bluuebunny/crossref_metadata_2025_split huggingface dataset:
Causality investigation among gut microbiota, immune cells, and prostate diseases: a Mendelian randomization study
Authors: Yue Shao-Yu , Li Wei-Yi , Xu Shun , Bai Xiao-Xin , Xu Wen-Long , Wang Xu , Ding He-Kang , Chen Jia , Du He-Xi , Xu Ling-Fan , Niu Di , Liang Chao-Zhao 
Published: September 2024

BackgroundThe gut microbiota has been demonstrated to have a significant role in the pathogenesis and progression of a variety of diseases, including prostate cancer, prostatitis, and benign prostatic hyperplasia. Potential links between prostate diseases, immune cells and the gut microbiota have not been adequately investigated.MethodsMR studies were conducted to estimate the effects of instrumental variables obtained from genome-wide association studies (GWASs) of 196 gut microbial taxa and 731 immune cells on the risk of prostate diseases. The primary method for analysing causal relationships was inverse variance-weighted (IVW) analysis, and the MR results were validated through various sensitivity analyses.ResultsMR analysis revealed that 28 gut microbiome taxa and 75 immune cell types were significantly associated with prostate diseases. Furthermore, reverse MR analysis did not support a causal relationship between prostate diseases and the intestinal microbiota or immune cells. Finally, the results of the mediation analysis indicated that Secreting Treg % CD4 Treg, Activated &amp; resting Treg % CD4 Treg, and Mo MDSC AC inhibited the role of the class Mollicutes in reducing the risk of PCa. In prostatitis, CD8+ T cells on EM CD8br hinder the increased risk associated with the genus Eubacterium nodatum group. Interestingly, in BPH, CD28- CD25++CD8br AC and CD16-CD56 on HLA DR+ NK promoted the role of the genus Dorea in reducing the risk of BPH.ConclusionThis study highlights the complex relationships among the gut microbiota, immune cells and prostate diseases. The involvement of the gut microbiota in regulating immune cells to impact prostate diseases could provide novel methods and concepts for its therapy and management.
Effect of intestinal microbiota transplantation on chronic hepatitis B virus infection associated liver disease
Authors: Deng Lisi , Guo Xiaozhen , Chen Jiehua , Li Baoyi , Liu Na , Xia Jinyu , Ou Mengdang , Hong Zhongsi 
Published: September 2024

BackgroundResearch on the effects of intestinal microbiota transplantation (IMT) on chronic HBV infection (CHB) progression associated liver disease (HBV-CLD) and alterations in the microbiota post-IMT are quite limited for the moment.MethodsBy integrating microbiome with metabolome analyses, we aimed to the function of IMT and the alterations of gut microbiota in patients with HBV-CLD. First, this study included 20 patients with HBV-CLD and ten healthy controls. Then, 16 patients with CHB were given IMT with donor feces (heterologous) via oral capsule. Fecal samples from CHB patients were obtained before and after IMT, as well as healthy controls, for 16S rDNA sequencing and untargeted metabolomics analysis.ResultsThe proalbuminemia were significantly increased after IMT, and the HBsAg and TBA showed a significant decrease after IMT in the HBV-CLD patients. There was statistical difference in the Chaol indexes between between CHB patients and healthy controls, suggesting a lower abundance of the gut microbiota in HBV-CLD patients. In addition, there was statistical difference in the Shannon and Simpson indexes between prior to IMT and post-IMT, indicating that the impaired abundance of the gut microbiota had been improved after IMT. The host-microbiota-metabolite interplay, amino acid metabolism, nicotinate and nicotinamide metabolism, starch and sucrose metabolism, steroid biosynthesis, and vitamins metabolism, were significantly lower in HBV-CLD patients than healthy controls.ConclusionIMT may improve the therapeutic effects on patients HBV-CLD. Furthermore, IMT appears to improve amino acid metabolism by impaired abundance of the gut microbiota and therefore improve liver prealbumin synthesis.
Neurocognitive deficits after botulism: a clinical case series study
Authors: Rosenqvist Laura , Sandvei Charlotte , Skarphedinsson Sigurdur 
Published: September 2024

