bluuebunny/crossref_metadata_2025 huggingface dataset:
DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure
Authors: Tang Wenwu , Wang Zhixin , Yuan Xinzhu , Chen Liping , Guo Haiyang , Qi Zhirui , Zhang Ying , Xie Xisheng
Published: January 2025

Introduction

Heart failure (HF) has a very high prevalence in patients with maintenance hemodialysis (MHD). However, there is still a lack of effective and reliable HF diagnostic markers and therapeutic targets for patients with MHD.

Methods

In this study, we analyzed transcriptome profiles of 30 patients with MHD by high-throughput sequencing. Firstly, the differential genes between HF group and control group of patients with MHD were screened. Secondly, HF-related genes were screened by WGCNA, and finally the genes intersecting the two were selected as candidate genes. Machine learning was used to identify hub gene and construct a nomogram model, which was verified by ROC curve and RT-qPCR. In addition, we further explored potential mechanism and function of hub genes in HF of patients with MHD through GSEA, immune cell infiltration analysis, drug analysis and establishment of molecular regulatory network.

Results

Totally 23 candidate genes were screened out by overlapping 673 differentially expressed genes (DEGs) and 147 key module genes, of which four hub genes (DEPDC1B, CDCA2, APOBEC3B and TYMS) were obtained by two machine learning algorithms. Through GSEA analysis, it was found that the four genes were closely related to ribosome, cell cycle, ubiquitin-mediated proteolysis. We constructed a ceRNA regulatory network, and found that 4 hub genes (TYMS, CDCA2 and DEPDC1B) might be regulated by 4 miRNAs (hsa-miR-1297, hsa-miR-4465, hsa-miR-27a-3p, hsa-miR-129-5p) and 21 lncRNAs (such as HCP5, CAS5, MEG3, HCG18). 24 small molecule drugs were predicted based on TYMS through DrugBank website. Finally, qRT-PCR experiments showed that the expression trend of biomarkers was consistent with the results of transcriptome sequencing.

Discussion

Overall, our results reveal the molecular mechanism of HF in patients with MHD and provide insights into potential diagnostic markers and therapeutic targets.
Evolving perspectives on aortic stenosis: the increasing importance of evaluating the right ventricle before aortic valve intervention
Authors: Androshchuk Vitaliy , Chehab Omar , Wilcox Joshua , McDonaugh Benedict , Montarello Natalie , Rajani Ronak , Prendergast Bernard , Patterson Tiffany , Redwood Simon
Published: January 2025

Aortic stenosis (AS) was historically considered a disease of the left side of the heart, with the main pathophysiological impact being predominantly on the left ventricle (LV). However, progressive pressure overload in AS can initiate a cascade of extra-valvular myocardial remodeling that could also precipitate maladaptive alterations in the structure and function of the right ventricle (RV). The haemodynamic and clinical importance of these changes in patients with AS have been largely underappreciated in the past. Contemporary data indicates that RV dilatation or impairment identifies the AS patients who are at increased risk of adverse clinical outcomes after aortic valve replacement (AVR). It is now increasingly recognised that effective quantitative assessment of the RV plays a key role in delineating the late clinical stage of AS, which could improve patient risk stratification. Despite the increasing emphasis on the pathological significance of RV changes in AS, it remains to be established if earlier detection of these changes can improve the timing for intervention. This review will summarise the features of normal RV physiology and the mechanisms responsible for RV impairment in AS. In addition, we will discuss the multimodality approach to the comprehensive assessment of RV size, function and mechanics in AS patients. Finally, we will review the emerging evidence reinforcing the negative impact of RV dysfunction on clinical outcomes in AS patients treated with AVR.
Surface movement and crack development laws of super-long working faces in medium-depth coal seam mining
Authors: Hou Pengfei , Wang Shuangming , Feng Dong , Xie Xiaoshen , Hou Enke
Published: January 2025

Introduction

With the increased application of super-long working faces in coal mining, the surface movement and crack development laws of super-long working faces present an urgent problem to be studied and solved. This study aimed to determine the surface movement and crack development laws of super-long working faces when mining medium-depth buried coal seams.

Methods

The research area in Xiaobaodang No. 2 coal mine, China, was the adjacent working faces 01, 02 and 03, with inclination widths of 300 m and 450 m, respectively. The laws were determined by applying methods such as manual surface movement observation, GNSS automatic surface movement observation, surface crack observation, and crack morphology tracing.

Results

Compared to the working face with an inclination width of 300 m, the maximum subsidence, maximum horizontal movement value, and maximum subsidence coefficient of the super-long working face with an inclination width of 450 m increased by 15.31%, 4.56%, and 16.13%, respectively. Under the influence of mining the 02 working face, the maximum subsidence of the 01 working face increased by 15% and the surface subsidence patterns of the 01 and 02 working face inclination observation lines showed an asymmetric W shape.

