric methods. Future studies should focus on early diagnosis, prevention, and treatment strategies of CKD, and explore more inflammation associated biomarkers and therapeutic targets for CKD.
The application of metagenomics, radiomics and machine learning for diagnosis of sepsis
Authors: Hu Xiefei , Zhi Shenshen , Wu Wenyan , Tao Yang , Zhang Yuanyuan , Li Lijuan , Li Xun , Pan Liyan , Fan Haiping , Li Wei
Published: September 2024

Introduction

Sepsis poses a serious threat to individual life and health. Early and accessible diagnosis and targeted treatment are crucial. This study aims to explore the relationship between microbes, metabolic pathways, and blood test indicators in sepsis patients and develop a machine learning model for clinical diagnosis.

Methods

Blood samples from sepsis patients were sequenced. α-diversity and β-diversity analyses were performed to compare the microbial diversity between the sepsis group and the normal group. Correlation analysis was conducted on microbes, metabolic pathways, and blood test indicators. In addition, a model was developed based on medical records and radiomic features using machine learning algorithms.

Results

The results of α-diversity and β-diversity analyses showed that the microbial diversity of sepsis group was significantly higher than that of normal group (p < 0.05). The top 10 microbial abundances in the sepsis and normal groups were Vitis vinifera, Mycobacterium canettii, Solanum pennellii, Ralstonia insidiosa, Ananas comosus, Moraxella osloensis, Escherichia coli, Staphylococcus hominis, Camelina sativa, and Cutibacterium acnes. The enriched metabolic pathways mainly included Protein families: genetic information processing, Translation, Protein families: signaling and cellular processes, and Unclassified: genetic information processing. The correlation analysis revealed a significant positive correlation (p < 0.05) between IL-6 and Membrane transport. Metabolism of other amino acids showed a significant positive correlation (p < 0.05) with Cutibacterium acnes, Ralstonia insidiosa, Moraxella osloensis, and Staphylococcus hominis. Ananas comosus showed a significant positive correlation (p < 0.05) with Poorly characterized and Unclassified: metabolism. Blood test-related indicators showed a significant negative correlation (p < 0.05) with microorganisms. Logistic regression (LR) was used as the optimal model in six machine learning models based on medical records and radiomic features. The nomogram, calibration curves, and AUC values demonstrated that LR performed best for prediction.

Discussion

This study provides insights into the relationship between microbes, metabolic pathways, and blood test indicators in sepsis. The developed machine learning model shows potential for aiding in clinical diagnosis. However, further research is needed to validate and improve the model.
Prevalence of musculoskeletal pain among undergraduate students
Authors: Kandasamy Geetha , Almanasef Mona , Almeleebia Tahani , Orayj Khalid , Shorog Eman , Alshahrani Asma M. , Prabahar Kousalya , Veeramani Vinoth Prabhu , Amirthalingam Palanisamy , Alqifari Saleh F. , Alrashidi Fayez , Aldurum Muteb , Almutiri Faiz , Alzaidi Adel , Almutairi Fahad
Published: September 2024

Introduction

Musculoskeletal disorders (MSDs) are rapidly rising in Saudi Arabia, reaching levels similar to those in the Western world. Hence, we aimed to assess the prevalence of neck, shoulder, and lower back pains (musculoskeletal pain, MSP) among students at King Khalid University in Abha, Saudi Arabia.

Methods

This cross-sectional study was conducted at King Khalid University in Abha, Saudi Arabia, from March 2023 to August 2023. Inclusion criteria were: university students aged 18 years and older of both sexes who agreed to participate in the study. The modified Nordic questionnaire was used, which comprised three parts.

Results

Out of 536 respondents, 337 were women and 199 were men. The average body mass index (BMI) of the study population was 25.3 ± 4.01. In total, 223 (41.60%) had a history of MSDs. Only 232 (43.28%) of the population did regular exercise. According to multiple logistic regression analysis, factors associated with MSDs are mobile device use (with both hands) with a large neck tilt below the horizon line position (OR = 2.276, CI 1.178–4.397, p = 0.014), family history of trauma (OR = 5.450, 95% CI 3.371–8.811, p = 0.000), family history of MSDs (OR = 4.241, 95% CI 2.296–7.835, p = 0.000), coffee consumption (OR = 1.967, CI 1.281–3.020, p = 0.002), and time spent on electronic devices: 1–3 h (OR = 0.252, 95% CI 0.124–0.511, p = 0.0001), 4–6 h (OR = 0.455, 95% CI 0.237–0.873, p = 0.018), and 6–9 h (OR = 0.348, 95% CI 0.184–0.660, p = 0.001).