PurposeThis case study examined long-term cognitive deficits after botulism. Only a very limited number of studies on post-acute cognitive impairment after botulism exist, and data are incomplete.MethodA semi-structured interview on long-term cognitive consequences of botulism was conducted for six family members, who contracted the infection after ingestion of lumpfish-roe 2.5 years ago. Two of the family members underwent neuropsychological assessment of attention, memory, and executive functioning as well.FindingResults of the semi-structured interviews showed individual subjective cognitive deficits across processing speed, attention, concentration, short-and long-term memory, and executive functioning. Test results showed mild cognitive impairment in attention and mild–moderate deficits in executive functioning.ConclusionThese results support previous findings that patients of various infectious diseases may suffer unspecific long-term neurocognitive deficits. Assessment and initiation of relevant post-acute treatment and rehabilitation might be central to prognosis, functional ability, and psychological well-being.
Negative association of serum neurofilament light chain with estimated glomerular filtration rate levels and the impact of gender
Authors: Peng Hongyan , Liang Zhuoxin , Huang Bolun , Zhang Senxiong , Yang Yiyu 
Published: September 2024

BackgroundThe relationship between kidney function and brain function is complex and poorly understood. This study aims to investigate the association between serum neurofilament light chain (sNfL) and levels of estimated glomerular filtration rate (eGFR), offering new insights into their interactions.MethodsData from the national health and nutrition examination survey (NHANES) in 2013–2014, linked with national death index records, were used. Participants who met specific criteria were analyzed. Baseline characteristics were stratified by tertiles of sNfL levels and compared using weighted Kruskal-Wallis and chi-square tests. Weighted linear regression models, both unadjusted and adjusted, evaluated the relationship between log sNfL and eGFR. Subgroup and interaction analyses validated the findings. Restricted cubic spline, scatter plots, and Spearman correlation confirmed the relationship between log sNfL and eGFR.ResultsA total of 2,038 eligible participants were included. Higher sNfL levels were significantly associated with lower eGFR (p &lt; 0.01). The highest sNfL tertile had a significantly higher mortality rate (p &lt; 0.01). Fully adjusted multivariable weighted linear regression showed a significant negative correlation between log sNfL and eGFR (per 10-unit increase; β = −0.07, 95% CI: −0.10 to −0.04, p &lt; 0.01). Subgroup analyses consistently supported this negative correlation (p &lt; 0.01). Interaction analysis revealed a significant gender difference (p = 0.032), with males showing a − 0.06 (−0.09, −0.04) decrease and females a − 0.07 (−0.11, −0.04) decrease in log sNfL per 10-unit increase in eGFR. Restricted cubic spline confirmed a linear relationship (p-non-linear = 0.121), and the Spearman correlation coefficient was −0.45. Females had slightly lower log sNfL levels compared to males at equivalent eGFR levels.ConclusionA significant negative correlation was found between log sNfL and eGFR levels. Gender influenced the degree of this negative association. Further research is needed to validate these findings and elucidate their underlying mechanisms.
Bibliometric and visualized analysis of the application of artificial intelligence in stroke
Authors: Xu Fangyuan , Dai Ziliang , Ye Yu , Hu Peijia , Cheng Hongliang 
Published: September 2024

BackgroundStroke stands as a prominent cause of mortality and disability worldwide, posing a major public health concern. Recent years have witnessed rapid advancements in artificial intelligence (AI). Studies have explored the utilization of AI in imaging analysis, assistive rehabilitation, treatment, clinical decision-making, and outcome and risk prediction concerning stroke. However, there is still a lack of systematic bibliometric analysis to discern the current research status, hotspots, and possible future development trends of AI applications in stroke.MethodsThe publications on the application of AI in stroke were retrieved from the Web of Science Core Collection, spanning 2004–2024. Only articles or reviews published in English were included in this study. Subsequently, a manual screening process was employed to eliminate literature not pertinent to the topic. Visualization diagrams for comprehensive and in-depth analysis of the included literature were generated using CiteSpace, VOSviewer, and Charticulator.ResultsThis bibliometric analysis included a total of 2,447 papers, and the annual publication volume shows a notable upward trajectory. The most prolific authors, countries, and institutions are Dukelow, Sean P., China, and the University of Calgary, respectively, making significant contributions to the advancement of this field. Notably, stable collaborative networks among authors and institutions have formed. Through clustering and citation burst analysis of keywords and references, the current research hotspots have been identified, including machine learning, deep learning, and AI applications in stroke rehabilitation and imaging for early diagnosis. Moreover, emerging research trends focus on machine learning as well as stroke outcomes and risk prediction.ConclusionThis study provides a comprehensive and in-depth analysis of the literature regarding AI in stroke, facilitating a rapid comprehension of the development status, cooperative networks, and research priorities within the field. Furthermore, our analysis may provide a certain reference and guidance for future research endeavors.
Pica is associated with lower willingness to change negative habits of diet and exercise, inadequate lifestyle, and less healthful food consumption in dialysis
Authors: Orozco-González Claudia N. , Marquez-Herrera Roxana M. , Martín-del-Campo Fabiola , Cortés-Sanabria Laura , Villasana-Ballesteros Mariana , Cueto-Manzano Alfonso M. 
Published: September 2024