Discussion

The widths of the cracks parallel to the open-off cut followed the dynamic development law of opening first, then closing or semi-closing. The widths of the cracks parallel to grooves followed the dynamic development law of opening first, then remaining open. The study results are important to protect mining buildings and the ecological environment.
Navigating the landscape of diversity leadership: Experiences of Finnish comprehensive school principals in the Helsinki area
Authors: Jantunen Anita , Sormunen Kati , Loukomies Anni , Kallioniemi Arto , Ahtiainen Raisa
Published: January 2025

This study explores the landscape of diversity leadership in Finnish comprehensive schools through the experiences and reflections of principals in the Helsinki area. Employing qualitative thematic analysis of principal interviews, we identified five key categories capturing the challenges and complexities principals navigate in leading diverse school communities: supporting structures for diversity, practical arrangements in school management, social encounters in schools, managemental issues concerning teachers and staff, and principals’ self-reflection. Principals emphasized the importance of establishing clear structures and practices to support diversity and inclusion, while also recognizing the need for flexibility and adaptability to meet the varied needs of diverse learners. They had to deal with practical challenges in managing certain aspect of diversity, constraints of municipal policies and resources, and the complexities of building positive relationships among diverse communities. Principals also engaged in critical self-reflection on their own identities, assumptions, and leadership practices in relation to diversity. Findings underscore the multifaceted nature of diversity leadership, encompassing structural, practical, social, professional, and personal dimensions. The study highlights the need for more systemic support, contextualized approaches, and professional development to build capacity for effective diversity leadership in increasingly diverse Finnish schools.
BOPPPS model implementation and students' performance: a systematic literature review
Authors: Liu Jiaying , Omar Siti Zobidah , Wang Yang , Xiang Yue
Published: January 2025

Applications of instructional models are among the key factors in enhancing student performance. While the BOPPPS model is widely implemented, a thorough and systematic evaluation of its impact on student performance remains absent. This systematic review synthesized findings from 19 studies to explore the relationship between the BOPPPS model and student performance. Using the PRISMA, Studies were analyzed for research characteristics, focusing on the use of BOPPPS model, learning subjects, student learning formats, and research theories to better analyze student performance. Specific student-related variables analyzed included academic performance, learning performance, skill tests performance, learning and cognitive ability performance, attendance performance, classroom performance, online performance, and other aspects. The results from the majority of the included studies consistently demonstrated a positive impact of the BOPPPS model on student performance across these diverse areas. To enhance understanding of the BOPPPS model's impact, future research could adopt longitudinal and mixed-method approaches, diversify and expand sample sizes, and explore cross-disciplinary and cross-cultural applications. Integrating new tools with the BOPPPS model is also recommended to further improve learner outcomes.
Teacher mobilizers: the power of leading learning and mobilizing teacher communities
Authors: Prasetia Indra , Pratiwi Sri Nurabdiah , Harfiani Rizka , Sugesti Tutik , Novia Siregar Astri
Published: January 2025

Mobilizer teachers are trained and professional teachers who play a strategic role in leading learning and improving the quality of education in schools. Although teacher mobilizers have become a reference point for positive changes in education in Indonesia, their presence is still considered by many to have not contributed to schools. However, there are various different assessments regarding the existence of mobilizer teachers. A number of groups believe that the effectiveness of mobilizer teachers is still low, while others believe that mobilizer teachers have the potential to successfully advance learning in schools. Apart from that, research on mobilizer teachers is still very minimal in Indonesia so it does not provide comprehensive knowledge about the contribution of mobilizer teachers in Indonesia. This research aims to explore the role of mobilizer teachers in leading learning and driving learning communities and their impact on student learning. A qualitative approach was used in this research and a total of 13 teachers were interviewed. The findings of this research indicate that mobilizer teacher leadership is instructional leadership that effectively leads learning and mobilizes the teacher community in the school and region and contributes to student learning.
Spatial-temporal characteristics and influencing factors of farmland carbon emissions in Guangdong Province, China
Authors: Chao Zihao , Zhu Ziyang , Li Yuchen
Published: January 2025

Agricultural carbon emissions account for 17% of total greenhouse gas emissions in China. To effectively address the eco-environment changes in farmland, which serves as the foundation of agricultural activities, it is essential to estimate regional farmland carbon emissions. This study calculated the farmland carbon emissions in Guangdong from 2011 to 2021 using the classical IPCC carbon emission calculation methodology. The decoupling characteristics betweem farmland carbon emissions and agricultural output values were analyzed utilizing a decoupling model, and the influencing factors were examined through the Logarithmic Mean Divisia Index (LMDI). The results indicate that: 1) Farmland carbon emissions in Guangdong decreased by 13.21% from 2011 to 2021, with pesticide reductions contributing the most to emission decreases. Chemical fertilizers were the largest contributor to farmland carbon emissions, accounting for approximately 61.78% of the total. 2) The spatial distribution of farmland carbon emissions followed the pattern of “Western Guangdong > Northern Guangdong > Eastern Guangdong > Pearl River Delta”. While emission intensity generally declined, regional disparities widened. 3) Most cities in Guangdong exhibited a strong decoupling relationship between farmland carbon emissions and agricultural output values, with decoupling coefficient ranging from −1.182 to −0.004. However, Heyuan and Shenzhen demonstrated a weak decoupling relationship. 4) The primary driver of increased farmland carbon emissions in Guangdong was the level of agricultural output, while improvements in agricultural production efficiency were the most significant inhibitory factor, followed by changes in the scale of agricultural labor force. This study offers policy recommendations to promote the reduction and sequestration of farmland carbon emissions in Guangdong.
Intein-mediated split SaCas9 for genome editing in plants
Authors: Hu Danling , Hu Lizhe , Lu Yaqiang , Dong Xiao , Cao Xingyu , Bai Shasha , Zhang Lingang , Li Dongming , Sun Yongwei
Published: January 2025