Conclusion

The present study concludes that MSP among university students is high. A history of trauma, a family history of MSDs, the hand and neck position when using electronic devices, the amount of time spent using them, and regular exercise are risk factors that are strongly associated with MSP. There is strong evidence to suggest that increasing physical activity plays a significant role in enhancing the functionality of the musculoskeletal (MSK) system and alleviating pain. It is recommended that universities implement educational programs to raise awareness and health screenings about the impact of device usage on MSK health and the benefits of regular exercise.
A bibliometric analysis of respiratory mechanics research related to acute respiratory distress syndrome from 1985 to 2023
Authors: Zhou Yi-Min , Tian Xiuli , Wang Yu-Mei , Wang Shuya , Yang Yan-Lin , Zhou Jian-Xin , Zhang Linlin
Published: September 2024

Background

Acute respiratory distress syndrome (ARDS) is a severe condition characterized by lung stiffness and compromised gas exchange, often requiring mechanical ventilation for treatment. In addition to its clinical significance, understanding the publication trends and research patterns in respiratory mechanics related to ARDS can provide insights into the evolution of this field from a bibliometric perspective, aiding in strategic planning and resource allocation for future research endeavors.

Objective

This study aimed to explore the trends and identify the hotspots in respiratory mechanics research related to ARDS.

Methods

All relevant studies on respiratory mechanics of ARDS published between 1985 and 2023 were retrieved from the Web of Science Core Collection (WoSCC), and the retrieval strategy was topic search “TS = respiratory mechanics OR lung mechanics AND TS = ARDS OR acute respiratory distress syndrome.” Annual trends, citation patterns, and contributions from countries, institutions, authors, and journals were analyzed using Bibliometrix Biblioshiny. Networks and overlay of authors, institutions, countries, journals, co-citations, and keywords were analyzed and visualized using VOSviewer.

Results

Our analysis included 1,248 articles published between 1985 and 2023, revealing fluctuations in publication output over time. The United States emerged as the leading contributor, with Critical Care Medicine being the most prominent journal. Key research themes included mechanical ventilation, acute lung injury, and protective ventilation strategies. International collaboration was evident, facilitating knowledge exchange and interdisciplinary cooperation.

Conclusion

Our study sheds light on the evolving landscape of respiratory mechanics research in ARDS. International collaboration is pivotal in advancing the field, while researchers increasingly focus on personalized approaches to address the complexities of ARDS respiratory mechanics.
Exploration of the link between COVID-19 and gastric cancer from the perspective of bioinformatics and systems biology
Authors: Ma Xiao , Huang Tengda , Li Xiaoquan , Zhou Xinyi , Pan Hongyuan , Du Ao , Zeng Yong , Yuan Kefei , Wang Zhen
Published: September 2024

Background

Coronavirus disease 2019 (COVID-19), an infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has caused a global pandemic. Gastric cancer (GC) poses a great threat to people’s health, which is a high-risk factor for COVID-19. Previous studies have found some associations between GC and COVID-19, whereas the underlying molecular mechanisms are not well understood.

Methods

We employed bioinformatics and systems biology to explore these links between GC and COVID-19. Gene expression profiles of COVID-19 (GSE196822) and GC (GSE179252) were obtained from the Gene Expression Omnibus (GEO) database. After identifying the shared differentially expressed genes (DEGs) for GC and COVID-19, functional annotation, protein-protein interaction (PPI) network, hub genes, transcriptional regulatory networks and candidate drugs were analyzed.

Results

We identified 209 shared DEGs between COVID-19 and GC. Functional analyses highlighted immune-related pathways as key players in both diseases. Ten hub genes (CDK1, KIF20A, TPX2, UBE2C, HJURP, CENPA, PLK1, MKI67, IFI6, IFIT2) were identified. The transcription factor/gene and miRNA/gene interaction networks identified 38 transcription factors (TFs) and 234 miRNAs. More importantly, we identified ten potential therapeutic agents, including ciclopirox, resveratrol, etoposide, methotrexate, trifluridine, enterolactone, troglitazone, calcitriol, dasatinib and deferoxamine, some of which have been reported to improve and treat GC and COVID-19.

Conclusion

This research offer valuable insights into the molecular interplay between COVID-19 and GC, potentially guiding future therapeutic strategies.
Enhancing healthcare recommendation: transfer learning in deep convolutional neural networks for Alzheimer disease detection
Authors: Pandey Purushottam Kumar , Pruthi Jyoti , Alzahrani Saeed , Verma Anshul , Zohra Benazeer
Published: September 2024