BackgroundIn dialysis patients, on the one hand unwillingness to change negative lifestyle patterns is associated with worse nutritional status and unhealthy lifestyle, whereas on the other, pica may be highly prevalent. However, it is not known whether pica is associated with unwillingness to change negative lifestyle behaviors, as well as with consumption of different types of foods. This study aimed to investigate this issue.MethodsThis is a cross-sectional study in dialysis patients. Lifestyle was assessed using the self-administered Instrument to Measure Lifestyle Questionnaire (IMEVID). Pica diagnosis was established according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. A food frequency questionnaire was performed and self-reported willingness to change was determined by a trans-theoretical model staging inventory.ResultsCompared with patients without pica, those with pica (particularly hard pica) had lower willingness to change unhealthy behavior in the case of diet (22% vs. 46% in precontemplation/contemplation stages, respectively) and exercise (43% vs. 62% in precontemplation/contemplation stages, respectively). Patients with hard pica had significantly (p &lt; 0.05) lower scores in almost all dimensions of the lifestyle questionnaire than those in the no pica group: diet (23.9 vs. 26.8, respectively), physical activity (5.5 vs. 7, respectively), knowledge of disease (5.7 vs. 6.4, respectively), emotion management (6.6 vs. 8, respectively) and adherence to treatment (13.4 vs. 14.7, respectively), but not in the consumption of tobacco and alcohol. Compared to patients with no pica, those with hard pica ate vegetables and fruits less frequently, and dairy products, fried foods and soda more frequently.ConclusionsPica was more frequently observed in patients with lower willingness to change negative habits of diet and exercise, in those who had more unhealthy behaviors in diet, exercise and emotion management dimensions and adherence to treatment, as well as in those who ate less frequently healthful foods and more frequently unhealthy foods.
Differentiation of pheochromocytoma and adrenal lipoid adenoma by radiomics: are enhanced CT scanning images necessary?
Authors: Liu Shi he , Nie Pei , Liu Shun li , Hao Dapeng , Zhang Juntao , Sun Rui , Yang Zhi tao , Zhang Chuan yu , Fu Qing 
Published: September 2024

PurposeTo establish various radiomics models based on conventional CT scan images and enhanced CT images, explore their value in the classification of pheochromocytoma (PHEO) and lipid-poor adrenal adenoma (LPA) and screen the most parsimonious and efficient modelMethodsThe clinical and imaging data of 332 patients (352 lesions) with PHEO or LPA confirmed by surgical pathology in the Affiliated Hospital of Qingdao University were retrospectively analyzed. The region of interest (ROI) on conventional and enhanced CT images was delineated using ITK-SNAP software. Different radiomics signatures were constructed from the radiomics features extracted from conventional and enhanced CT images, and a radiomics score (Rad score) was calculated. A clinical model was established using demographic features and CT findings, while radiomics nomograms were established using multiple logistic regression analysis.The predictive efficiency of different models was evaluated using the area under curve (AUC) and receiver operating characteristic (ROC) curve. The Delong test was used to evaluate whether there were statistical differences in predictive efficiency between different models.ResultsThe radiomics signature based on conventional CT images showed AUCs of 0.97 (training cohort, 95% CI: 0.95∼1.00) and 0.97 (validation cohort, 95% CI: 0.92∼1.00). The AUCs of the nomogram model based on conventional scan CT images and enhanced CT images in the training cohort and the validation cohort were 0.97 (95% CI: 0.95∼1.00) and 0.97 (95% CI: 0.94~1.00) and 0.98 (95% CI: 0.97∼1.00) and 0.97 (95% CI: 0.94∼1.00), respectively. The prediction efficiency of models based on enhanced CT images was slightly higher than that of models based on conventional CT images, but these differences were statistically insignificant(P&gt;0.05).ConclusionsCT-based radiomics signatures and radiomics nomograms can be used to predict and identify PHEO and LPA. The model established based on conventional CT images has great identification and prediction efficiency, and it can also enable patients to avoid harm from radiation and contrast agents caused by the need for further enhancement scanning in traditional image examinations.
The value of multiparameter MRI of early cervical cancer combined with SCC-Ag in predicting its pelvic lymph node metastasis
Authors: Xu Xiaoqian , Liu Fenghai , Zhao Xinru , Wang Chao , Li Da , Kang Liqing , Liu Shikai , Zhang Xiaoling 
Published: September 2024