Virus-induced genome editing (VIGE) technologies have been developed to address the limitations to plant genome editing, which heavily relies on genetic transformation and regeneration. However, the application of VIGE in plants is hampered by the challenge posed by the size of the commonly used gene editing nucleases, Cas9 and Cas12a. To overcome this challenge, we employed intein-mediated protein splicing to divide the SaCas9 transcript into two segments (Split-v1) and three segments (Split-v3). The Split-v1 system demonstrated genome editing efficiencies in transgenic plants comparable to those achieved with wild-type SaCas9, with efficiencies ranging from 70.2% to 96.1%. Additionally, we constructed barley stripe mosaic virus (BSMV)-based vectors to co-express Split-v1 SaCas9 and gRNAs targeting LcHRC, LcGW2, and LcTB1 in sheepgrass (Leymus chinensis), a Gramineae forage species known for its recalcitrance to genetic transformation. Infected leaves of sheepgrass exhibited genome editing efficiencies ranging from 10.40% to 37.03%. These results demonstrate the potential of intein-mediated split nuclease systems to broaden the applicability of VIGE in challenging plant species.
Integration of single-cell transcriptomics and bulk transcriptomics to explore prognostic and immunotherapeutic characteristics of nucleotide metabolism in lung adenocarcinoma
Authors: Zhang Kai , Wang Luyao , Chen Huili , Deng Lili , Hu Mengling , Wang Ziqiang , Xie Yiluo , Lian Chaoqun , Wang Xiaojing , Zhang Jing
Published: January 2025

Background

Lung adenocarcinoma (LUAD) is a highly aggressive tumor with one of the highest morbidity and mortality rates in the world. Nucleotide metabolic processes are critical for cancer development, progression, and alteration of the tumor microenvironment. However, the effect of nucleotide metabolism on LUAD remains to be thoroughly investigated.

Methods

Transcriptomic and clinical data of LUAD were downloaded and organized from TCGA and GEO databases. Genes related to nucleotide metabolism were downloaded from the Msigdb database. Genes associated with LUAD prognosis were identified using univariate COX analysis, and a prognostic risk model was constructed using the machine learning combination of Lasso + Stepcox. The model’s predictive validity was evaluated using KM survival and timeROC curves. Based on the prognostic model, LUAD patients were classified into different nucleotide metabolism subtypes, and the differences between patients of different subtypes were explored in terms of genomic mutations, functional enrichment, tumor immune characteristics, and immunotherapy responses. Finally, the key gene SNRPA was screened, and a series of in vitro experiments were performed on LUAD cell lines to explore the role of SNRPA in LUAD.

Result

LUAD patients could be accurately categorized into subtypes based on the nucleotide metabolism-related prognostic risk score (NMBRS). There were significant differences in prognosis between patients of different subtypes, and the NMBRS showed high accuracy in predicting the prognosis of LUAD patients. In addition, patients of different subtypes showed significant differences in genomic mutation and functional enrichment and exhibited different anti-tumor immune profiles. Importantly, NMBRS can be used to predict the responsiveness of LUAD patients to immunotherapy. The results of in vitro cellular experiments indicate that SNRPA plays an important role in the development and progression of lung adenocarcinoma.

Conclusion

This study comprehensively reveals the prognostic value and clinical application of nucleotide metabolism in LUAD. A prognostic signature constructed based on genes related to nucleotide metabolism accurately predicted the prognosis of LUAD patients, and this signature can be used as a guide for LUAD immunotherapy.
Changes in health related quality of life in mothers with inflammatory joint disease from year 2000 to 2020 – a comparative cross-sectional study
Authors: Koksvik Hege Svean , Nilssen Ingrid , Jakobsen Bente , Bjørngaard Hilde , Wallenius Marianne , Grønning Kjersti
Published: January 2025

Objectives

More knowledge about health related quality of life (HRQoL) among mothers with inflammatory joint disease (IJD) is needed to understand the complex challenges for this group of patients. The overall aim of this study was to investigate changes in HRQoL among mothers with IJD from year 2000 to year 2020.

Methods

This study had a comparative cross-sectional design with two study groups 20 years apart, year 2000 (n = 77) and year 2020 (n = 197). Patients were identified from RevNatus, a Norwegian nationwide medical quality register (2020 cohort) and from a national centre for pregnancy and rheumatic disease (2000 cohort). Mothers with the diagnoses of rheumatoid arthritis, juvenile idiopathic arthritis, axial spondyloarthritis and psoriatic arthritis with children aged 0–6 were included. Data on HRQoL were self-reported and assessed by the RAND-36 (SF-36) questionnaire, along with data on educational status, number of children, months since last childbirth and eight questions on experienced motherhood limitations and experienced anxiety and distress for the children. Descriptive statistics were performed using the Mann-Whitney U-test, the Pearson chi-squared test and independent samples t-test. Multivariable linear regression were used to investigate changes and association between the RAND36 (SF-36) scores and the two study groups and possible confouders.