Neurodegenerative disorders such as Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI) significantly impact brain function and cognition. Advanced neuroimaging techniques, particularly Magnetic Resonance Imaging (MRI), play a crucial role in diagnosing these conditions by detecting structural abnormalities. This study leverages the ADNI and OASIS datasets, renowned for their extensive MRI data, to develop effective models for detecting AD and MCI. The research conducted three sets of tests, comparing multiple groups: multi-class classification (AD vs. Cognitively Normal (CN) vs. MCI), binary classification (AD vs. CN, and MCI vs. CN), to evaluate the performance of models trained on ADNI and OASIS datasets. Key preprocessing techniques such as Gaussian filtering, contrast enhancement, and resizing were applied to both datasets. Additionally, skull stripping using U-Net was utilized to extract features by removing the skull. Several prominent deep learning architectures including DenseNet-201, EfficientNet-B0, ResNet-50, ResNet-101, and ResNet-152 were investigated to identify subtle patterns associated with AD and MCI. Transfer learning techniques were employed to enhance model performance, leveraging pre-trained datasets for improved Alzheimer’s MCI detection. ResNet-101 exhibited superior performance compared to other models, achieving 98.21% accuracy on the ADNI dataset and 97.45% accuracy on the OASIS dataset in multi-class classification tasks encompassing AD, CN, and MCI. It also performed well in binary classification tasks distinguishing AD from CN. ResNet-152 excelled particularly in binary classification between MCI and CN on the OASIS dataset. These findings underscore the utility of deep learning models in accurately identifying and distinguishing neurodegenerative diseases, showcasing their potential for enhancing clinical diagnosis and treatment monitoring.
The metaverse in nuclear medicine: transformative applications, challenges, and future directions
Authors: Tang Yufu , Liang Hongying , Yang Xin , Xue Xiangming , Zhan Jingming
Published: September 2024

The metaverse, a rapidly evolving virtual reality space, holds immense potential to revolutionize nuclear medicine by enhancing education, training, diagnostics, and therapeutics. This review explores the transformative applications of the metaverse in nuclear medicine, where immersive virtual learning environments, simulation-based training, artificial intelligence (AI)-powered decision support systems integrated into interactive three-dimensional (3D) visualizations, and personalized dosimetry using realistic patient-specific virtual models are seamlessly incorporated into the metaverse ecosystem, creating a synergistic platform for healthcare professionals and patients alike. However, the responsible and sustainable adoption of the metaverse in nuclear medicine requires a multidisciplinary approach to address challenges related to standardization, accessibility, data security, and ethical concerns. The formation of cross-disciplinary consortia, increased research and development (R&D) investment, and the strengthening of data governance and cybersecurity measures are crucial steps in ensuring the safe and effective integration of the metaverse in healthcare. As the metaverse continues to evolve, researchers, practitioners, and policymakers must collaborate and explore its potential, navigate the challenges, and shape a future where technology and medicine seamlessly integrate to enhance patient care and outcomes in nuclear medicine. Further research is needed to fully understand the implications of the metaverse in clinical practice, education, and research, as well as to develop evidence-based guidelines for its responsible implementation. By embracing responsible innovation and collaboration, the nuclear medicine community can harness the power of the metaverse to transform and improve patient care.
Diagnostic values of BALF metagenomic next-generation sequencing, BALF real-time PCR and serum BDG for Pneumocystis jirovecii pneumonia in HIV-infected patients
Authors: Chen Qianhui , Chen Xiaoping , Mo Pingzheng , Chen Liangjun , Du Qian , Hu Wenjia , Jiang Qunqun , Zhang Zhongwei , Zhang Yongxi , Guo Qinglian , Xiong Yong , Deng Liping
Published: September 2024

Introduction

This study aimed to assess the diagnostic values of bronchoalveolar lavage fluid (BALF) real-time polymerase chain reaction (PCR) and BALF metagenomic next-generation sequencing (mNGS) for Pneumocystis jirovecii pneumonia (PJP) in patients infected with human immunodeficiency virus (HIV).

Methods

A total of 99 HIV-infected PJP patients and 61 HIV-infected patients diagnosed with non-PJP pneumonia between March 2019 and December 2022 were enrolled. P. jirovecii and multiple other co-pathogens detected in BALF by mNGS were analyzed. The clinical final diagnosis was employed as a benchmark. We compared the diagnostic performance of mNGS in PJP with serum BDG and BALF real-time PCR. The mixed infections detected by mNGS and modifications of antimicrobial treatment were also analyzed.

Results

The sensitivity of mNGS test of BALF samples reached 85.86%, which was significantly higher than serum BDG (39.39%, P < 0.001). The sensitivity of BALF P. jirovecii PCR (84.85%) was similar with mNGS (P > 0.05). The specificity of mNGS (100%) was also same as PCR (100.0%), and superior to serum BDG (88.52%, P < 0.001). Besides, mNGS performs remarkably well in identifying co-pathogens of PJP patients infected with HIV. In addition to P. jirovecii, 82 cases (82.83%) of other co-pathogens were identified based on mNGS. Moreover, thirty-four patients (34.34%) increased therapeutic dose of trimethoprim-sulfamethoxazole (TMP-SMZ) based on BALF P. jirovecii PCR. Based on the mNGS results, initial antimicrobial treatment was modified in 86.87% (86/99) of PJP patients.