PurposeTo investigate the value of multiparameter MRI of early cervical cancer (ECC) combined with pre-treatment serum squamous cell carcinoma antigen (SCC-Ag) in predicting its pelvic lymph node metastasis (PLNM).Material and methods115 patients with pathologically confirmed FIGO IB1~IIA2 cervical cancer were retrospectively included and divided into the PLNM group and the non-PLNM group according to pathological results. Quantitative parameters of the primary tumor include Ktrans, Kep, Ve from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), ADCmean, ADCmin, ADCmax, D, D* and f from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) were measured. Pre-treatment serum SCC-Ag was obtained. The difference of the above parameters between the two groups were compared using the student t-test or Mann-Whitney U test. Multivariate Logistic regression analysis was performed to determine independent risk factors. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic efficacy of individual parameters and their combination in predicting PLNM from ECC.ResultsThe PLNM group presented higher SCC-Ag [14.25 (6.74,36.75) ng/ml vs.2.13 (1.32,6.00) ng/ml, P&lt;0.001] and lower Ktrans (0.51 ± 0.20 min-1 vs.0.80 ± 0.33 min-1, P &lt; 0.001), ADCmean (0.85 ± 0.09 mm/s2 vs.1.06 ± 0.35 mm/s2, P&lt;0.001), ADCmin [0.67 (0.61,0.75) mm/s2 vs. 0.75 (0.64,0.90) mm/s2, P = 0.012] and f (0.91 ± 0.09 vs. 0.27 ± 0.14, P = 0.001) than the non-LNM group. Multivariate analysis showed that SCC-Ag (OR = 1.154, P = 0.007), Ktrans (OR=0.003, P &lt; 0.001) and f (OR = 0.001, P=0.036) were independent risk factors of PLNM. The combination of SCC-Ag, Ktrans and f possessed the best predicting efficacy for PLNM with an area under curve (AUC) of 0.896, which is higher than any individual parameter: SCC-Ag (0.824), Ktrans (0.797), and f (0.703). The sensitivity and specificity of the combination were 79.1% and 94.0%, respectively.ConclusionsQuantitative parameters Ktrans and f derived from DCE-MRI and IVIM-DWI of primary tumor and SCC-Ag have great value in predicting PLNM. The diagnostic efficacy of their combination has been further improved.
The prognostic value of Th17/Treg cell in cervical cancer: a systematic review and meta-analysis
Authors: Zhang Jingwei , Zhan Jijie , Guan Ziting , Lin Xinmei , Li Tian , Li Miao , Zhang Changlin , Zhong Li 
Published: September 2024

BackgroundThe prognostic significance of Treg and Th17 cells, as well as their ratio (Th17/Treg), in cervical cancer remains a topic of debate. Our study aimed to clarify their association with patient survival and clinical outcomes in cervical cancer through a comprehensive meta-analysis.Materials and methodsWe conducted a comprehensive search in PubMed, Embase, and Web of Science to identify eligible studies. Studies related to cervical cancer and involving Treg cells or Th17 cells were included. For prognostic analysis, we collected Hazard Ratio values of patient survival. For studies focusing on clinical characteristics, we selected mean and standard deviation values for further analysis. This study was registered at PROSPERO (ID:CRD42024546507).ResultsOut of the 2949 records initially retrieved, we ultimately included 21 studies in our analysis. High levels of Treg cells were found to be correlated with shorter survival in patients with cervical cancer. Subgroup analysis revealed that the prognostic effect of Treg cells on cervical cancer was not influenced by their source or definition. However, analyses of different survival measures indicated that only Overall Survival showed a correlation with Treg cell levels. Additionally, Treg cells were associated with clinical staging. High-grade Th17 cells were associated with lymphatic metastases and advanced clinical stage. The Th17/Treg ratio was found to be elevated in both cervical intraepithelial neoplasia and cervical cancer patients compared to controls.DiscussionDespite limitations such as heterogeneity among selected studies and inadequate subgroup analyses, our study contributes to a deeper understanding of the significance of Treg cells in the onset and progression of cervical cancer. It also provides valuable insights for future research in immunotherapy.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42024546507.
Rapid detection of liver metastasis risk in colorectal cancer patients through blood test indicators
Authors: Yu Zhou , Li Gang , Xu Wanxiu 
Published: September 2024