Results

The 2020 cohort had significantly higher scores on bodily pain (p < 0.001), physical function (p < 0.001), and role physical (p = 0.01) scales compared to the 2000 cohort, indicating better health. There were no significant differences between the two cohorts in the mental health (MH) (p = 0.81), vitality (p = 0.09), general health (p = 0.06), social function (p = 0.83), and role emotional (p = 0.93) scales. Compared to the calculated norm scores, the 2020 cohort had significantly lower scores on all scales (p < 0.01) except on the MH scale (p = 0.37).

Conclusion

Mothers with IJD were affected in most dimensions of RAND-36 (SF-36) both in year 2000 and year 2020. The findings emphasize the importance of understanding the intrusiveness of being a mother with IJD despite the improved medical treatment options over the last 20 years.
Col1A1 as a new decoder of clinical features and immune microenvironment in ovarian cancer
Authors: Xiao Xiao , Long Fangyi , Yu Shaolan , Wu Wengjuan , Nie Dayan , Ren Xiaoyan , Li Wen , Wang Xujuan , Yu Ling , Wang Pinghan , Wang Gang
Published: January 2025

Backgrounds

Collagen type I alpha 1 chain (COL1A1) is a key protein encoding fibrillar collagen, playing a crucial role in the tumor microenvironment (TME) due to its complex functions and close association with tumor invasiveness. This has made COL1A1 a focal point in cancer biology research. However, studies investigating the relationship between COL1A1 expression levels and clinical characteristics of ovarian cancer (OC) remain limited.

Methods

This study integrated resources from publicly available online databases and immunohistochemistry (IHC) techniques to analyze and validate COL1A1 expression in OC tissues, and evaluated its potential association with clinical features in OC patients. The prognostic value of COL1A1 was assessed using Kaplan-Meier (KM) survival curve analysis. The TIMER and TISIDB databases to explore the potential relationship between COL1A1 expression and immune microenvironment in OC tissues. The LinkedOmics and INPUT2 databases were used to analyze differential gene expression in OC, This was followed by enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) annotations to identify and predict potential signaling pathways associated with COL1A1.

Results

Our study demonstrated that COL1A1 expression was significantly elevated in OC tissues compared to normal ovarian tissues. This elevated expression was closely associated with tumor metastasis, poor prognosis, and advanced pathological stages in OC patients. Moreover, COL1A1 expression showed a significant correlation with immune cell infiltration and the expression of immune-related genes within the TME.Further analyses revealed that COL1A1 and its co-expressed genes were primarily enriched in key signaling pathways involved in OC invasion, metastasis, and angiogenesis, indicating its potential role in driving OC progression.

Conclusions

Our study found that upregulation of COL1A1 expression is significantly associated with lymph node metastasis of OC and can affect the immune microenvironment. Based on this, COL1A1 could serve as a promising biomarker for OC prognosis and provide a new perspective for the development of potential immunotherapies for patients with OC.
Bibliometric analysis of metformin as an immunomodulator (2013–2024)
Authors: Zhou Tongyi , Yu Yunfeng , Li Liu , Liu Xiu , Xiang Qin , Yu Rong
Published: January 2025

Background

Metformin, the frontline treatment for diabetes, has considerable potential as an immunomodulator; however, detailed bibliometric analyses on this subject are limited.

Methods

This study extracted 640 relevant articles from the Web of Science (WOS) Core Collection and conducted visual analyses using Microsoft Excel, VOSviewer, and CiteSpace.

Results

The findings showed that research on the immunomodulatory function of metformin has grown steadily since 2017, with China and the United States being the leading contributors. These studies have mostly been published in journals such as the International Journal of Molecular Sciences, Cancers, Frontiers in Immunology, and Scientific Reports. Keyword co-occurrence analysis highlighted metformin’s role as an immunomodulator, particularly in the context of the tumor immune microenvironment, immunosuppressive checkpoints, and metformin derivatives. Recent research has highlighted metformin’s application in aging, autoimmune diseases, COVID-19, and tuberculosis. Additionally, its role in regulating inflammation and gut microbiota is also being investigated.

Conclusion

Overall, the immunomodulatory effects of metformin were investigated in anti-tumor, antiviral, anti-aging, and autoimmune disease research. This highlights the scope of metformin use in these fields, while also significantly enhancing its clinical value as a repurposed drug.
Extracellular matrix re-normalization to improve cold tumor penetration by oncolytic viruses
Authors: Soko Geofrey F. , Kosgei Benson K. , Meena Stephene S. , Ng Ying Jing , Liang Huihui , Zhang Bing , Liu Qingjun , Xu Tielong , Hou Xinju , Han Ray P. S.
Published: January 2025