Conclusion

BALF mNGS and real-time PCR are two powerful techniques for rapid diagnosis of PJP with high specificity and sensitivity. Moreover, the benefit of mNGS is that it may identify other organisms besides PJP and it may benefit proper and prompt treatment.
Nature based solutions for removal of steroid estrogens in wastewater
Authors: Liyanage Sureka , Lay Mark , Glasgow Graeme , Tanner Chris , Craggs Rupert , Northcott Grant
Published: September 2024

Estrogens are a growing problem in wastewater discharges because they are continuously entering the environment and are biologically active at extremely low concentrations. Their effects on wildlife were first identified several decades before, but the environmental limits and the remedial measures are still not completely elucidated. Most conventional treatment processes were not designed with sufficiently long retention times to effectively remove estrogens. Nature-based wastewater treatment technologies such as treatment wetlands (TW) and high-rate algal ponds (HRAP) are economically feasible alternatives for decentralized wastewater treatment and have promise for removing steroid hormones including estrogens. For small communities with populations below 50,000, the overall cost of TWs and HRAPs is considerably lower than that of advanced decentralized treatment technologies such as activated sludge systems (AS) and sequencing batch reactors (SBR). This results from the simplicity of design, use of less materials in construction, lower energy use, operation and maintenance costs, and operation by non-skilled personnel. The nature-based technologies show high removal (>80%) for both natural and synthetic estrogens. Estrogen removal in TWs can be enhanced using alternative media such as palm mulch, biochar, and construction wastes such as bricks, instead of traditional substrates such as sand and gravel. While TWs are effective in estrogen removal, they have the disadvantage of requiring a relatively large footprint, but this can be reduced by using intensified multilayer wetland filters (IMWF). Using filamentous algae in HRAP (high-rate filamentous algal pond; HRFAP) is an emerging technology for wastewater treatment. The algae supply oxygen via photosynthesis and assimilate nutrients into readily harvestable filamentous algal biomass. Diurnal fluctuations in oxygen supply and pH in these systems provide conditions conducive to the breakdown of estrogens and a wide range of other emerging contaminants. The performance of these nature-based systems varies with seasonal changes in environmental conditions (particularly temperature and solar irradiation), however a greater understanding of operating conditions such as loading rate, hydraulic retention time (HRT), pond/bed depth, dissolved oxygen (DO) concentration and pH, which influence the removal mechanisms (biodegradation, sorption and photodegradation) enable TWs and HRAPs to be successfully used for removing estrogens.
Unveiling genetic links between gut microbiota and asthma: a Mendelian randomization
Authors: Zheng XuWen , Chen MaoBing , Zhuang Yi , Zhao Liang , Qian YongJun , Shi ChengCheng
Published: September 2024

Background

Multiple studies suggest a potential connection between the gut microbiome and asthma. Our objective is to use advanced genetic and metagenomic techniques to elucidate the causal relationships and underlying mechanisms between gut microbiota and asthma.

Methods

The study utilized comprehensive Linkage Disequilibrium Score Regression (LDSC) and Mendelian randomization (MR) analyses to examine the relationship between 119 gut microbiota genera and asthma, using publicly accessible genome-wide association studies (GWAS). The meta-analysis synthesized summary effect estimates obtained from LDSC, forward MR, and reverse MR. The MiBioGen collaboration, involving 18,340 individuals, identified genetic variations associated with gut bacteria. Asthma data were collected from the UK Biobank, FinnGen, and GERA, encompassing a total of 82,060 cases and 641,049 controls.

Results

LDSC analysis revealed significant negative genetic correlations between asthma and RuminococcaceaeUCG004 (Rg = −0.55, p = 7.66 × 10−5) and Subdoligranulum (Rg = −0.35, p = 3.61 × 10−4). Forward MR analysis suggested associations between Butyricicoccus (OR = 0.92, p = 0.01), Turicibacter (OR = 0.95, p = 0.025), Butyrivibrio (OR = 0.98, p = 0.047), and reduced asthma risk. Conversely, Coprococcus2 (OR = 1.10, p = 0.035) and Roseburia (OR = 1.07, p = 0.039) were associated with increased risk. Reverse MR analysis indicated significant associations between genetically predicted asthma and Eubacteriumxylanophilumgroup (Beta = −0.08, p = 9.25 × 10−7), LachnospiraceaeNK4A136group (Beta = −0.05, p = 1.26 × 10−4), and Eisenbergiella (Beta = 0.06, p = 0.015, Rg_P = 0.043).