IntroductionColorectal cancer (CRC) is one of the most common malignancies, with liver metastasis being its most common form of metastasis. The diagnosis of colorectal cancer liver metastasis (CRCLM) mainly relies on imaging techniques and puncture biopsy techniques, but there is no simple and quick early diagnosisof CRCLM. MethodsThis study aims to develop a method for rapidly detecting the risk of liver metastasis in CRC patients through blood test indicators based on machine learning (ML) techniques, thereby improving treatment outcomes. To achieve this, blood test indicators from 246 CRC patients and 256 CRCLM patients were collected and analyzed, including routine blood tests, liver function tests, electrolyte tests, renal function tests, glucose determination, cardiac enzyme profiles, blood lipids, and tumor markers. Six commonly used ML models were used for CRC and CRCLM classification and optimized by using a feature selection strategy.ResultsThe results showed that AdaBoost algorithm can achieve the highest accuracy of 89.3% among the six models, which improved to 91.1% after feature selection strategy, resulting with 20 key markers. ConclusionsThe results demonstrate that the combination of machine learning techniques with blood markers is feasible and effective for the rapid diagnosis of CRCLM, significantly im-proving diagnostic ac-curacy and patient prognosis.
From sugar binders to diabetes fighters: the lectin saga of antihyperglycemic activity through systematic review and meta-analysis
Authors: Simha N. Akshaya , Patil Shashank M. , M. K. Jayanthi , N. Chaitra , Wong Ling Shing , Kijsomporn Jureerat , Raj Ranjith , Ramu Ramith 
Published: September 2024

IntroductionLectins are carbohydrate-binding proteins that are extremely selective for sugar groups in the other molecules. As a result, they perform a variety of roles in biological processes involving cell, carbohydrate, and protein recognition at the cellular and molecular levels. Because lectins can bind to carbohydrates, they may play a role in determining the rate of carbohydrate digestion. They also bind to some proteins involved in diabetes mellitus (DM) pathophysiology. The present review aims to summarize the efficiency of lectins from different sources as potential antihyperglycemic agents.MethodsThe Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were employed for the drafting. In this regard, published scientific articles on the effects of different lectins on blood glucose (BG), glucose tolerance, hormonal effects, carbohydrate-digesting enzymes, oxidative stress, and insulin production process were collected from reputed journals using electronic databases. Furthermore, the toxicity effects of lectins from different sources were collected. A specific keyword search was completed to collect numerous articles with unique experimental designs and significant results. This was followed by the selection of the requisite articles based on the criteria designed by the authors. Data extraction was based on the common research elements included in the articles.Results and DiscussionOf 13 identified studies, 11 studies were considered after double screening based on the inclusion criteria. All 11 pharmacological investigations were considered for review. Subsequent studies reflected on the pharmacological properties of lectins on the levels of BG, oxidative stress, β-cell proliferation, insulin resistance, inhibition of carbohydrate digesting enzymes, body weight, food and water intake, lipid profile, and other parameters. This review highlights lectins as potential anti-diabetic agents.ConclusionHowever, due to limited research, systematic evaluation is recommended for their development and promotion as effective potential antihyperglycemic agents. The clinical efficacy and safety of lectins against diabetes mellitus must also be evaluated.
Cannabidiol, a plant-derived compound, is an emerging strategy for treating cognitive impairments: comprehensive review of randomized trials
Authors: Yndart Arias Adriana , Vadell Kamila , Vashist Arti , Kolishetti Nagesh , Lakshmana Madepalli K. , Nair Madhavan , Liuzzi Juan P. 
Published: September 2024

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