Immunologically inert or cold tumors pose a substantial challenge to the effectiveness of immunotherapy. The use of oncolytic viruses (OVs) to induce immunogenic cell death (ICD) in tumor cells is a well-established strategy for initiating the cancer immunity cycle (CIC). This process promotes the trafficking and infiltration of CD8+ T cells into tumors, thereby eliciting a tumor-specific immune response. Despite the potential of OVs for handling cold tumors, clinical outcomes have fallen short of expectations. To better understand the obstacles faced by oncolytic virus immunotherapy (OVI), we would like to revisit the OV issue. Growing evidence indicates that limited intratumoral penetration and inadequate intratumoral distribution of OVs are critical factors contributing to the suboptimal response to OVI. Aberrant expressions of matrix proteins by cancer-associated fibroblasts (CAFs) alter the mechanical properties of the tumor extracellular matrix (ECM). This results in increased ECM desmoplasia and elevated intratumoral interstitial fluid pressure (IFP), creating physical barriers that impede the penetration and dissemination of OVs within tumors. This review explores the latest advancements in strategies designed to improve the intratumoral penetration of OVs to facilitate the penetration of tumor-infiltrating lymphocytes (TILs) into cold tumors. Additionally, we investigated current clinical trials and challenges associated with translating these strategies into clinical practice to improve patient outcomes.
Characteristics and outcomes of patients with LAM receiving sirolimus in France based on real-life data
Authors: Cottin Vincent , Cases Antoine , Bourdin Virginie , Reynaud-Gaubert Martine , Hirschi Sandrine , Kerjouan Mallorie , Diesler Rémi , Chardès Brieux , Fiévez Stéphane , Assi Nada , Schmidt Aurélie , Denis Hélène , Wémeau-Stervinou Lidwine , Uzunhan Yurdagul
Published: January 2025

LAM is a rare multi-cystic lung disease for which treatment with sirolimus is indicated in cases of moderate or severe lung disease or declining lung function. The aim of this study was to describe patients treated with sirolimus for LAM and their outcomes. This retrospective observational study was based on data from the French national health insurance data system (SNDS). All adult women receiving sirolimus were identified in France between 2014 and 2021. In the absence of a specific LAM code in the system, an algorithm was developed to identify patients treated for possible LAM exclusion of other sirolimus indications (transplantation, graft-versus-host disease), or probable LAM (among possible LAM, patients hospitalized for pneumothorax, pleural drainage, pleurisy, ascites, chronic respiratory failure, lung transplantation, or angiomyolipoma). Over the entire study period, 638 patients were considered as treated with sirolimus for possible LAM, including 208 patients treated for “probable” LAM and 33 patients for TSC-LAM. Median [Q1; Q3] age at index date was 45.0 years [34.0; 58.5] for patients with probable LAM and 40.0 years [28.0; 56.0] for patients with TSC-LAM. Overall, the number of incident patients varied from 28 to 96 each year for possible LAM, from 11 to 33 each year for probable LAM and from 1 to 4 patients each year for TSC-LAM patients. In 2021, the incidence rate of patients treated with sirolimus for probable LAM in France was estimated at 0.9 per 1,000,000 French adult women and the prevalence rate at 6.3 per 1,000,000 French adult women. The 5-year survival after sirolimus initiation was 84% (95% CI: 76%; 90%) for probable LAM patients, and 77% (95% CI: 48%; 91%) for TSC-LAM patients. This study provides an updated epidemiological estimate of LAM patients treated with sirolimus in France between 2014 and 2021. Even though some of the results should be interpreted cautiously in the light of limitations related to the use of claims database, evolution of the disease and missing safety data, the information retrieved in this study is very valuable, as few studies provide real-world information on LAM populations.
Strongyloides stercoralis combined with concurrent multiple pathogens infections in an immunosuppressed patient: a case report
Authors: Fang Jingchun , Fang Huimin , Guo Penghao , Peng Yaqin , Chen Peisong
Published: January 2025

Background

Strongyloides stercoralis is an opportunistic pathogenic parasite. Most individuals with normal immune function may not exhibit significant symptoms, and the signs are atypical, which can easily lead to missed diagnoses and delayed treatment. People with underlying diseases and weakened immunity are prone to develop severe conditions after infection with Strongyloides stercoralis.

Case presentation

We report an immunocompromised patient in whom the pathogen was initially not detectable using traditional parasitic detection techniques. However, Strongyloides stercoralis was identified in both the alveolar lavage fluid and blood through metagenomic next-generation sequencing. Subsequently, Strongyloides stercoralis was detected in the alveolar lavage fluid after multiple rounds of testing using traditional microscopic examination techniques. Based on the mNGS results and other examination findings, the patient was diagnosed with Strongyloides stercoralis in combination with concurrent multiple pathogens infections. After the combined drug therapy of Meropenem, Vancomycin, and Albendazole, the patient’s condition was gradually brought under control.

Conclusion

This case demonstrates the advantage of integrating traditional detection methods with metagenomics next-generation sequencing technology in the etiological diagnosis of immunocompromised individuals. It is conducive to clarifying the etiological diagnosis of patients and thereby facilitating the timely initiation of corresponding treatments.
Artificial intelligence in healthcare: transforming patient safety with intelligent systems—A systematic review
Authors: De Micco Francesco , Di Palma Gianmarco , Ferorelli Davide , De Benedictis Anna , Tomassini Luca , Tambone Vittoradolfo , Cingolani Mariano , Scendoni Roberto
Published: January 2025

Introduction

Adverse events in hospitals significantly compromise patient safety and trust in healthcare systems, with medical errors being a leading cause of death globally. Despite efforts to reduce these errors, reporting remains low, and effective system changes are rare. This systematic review explores the potential of artificial intelligence (AI) in clinical risk management.

Methods

The systematic review was conducted using the PRISMA Statement 2020 guidelines to ensure a comprehensive and transparent approach. We utilized the online tool Rayyan for efficient screening and selection of relevant studies from three different online bibliographic.