Conclusion

The findings underscore significant genetic correlations and causal relationships between specific gut microbiota and asthma. These insights highlight the potential of gut microbiota as both markers and modulators of asthma risk, offering new avenues for targeted therapeutic strategies.
Isolation, identification, and mechanism analysis of plant growth-promoting rhizobacteria in tobacco
Authors: Jiang Chuandong , Peng Fuyu , Zhang Li , Zhang Yuqin , Wang Jie , Li Junmin , Cui Binghui , Cao Changdai , Wang Chengqiang , Qin Yunlei , Wang Ran , Zhao Zongpeng , Jiang Jiazhu , Yang Mingfeng , Sun Mingming , Yang Long , Zhang Qiang
Published: September 2024

Plant growth, crop yield, and pest and disease control are enhanced by PGPR (Plant growth promoting rhizobacteria), which are beneficial microorganisms found in a close symbiosis with plant roots. Phytohormones are secreted, nutrient uptake is improved, and soil properties along with the microbiological environment are regulated by these microorganisms, making them a significant focus in agricultural research. In this study, the efficient PGPR strain T1 was isolated and screened from tobacco inter-root soil, and identified and confirmed by ITS sequencing technology. Tobacco growth indicators and soil property changes were observed and recorded through potting experiments. The activities of key enzymes (e.g., sucrase, catalase, urease) in soil were further determined. High-throughput sequencing technology was utilized to sequence the soil microbial community, and combined with macro-genomics analysis, the effects of T1 strain on soil microbial diversity and metabolic pathways were explored. Following the application of T1, significant improvements were observed in the height, leaf length, and width of tobacco plants. Furthermore, the physical and chemical properties of the soil were notably enhanced, including a 26.26% increase in phosphorus availability. Additionally, the activities of key soil enzymes such as sucrase, catalase, and urease were significantly increased, indicating improved soil health and fertility. Comprehensive joint microbiomics and macrogenomics analyses revealed a substantial rise in the populations of beneficial soil microorganisms and an enhancement in metabolic pathways, including amino acid metabolism, synthesis, and production of secondary metabolites. These increase in beneficial microorganisms and the enhancement of their metabolic functions are crucial for plant growth and soil fertility. This study provides valuable references for the development of innovative microbial fertilizers and offers programs for the sustainable development of modern agriculture.
Variations in microbial community compositions and processes imposed under contrast geochemical contexts in Sicilian mud volcanoes, Italy
Authors: Chen Jhen-Nien , Chiu Yi-Ping , Tu Tzu-Hsuan , Italiano Francesco , Wang Pei-Ling , Lin Li-Hung
Published: September 2024

Terrestrial mud volcanoes represent surface features of channels for subsurface methane transport and, therefore, constitute an important source of methane emission from natural environments. How microbial processes regulate methane emissions in terrestrial mud volcanoes has yet to be fully addressed. This study demonstrated the geochemical characteristics and microbial communities of four mud volcano and seep sites in two geological settings of Sicily, Italy. At sites within the accretionary wedge that exhibited higher methane and sulfate concentrations, the communities were dominated by members capable of catalyzing methane and sulfate metabolisms and organic degradation. In particular, both anaerobic and aerobic methanotrophs were abundant and their abundance distribution coincided with the geochemical transition. In contrast, the sites near Mount Etna were characterized by high fluid salinity, CO2, and low methane and sulfate concentrations, with communities consisting of halophilic organic degraders and sulfur metabolizers, along with a minor presence of aerobic methanotrophs. Substantial variations in community composition and geochemistry across spatial and vertical redox gradients suggest that physicochemical contexts imposed by the geology, fluid path, and source characteristics play a vital role in shaping community composition and cycling of methane, sulfur and organic carbon in Sicily mud volcanoes.
Photobiomodulation regulates astrocyte activity and ameliorates scopolamine-induced cognitive behavioral decline
Authors: Park Ji On , Hong Namgue , Lee Min Young , Ahn Jin-Chul
Published: September 2024

Introduction

The pathophysiological mechanism of Alzheimer’s disease (AD) has not been clearly identified, and effective treatment methods have not yet been established. Scopolamine causes cholinergic dysfunction in the brain, including the accumulation of amyloid-beta plaques, thereby increasing oxidative stress and neuroinflammation, mimicking AD. Glial cells such as astrocytes have recently been identified as possible biomarkers for AD. Photobiomodulation (PBM) elicits a beneficial biological response in cells and tissues. PBM effects on the central nervous system (CNS) have been widely researched, including effects on astrocyte activity.

Methods

In the present study, PBM was performed using light at the near-infrared wavelength of 825 nm. The Morris water maze and Y-maze tests were employed to evaluate cognitive function decline in a scopolamine-induced memory dysfunction model and its improvement with PBM. In addition, alteration of the mitogen-activated protein kinase (MAPK) pathway and immunofluorescence expression levels of active astrocytes were observed in the hippocampus, which is one of the areas affected by AD, to evaluate the mechanism of action of PBM.

Results

A reduction in the neuronal cell death in the hippocampus caused by scopolamine was observed with PBM. Moreover, alteration of a MAPK pathway-related marker and changes in glial fibrillary acidic protein (an active astrocyte marker) expression were observed in the PBM-treated group. Finally, significant correlations between functional and histological results were found, validating the results.