Results

AI systems, including machine learning and natural language processing, show promise in detecting adverse events, predicting medication errors, assessing fall risks, and preventing pressure injuries. Studies reveal that AI can improve incident reporting accuracy, identify high-risk incidents, and automate classification processes. However, challenges such as socio-technical issues, implementation barriers, and the need for standardization persist.

Discussion

The review highlights the effectiveness of AI in various applications but underscores the necessity for further research to ensure safe and consistent integration into clinical practices. Future directions involve refining AI tools through continuous feedback and addressing regulatory standards to enhance patient safety and care quality.
A compound heterozygous ADAMTS13 mutation causes congenital thrombotic thrombocytopenic purpura: a case report
Authors: Huang Yezi , Zhou Lixia , Song Yuan , Zou Wanting , Tang Aiping , Tao Si , Tang Duozhuang
Published: January 2025

Congenital thrombotic thrombocytopenic purpura (cTTP) is a thrombotic microangiopathy (TMA) characterized by severe hereditary ADAMTS13 (a disintegrin and metalloproteinase with thrombospondin type 1 motifs 13) deficiency caused by ADAMTS13 mutations. This rare autosomal recessive genetic disorder is often misdiagnosed as immune thrombocytopenia (ITP) or hemolytic uremic syndrome (HUS). Here, we report a 21-year-old male cTTP patient with a compound heterozygous ADAMTS13 mutation. The patient was admitted for acute thrombocytopenia, with a 5-year history of chronic thrombocytopenia and 1 month of renal dysfunction. Initially diagnosed with ITP, he was treated with immunosuppressive therapy, including glucocorticoids and intravenous immunoglobulin, which provided temporary relief but failed to prevent recurrent thrombocytopenia. Ultimately, cTTP was confirmed by the low ADAMTS13 0% activity and two heterozygous variants (c.1335del and c.1045C > T) in the ADAMTS13 gene, and the patient received prophylactic fresh-frozen plasma (FFP) infusions every 2–3 weeks regularly. Interestingly, the patient also exhibited elevated sC5b-9 levels during the acute phase, necessitating differentiation from HUS. This report highlights a cTTP caused by a compound heterozygous ADAMTS13 mutation, although its pathogenesis requires further investigation. Given the atypical clinical manifestations of cTTP, it is necessary to conduct ADAMTS13 activity and even genetic testing in patients with recurrent thrombocytopenia and end-organ damage.
Improved protocol for metabolite extraction and identification of respiratory quinones in extremophilic Archaea grown on mineral materials
Authors: Gfellner Sebastian V. , Colas Cyril , Gabant Guillaume , Groninga Janina , Cadene Martine , Milojevic Tetyana
Published: January 2025

We investigated the metabolome of the iron- and sulfur-oxidizing, extremely thermoacidophilic archaeon Metallosphaera sedula grown on mineral pyrite (FeS2). The extraction of organic materials from these microorganisms is a major challenge because of the tight contact and interaction between cells and mineral materials. Therefore, we applied an improved protocol to break the microbial cells and separate their organic constituents from the mineral surface, to extract lipophilic compounds through liquid–liquid extraction, and performed metabolomics analyses using MALDI-TOF MS and UHPLC-UHR-Q/TOF. Using this approach, we identified several molecules involved in central carbon metabolism and in the modified Entner-Doudoroff pathway found in Archaea, sulfur metabolism-related compounds, and molecules involved in the adaptation of M. sedula to extreme environments, such as metal tolerance and acid resistance. Furthermore, we identified molecules involved in microbial interactions, i.e., cell surface interactions through biofilm formation and cell–cell interactions through quorum sensing, which relies on messenger molecules for microbial communication. Moreover, we successfully extracted and identified different saturated thiophene-bearing quinones using software for advanced compound identification (MetaboScape). These quinones are respiratory chain electron carriers in M. sedula, with biomarker potential for life detection in extreme environmental conditions.
Microbial communities in the phyllosphere and endosphere of Norway spruce under attack by Heterobasidion
Authors: Meng Wen-jing , Wen Zi-lan , Kasanen Risto , Sun Hui , Asiegbu Fred O.
Published: January 2025

Heterobasidion annosum species complex has been regarded as the most destructive disease agent of conifer trees in boreal forests. Tree microbiome can regulate the plant–pathogen interactions by influencing both host resistance and pathogen virulence. Such information would help to improve the future health of forests and explore strategies to enhance ecosystem stability. In this study, using next-generation sequencing technology, we investigated the microbial community in different tree regions (needles, upper stem, and lower stem) of Norway spruce with and without wood decay symptoms. The primary purpose was to uncover signature characteristic microbiome harbored by asymptomatic trees compared to diseased trees. Additionally, the study was to explore the inter-kingdom and intra-kingdom interactions in microbiome (bacteria and fungi) of symptomatic versus asymptomatic trees. The results showed that in upper stem, species richness (Chao1) of fungi and bacteria were both higher in asymptomatic trees than symptomatic trees (P < 0.05). Compared to symptomatic trees, asymptomatic trees harbored a higher abundance of Actinobacteriota, bacterial genera of Methylocella, Conexibacter, Jatrophihabitans, and fungal genera of Mollisia. Fungal communities from the same anatomic region differed between the symptomatic and asymptomatic trees. Bacterial communities from the two stem regions were also distinct between the symptomatic and asymptomatic trees. The symptomatic trees possessed a less stable microbial network with more positive correlations compared to the asymptomatic trees. In the lower stem, at intra-kingdom level, the distribution of correlation numbers was more even in the bacterial network compared to the fungal network. In conclusion, the Heterobasidion attack decreased the microbial community species richness and shifted the community structure and functional structure to varying degrees. The microbial network was enlarged and became more unstable at both inter-kingdom and intra-kingdom level due to the Heterobasidion infection.
Revolutionizing diagnosis of pulmonary Mycobacterium tuberculosis based on CT: a systematic review of imaging analysis through deep learning
Authors: Zhang Fei , Han Hui , Li Minglin , Tian Tian , Zhang Guilei , Yang Zhenrong , Guo Feng , Li Maomao , Wang Yuting , Wang Jiahe , Liu Ying
Published: January 2025

Introduction

The mortality rate associated with Mycobacterium tuberculosis (MTB) has seen a significant rise in regions heavily affected by the disease over the past few decades. The traditional methods for diagnosing and differentiating tuberculosis (TB) remain thorny issues, particularly in areas with a high TB epidemic and inadequate resources. Processing numerous images can be time-consuming and tedious. Therefore, there is a need for automatic segmentation and classification technologies based on lung computed tomography (CT) scans to expedite and enhance the diagnosis of TB, enabling the rapid and secure identification of the condition. Deep learning (DL) offers a promising solution for automatically segmenting and classifying lung CT scans, expediting and enhancing TB diagnosis.

Methods

This review evaluates the diagnostic accuracy of DL modalities for diagnosing pulmonary tuberculosis (PTB) after searching the PubMed and Web of Science databases using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines.

Results

Seven articles were found and included in the review. While DL has been widely used and achieved great success in CT-based PTB diagnosis, there are still challenges to be addressed and opportunities to be explored, including data scarcity, model generalization, interpretability, and ethical concerns. Addressing these challenges requires data augmentation, interpretable models, moral frameworks, and clinical validation.

Conclusion

Further research should focus on developing robust and generalizable DL models, enhancing model interpretability, establishing ethical guidelines, and conducting clinical validation studies. DL holds great promise for transforming PTB diagnosis and improving patient outcomes.
An artificial transcription factor that activates potent interferon-γ expression in human Jurkat T Cells
Authors: King Ashley , Noblitt Davis , Sherron Olivia , Kjerfve Clara , Pless Lydia , Truex Nicholas L.
Published: January 2025

Interferon (IFN)-γ is a central regulator of cell-mediated immunity in human health and disease, but reduced expression of the target receptors impairs signaling activity and leads to immunotherapy resistance. Although intracellular expression of IFN-γ restores the signaling and downstream functions, we lack the tools to activate the IFNG gene instead of cell surface receptors. This paper introduces the design and characterization of an artificial transcription factor (ATF) protein that recognizes the IFNG gene with six zinc finger domains, which are dovetailed to a VP64 signaling domain that promotes gene transcription and translation. Biological studies with human Jurkat T cells reveal that the ATF amplifies IFNG gene transcription and translation, and also stimulates gene transcription for multiple class I and II HLA alleles and interferon-stimulated genes (ISGs). Biophysical characterization showed the recombinant ATF protein recognizes the human IFNG gene with nanomolar affinity (KD = 5.27 ± 0.3 nM), adopts a protein secondary structure associated with the ββα-fold of zinc finger domains, and is resistant to thermal denaturation. These studies demonstrate that transcriptional targeting of cytokine genes, rather than surface receptors, activates cytokine expression and shows significant potential for directing immune function.
Deciphering olfactory receptor binding mechanisms: a structural and dynamic perspective on olfactory receptors
Authors: Wang Jingtao , Zhang Qidong , Fan Wu , Shi Qingzhao , Mao Jian , Xie Jianping , Chai Guobi , Zhang Chenglei
Published: January 2025

Olfactory receptors, classified as G-protein coupled receptors (GPCRs), have been a subject of scientific inquiry since the early 1950s. Historically, investigations into the sensory mechanisms of olfactory receptors were often confined to behavioral characteristics in model organisms or the expression of related proteins and genes. However, with the development of cryo-electron microscopy techniques, it has gradually become possible to decipher the specific structures of olfactory receptors in insects and humans. This has provided new insights into the binding mechanisms between odor molecules and olfactory receptors. Furthermore, due to the rapid advancements in related fields such as computer simulations, the prediction and exploration of odor molecule binding to olfactory receptors have been progressively achieved through molecular dynamics simulations. Through this comprehensive review, we aim to provide a thorough analysis of research related to the binding mechanisms between odor molecules and olfactory receptors from the perspectives of structural biology and molecular dynamics simulations. Finally, we will provide an outlook on the future of research in the field of olfactory receptor sensory mechanisms.
Correlations among lymphocyte count, white matter hyperintensity and brain atrophy in patients with ischemic stroke
Authors: Liu Chenchen , Shi Dai , Ni Xiaoqiong , You Shoujiang , Wu Xiaofen , Zhuang Sheng , Cai Wu , Xu Liang
Published: January 2025

Background

White matter hyperintensity (WMH) and brain atrophy, as imaging marker of cerebral small-vessel diseases (CSVD), have a high prevalence and strong prognostic value in stroke. We aimed to explore the association between lymphocyte count, a maker of inflammation, and WMH and brain atrophy in patients with acute ischemic stroke (AIS).