Discussion

These findings indicate the possibility of behavioral and histological improvement due to PBM in scopolamine-induced CNS alteration, which mimics AD. This improvement could be related to neuroinflammatory modulation and altered astrocyte activity.
Determinants of infarct progression and perfusion core growth in transferred LVO patients from remote regions
Authors: Valente Michael , Bivard Andrew , Yan Bernard , Davis Stephen M. , Campbell Bruce C. V. , Mitchell Peter J. , Ma Henry , Parsons Mark W.
Published: September 2024

Introduction

Repeat imaging when regional and remote stroke patients arrive at a comprehensive stroke center (CSC) can delay endovascular thrombectomy (EVT). We examined which clinical and imaging parameters predict infarct progression and perfusion core growth during transport.

Methods

We included patients recruited from 2017 to 2023 in a prospective database who were transferred from remote sites with large vessel occlusion, had CT perfusion imaging at the primary stroke center (PSC), and had repeat CT on arrival at the CSC demonstrating persistent occlusion. The key imaging characteristics were perfusion core change (rCBF < 30%) and ASPECTS change. Multiple and ordinal logistic regression analyses were used to assess the relationship between background clinical and imaging variables and the CT-perfusion core and ASPECTS on arrival. DEFUSE 3 criteria (ASPECTS ≥ 6, perfusion core < 70 mL) were used to define “favorable imaging.”

Results

In 90 patients with CT perfusion at both PSC and CSC and persistent occlusion, the median time from onset to PSC presentation was 279 min (IQR 143–702). The median time from PSC presentation to CSC arrival was 243.5 min (IQR 186–335), and the median distance traveled was 186.5 km (IQR 101–258). Lower baseline ASPECTS (per point) was associated with a 7 mL increase (95%CI 2–11 mL) in perfusion core between scans (p = 0.004). The time from onset, the time between PSC and CSC, and the distance traveled were not significantly associated with either ASPECTS or perfusion core growth during transport. In total, 11 out of 78 patients (14%) had deterioration of initially favorable imaging profiles during transport.

Conclusion

Perfusion core growth during transport was uncommon and most strongly associated with lower ASPECTS at the PSC. Initially, favorable PSC imaging May predict whether repeat imaging is necessary at the CSC.
Effect of glymphatic system function on cognitive function in patients with chronic kidney disease
Authors: Ko Junghae , Park Bong Soo , Heo Chang Min , Yi Jiyae , Lee Dong Ah , Park Kang Min
Published: September 2024

Objectives

Studies have recently shown an alteration of the structural connectivity and a dysfunctional glymphatic system in patients with chronic kidney disease (CKD). In this study, we aimed to investigate the effects of the structural connectivity and glymphatic system on the cognitive function of patients with CKD.

Methods

We prospectively enrolled patients with CKD and healthy controls. The CKD group was divided into two regarding their cognitive function. All patients received brain magnetic resonance imaging, including diffusion tensor imaging (DTI). We calculated the measures of structural connectivity and diffusion tensor image analysis along the perivascular space (DTI-ALPS) index, a neuroimaging marker of the glymphatic system function, and compared the indices between groups.

Results

The mean clustering coefficient, local efficiency, and small-worldness index in patients with CKD were lower than those in healthy controls (0.125 ± 0.056 vs. 0.167 ± 0.082, p = 0.008; 1.191 ± 0.183 vs. 1.525 ± 0.651, p = 0.002; 0.090 ± 0.043 vs. 0.143 ± 0.102, p = 0.003; respectively). The DTI-ALPS index was lower in patients with CKD than in healthy controls (1.436 vs. 1.632, p < 0.001). Additionally, the DTI-ALPS index differed significantly between CKD patients with and without cognitive impairment. Notably, this index was lower in patients with CKD and cognitive impairment than in patients without cognitive impairment (1.338 vs. 1.494, p = 0.031). However, there were no differences of the structural connectivity between CKD patients with and without cognitive impairment.

Conclusion

We found lower DTI-ALPS index in patients with CKD, which could be related with glymphatic system dysfunction. Moreover, those with cognitive impairment in the CKD group had a lower index than those without, indicating a link between the glymphatic system function and cognitive function.
Entorhinal cortex–hippocampal circuit connectivity in health and disease
Authors: Hernández-Frausto Melissa , Vivar Carmen
Published: September 2024