Methods

A total of 727 AIS patients with lymphocyte count and brain magnetic resonance imaging data were enrolled. Participants were divided into four groups according to the quartiles of baseline lymphocyte counts. WMH is frequently divided into periventricular hyperintensity (PVH) and deep white matter hyperintensity (DWMH). WMH was defined as Fazekas scale score ≥ 3; PVH was defined as periventricular Fazekas scale ≥2; DWMH was defined as deep Fazekas scale ≥2. Brain atrophy was defined as global cortical atrophy score ≥ 1. Multivariable logistic regression models were used to assess the association between lymphocyte count and WMH and brain atrophy.

Results

Among 727 AIS, 517 (71.1%), 442 (60.8%), 459 (63.1%), 583 (80.2%) had WMH, PVH, DWMH and brain atrophy, respectively. After adjustment for potential covariates, the highest quartiles of lymphocyte counts were significantly associated with lower risk of WMH (adjusted odds ratio [aOR] 0.57, 95% confidence intervals [CI] 0.32–0.99), PVH (aOR 0.52, 95% CI 0.31–0.87), DWMH (aOR 0.53 95% CI 0.32–0.90) as well as brain atrophy (aOR 0.46, 95% CI 0.23–0.92) compared with the lowest quartiles of lymphocyte counts, respectively. Furthermore, a notable inverse association was observed between continuous lymphocyte counts and WMH, PVH, DWMH, and brain atrophy. Additionally, we found that the inverse association between baseline lymphocyte count and WMH was significant only in individuals with mild stroke.

Conclusion

In patients with AIS, there was an independent and inverse association between the baseline lymphocyte count and both WMH and brain atrophy.
Multimodal consumer choice prediction using EEG signals and eye tracking
Authors: Usman Syed Muhammad , Khalid Shehzad , Tanveer Aimen , Imran Ali Shariq , Zubair Muhammad
Published: January 2025

Marketing plays a vital role in the success of a business, driving customer engagement, brand recognition, and revenue growth. Neuromarketing adds depth to this by employing insights into consumer behavior through brain activity and emotional responses to create more effective marketing strategies. Electroencephalogram (EEG) has typically been utilized by researchers for neuromarketing, whereas Eye Tracking (ET) has remained unexplored. To address this gap, we propose a novel multimodal approach to predict consumer choices by integrating EEG and ET data. Noise from EEG signals is mitigated using a bandpass filter, Artifact Subspace Reconstruction (ASR), and Fast Orthogonal Regression for Classification and Estimation (FORCE). Class imbalance is handled by employing the Synthetic Minority Over-sampling Technique (SMOTE). Handcrafted features, including statistical and wavelet features, and automated features from Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM), have been extracted and concatenated to generate a feature space representation. For ET data, preprocessing involved interpolation, gaze plots, and SMOTE, followed by feature extraction using LeNet-5 and handcrafted features like fixations and saccades. Multimodal feature space representation was generated by performing feature-level fusion for EEG and ET, which was later fed into a meta-learner-based ensemble classifier with three base classifiers, including Random Forest, Extended Gradient Boosting, and Gradient Boosting, and Random Forest as the meta-classifier, to perform classification between buy vs. not buy. The performance of the proposed approach is evaluated using a variety of performance metrics, including accuracy, precision, recall, and F1 score. Our model demonstrated superior performance compared to competitors by achieving 84.01% accuracy in predicting consumer choices and 83% precision in identifying positive consumer preferences.
Classification of female MDD patients with and without suicidal ideation using resting-state functional magnetic resonance imaging and machine learning
Authors: Fattahi Morteza , Esmaeil-Zadeh Milad , Soltanian-Zadeh Hamid , Rostami Reza , Mansouri Jamil , Hossein-Zadeh Gholam-Ali
Published: January 2025

Spontaneous blood oxygen level-dependent signals can be indirectly recorded in different brain regions with functional magnetic resonance imaging. In this study resting-state functional magnetic resonance imaging was used to measure the differences in connectivity and activation seen in major depressive disorder (MDD) patients with and without suicidal ideation and the control group. For our investigation, a brain atlas containing 116 regions of interest was used. We also used four voxel-based connectivity models, including degree centrality, the fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity, and voxel-mirrored Homotopic Connectivity. Feature selection was conducted using a sequential backward floating selection approach along with a Random Forest Classifier and Elastic Net. While all four models yield significant results, fALFF demonstrated higher accuracy rates in classifying the three groups. Further analysis revealed three features that demonstrated statistically significant differences between these three, resulting in a 90.00% accuracy rate. Prominent features identified from our analysis, with suicide ideation as the key variable, included the Superior frontal gyrus (dorsolateral and orbital parts), the median cingulate, and the paracingulate gyri. These areas are associated with the Central Executive Control Network (ECN), the Default Mode Network, and the ECN, respectively. Comparing the results of MDD patients with suicidal ideation to those without suicidal ideations suggests dysfunctions in decision-making ability, in MDD females suffering from suicidal tendencies. This may be related to a lack of inhibition or emotion regulation capability, which contributes to suicidal ideations.