The entorhinal cortex (EC) and hippocampal (HC) connectivity is the main source of episodic memory formation and consolidation. The entorhinal–hippocampal (EC-HC) connection is classified as canonically glutamatergic and, more recently, has been characterized as a non-canonical GABAergic connection. Recent evidence shows that both EC and HC receive inputs from dopaminergic, cholinergic, and noradrenergic projections that modulate the mnemonic processes linked to the encoding and consolidation of memories. In the present review, we address the latest findings on the EC-HC connectivity and the role of neuromodulations during the mnemonic mechanisms of encoding and consolidation of memories and highlight the value of the cross-species approach to unravel the underlying cellular mechanisms known. Furthermore, we discuss how EC-HC connectivity early neurodegeneration may contribute to the dysfunction of episodic memories observed in aging and Alzheimer’s disease (AD). Finally, we described how exercise may be a fundamental tool to prevent or decrease neurodegeneration.
Artificial intelligence role in advancement of human brain connectome studies
Authors: Shekouh Dorsa , Sadat Kaboli Helia , Ghaffarzadeh-Esfahani Mohammadreza , Khayamdar Mohammadmahdi , Hamedani Zeinab , Oraee-Yazdani Saeed , Zali Alireza , Amanzadeh Elnaz
Published: September 2024

Neurons are interactive cells that connect via ions to develop electromagnetic fields in the brain. This structure functions directly in the brain. Connectome is the data obtained from neuronal connections. Since neural circuits change in the brain in various diseases, studying connectome sheds light on the clinical changes in special diseases. The ability to explore this data and its relation to the disorders leads us to find new therapeutic methods. Artificial intelligence (AI) is a collection of powerful algorithms used for finding the relationship between input data and the outcome. AI is used for extraction of valuable features from connectome data and in turn uses them for development of prognostic and diagnostic models in neurological diseases. Studying the changes of brain circuits in neurodegenerative diseases and behavioral disorders makes it possible to provide early diagnosis and development of efficient treatment strategies. Considering the difficulties in studying brain diseases, the use of connectome data is one of the beneficial methods for improvement of knowledge of this organ. In the present study, we provide a systematic review on the studies published using connectome data and AI for studying various diseases and we focus on the strength and weaknesses of studies aiming to provide a viewpoint for the future studies. Throughout, AI is very useful for development of diagnostic and prognostic tools using neuroimaging data, while bias in data collection and decay in addition to using small datasets restricts applications of AI-based tools using connectome data which should be covered in the future studies.
Beta tACS of varying intensities differentially affect resting-state and movement-related M1-M1 connectivity
Authors: Wansbrough Kym , Marinovic Welber , Fujiyama Hakuei , Vallence Ann-Maree
Published: September 2024

Due to the interconnected nature of the brain, changes in one region are likely to affect other structurally and functionally connected regions. Emerging evidence indicates that single-site transcranial alternating current stimulation (tACS) can modulate functional connectivity between stimulated and interconnected unstimulated brain regions. However, our understanding of the network response to tACS is incomplete. Here, we investigated the effect of beta tACS of different intensities on phase-based connectivity between the left and right primary motor cortices in 21 healthy young adults (13 female; mean age 24.30 ± 4.84 years). Participants underwent four sessions of 20 min of 20 Hz tACS of varying intensities (sham, 0.5 mA, 1.0 mA, or 1.5 mA) applied to the left primary motor cortex at rest. We recorded resting-state and event-related electroencephalography (EEG) before and after tACS, analyzing changes in sensorimotor beta (13–30 Hz) imaginary coherence (ImCoh), an index of functional connectivity. Event-related EEG captured movement-related beta activity as participants performed self-paced button presses using their right index finger. For resting-state connectivity, we observed intensity-dependent changes in beta ImCoh: sham and 0.5 mA stimulation resulted in an increase in beta ImCoh, while 1.0 mA and 1.5 mA stimulation decreased beta ImCoh. For event-related connectivity, 1.5 mA stimulation decreased broadband ImCoh (4–90 Hz) during movement execution. None of the other stimulation intensities significantly modulated event-related ImCoh during movement preparation, execution, or termination. Interestingly, changes in ImCoh during movement preparation following 1.0 mA and 1.5 mA stimulation were significantly associated with participants’ pre-tACS peak beta frequency, suggesting that the alignment of stimulation frequency and peak beta frequency affected the extent of neuromodulation. Collectively, these results suggest that beta tACS applied to a single site influences connectivity within the motor network in a manner that depends on the intensity and frequency of stimulation. These findings have significant implications for both research and clinical applications.
Causal relationship between genetic-predicted uric acid and cervical cancer risk: evidence for nutritional intervention on cervical cancer prevention
Authors: Cao Chunge , Cai Dajun , Liu Hao , Zhang Xia , Cai Lina , Sun Caiping , Wang Huifang , Zhao Hu , Yue Chaoyan
Published: September 2024

Introduction

The relationship between serum uric acid (SUA) and cervical cancer is inconclusive. This study aims to investigate the causal relationship between SUA levels and cervical cancer incidence, and to evaluate the potential role of nutritional interventions in cervical cancer prevention.

Methods

We conducted a two-sample bidirectional Mendelian randomization (MR) analysis using genetic instruments from publicly available genome-wide association studies (GWASs) of individuals of predominantly European ancestry. Methods such as inversevariance weighted, weighted-median, weighted model, and MR-Egger were applied. Sensitivity tests, including leave-one-out, MR-PRESSO, and Cochran’s Q test, assessed heterogeneity and pleiotropy.

Results

Our findings revealed that a high SUA concentration significantly increased the risk of malignant cervical cancer: a 1 mg/mL increase in SUA was associated with a 71% higher risk (OR = 1.71, 95% CI = 1.10–2.67; p = 0.018). Stratification by histological type showed a significant causal effect on cervical adenocarcinoma risk (OR = 2.56, 95% CI = 1.14–5.73; p = 0.023). However, no clear evidence was found for a causal effect of cervical cancer on SUA levels.

Conclusion

This study identified a causal relationship between elevated SUA levels and the risk of malignant cervical cancer, particularly cervical adenocarcinoma. These findings provide novel insights into the mechanisms of cervical carcinogenesis and suggest that managing SUA levels could be a potential strategy for cervical cancer prevention through dietary management.
Consumption of edible oil blended with flax, coconut, sunflower, and olive oil can significantly improve the negative health consequences of high-fat/high-cholesterol diet in Sprague Dawley rats
Authors: Rabail Roshina , Altemimi Ammar B. , Maerescu Cristina Maria , Socol Claudia Terezia , Criste Florin Leontin , Khalid Abdur Rauf , Mahwish  , Hussain Shahzad , Liu Zhi-Wei , Aadil Rana Muhammad
Published: September 2024

Background

Increasing cardiac, hepatic, and metabolic diseases have raised the need to modify our contemporary lifestyles toward balancing and diversifying the nutrients in our daily diet. Objective: Dietary fats should be modified to healthier versions by blending different vegetable oils. Therefore, in this study, an oil blend with health-protective and promoting fatty acid combinations was investigated to bring down the progression of cardiac and other metabolic diseases.

Methodology

A bio-efficacy trial was performed to investigate the therapeutic potential of an oil blend in 30 hyperlipidemic rats. Five rats were allocated to each group (coconut, flaxseed, olive, sunflower, and blended oil) for 42 days and were compared with the initial values of hyperlipidemic rats. Methodological investigations were performed for the body weight, naso-anal length, various obesity indices, visceral fat accumulation, blood and serum, cardiovascular risk indices, and echocardiograph.

Results

Blended oil consumption indicated significant reductions of 53.12% in body fat content (3.98 ± 0.96), 6.82% in Lee index (289.60 ± 8.27), 16.84% in BMI (0.15 ± 0.003), 57.37% in total cholesterol (52.00 ± 9.03), 68.57% in triacylglycerides (99.00 ± 9.19), 61.16% in atherogenic index (0.88 ± 0.12), and 58.72% in coronary risk index (2.88 ± 0.12), when compared with the initial values.

Conclusion

Blended oil consumption has significantly reduced various obesity indices, improved lipid profile, and provided significant protection against cardiovascular risk indices. Moreover, the results of blended oil indicated significant health protective ameliorations in electrocardiographs. Its regular consumption could help to reduce the onset of obesity and metabolic diseases.
Malignant granular cell tumor of chest wall: a case report
Authors: Flauto Fabiano , Servetto Alberto , Bianco Roberto , Formisano Luigi
Published: September 2024

Background

Granular Cell Tumors (GCTs), also known as Abrikossoff tumors, are rare neoplasms that typically originate from Schwann cells. These tumors most commonly occur in the head and neck region, particularly the tongue. While GCTs are generally benign, less than 2% of cases exhibit aggressive biological features such as rapid growth, high recurrence rates, and metastasis. In this report, we present a rare case of a Malignant Granular Cell Tumor (MGCT) of the chest wall, which posed significant challenges in both characterization and management.

Case Presentation

A fifty-year-old man underwent an ultrasound examination for a nodular mass on his right chest wall. The ultrasound revealed a firm, hard mass measuring 2 cm x 2 cm with an uncertain diagnosis. A fine-needle aspiration biopsy (FNAB) guided by ultrasound was performed, resulting in a diagnosis of Abrikossoff tumor. The patient subsequently underwent radical excision of the mass, which confirmed the initial diagnosis. Nine months after surgery, a new mass with similar characteristics was detected during a physical examination. The patient underwent a second surgery, but this time the histopathological examination was negative for neoplastic cells. However, another mass appeared at the same site as the previous surgical excision. A CT scan and MRI of the right chest wall confirmed the presence of a 2 cm x 2 cm nodular mass. The patient then underwent a deeper excision. Histomorphological and immunohistochemical assessments confirmed the recurrence of MGCT.

Conclusion

This case highlights the malignant potential of GCTs. The numerous local recurrences necessitated three surgeries and additional procedures. The aggressive nature of this pathology underscores the complexity of managing these tumors, which are poorly understood and lack proven post-operative strategies for controlling local and distant disease.