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Background: Extracellular cold-inducible RNA-binding protein (eCIRP) plays a vital role in the inflammatory response during cerebral ischaemia. However, the potential role and regulatory mechanism of eCIRP in traumatic brain injury (TBI) remain unclear. Here, we explored the effect of eCIRP on the development of TBI using a neural-specific CIRP knockout (KO) mouse model to determine the contribution of eCIRP to TBI-induced neuronal injury and to discover novel therapeutic targets for TBI. Methods: TBI animal models were generated in mice using the fluid percussion injury method. Microglia or neuron lines were subjected to different drug interventions. Histological and functional changes were observed by immunofluorescence and neurobehavioural testing. Apoptosis was examined by a TdT-mediated dUTP nick end labelling assay in vivo or by an annexin-V assay in vitro. Ultrastructural alterations in the cells were examined via electron microscopy. Tissue acetylation alterations were identified by non-labelled quantitative acetylation via proteomics. Protein or mRNA expression in cells and tissues was determined by western blot analysis or real-time quantitative polymerase chain reaction. The levels of inflammatory cytokines and mediators in the serum and supernatants were measured via enzyme-linked immunoassay. Results: There were closely positive correlations between eCIRP and inflammatory mediators, and between eCIRP and TBI markers in human and mouse serum. Neural-specific eCIRP KO decreased hemispheric volume loss and neuronal apoptosis and alleviated glial cell activation and neurological function damage after TBI. In contrast, eCIRP treatment resulted in endoplasmic reticulum disruption and ER stress (ERS)-related death of neurons and enhanced inflammatory mediators by glial cells. Mechanistically, we noted that eCIRP-induced neural apoptosis was associated with the activation of the protein kinase RNA-like ER kinase-activating transcription factor 4 (ATF4)-C/EBP homologous protein signalling pathway, and that eCIRP-induced microglial inflammation was associated with histone H3 acetylation and the α7 nicotinic acetylcholine receptor. Conclusions: These results suggest that TBI obviously enhances the secretion of eCIRP, thereby resulting in neural damage and inflammation in TBI. eCIRP may be a biomarker of TBI that can mediate the apoptosis of neuronal cells through the ERS apoptotic pathway and regulate the inflammatory response of microglia via histone modification.
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Background: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) account for a significant proportion of gynecological malignancies and represent a major global health concern. Globally, CESC is ranked as the fourth most common cancer among women. Conventional treatment of this disease has a less favorable prognosis for most patients. However, the discovery of early molecular biomarkers is therefore important for the diagnosis of CESC, as well as for slowing down their progression process. Methods: To identify differentially expressed genes strongly associated with prognosis, univariate Cox proportional hazard analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used. Using multiple Cox proportional hazard regression, a multifactorial model for prognostic risk assessment was then created. Results: The expression of biological clock-related genes, which varied considerably among distinct subtypes and were associated with significantly diverse prognoses, was used to categorize CESC patients. These findings demonstrate how the nomogram developed based on the 7-CRGs signature may assist physicians in creating more precise, accurate, and successful treatment plans that can aid CESC patients at 1, 3, and 5 years. Conclusions: By using machine learning techniques, we thoroughly investigated the impact of CRGs on the prognosis of CESC patients in this study. By creating a unique nomogram, we were able to accurately predict patient prognosis. At the same time, we showed new perspectives on the development of CESC and its treatment by analyzing the associations of the prognostic model with immunity, enrichment pathways, chemotherapy sensitivity, and so on. This research provides a new direction for clinical treatment.
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BACKGROUND: Previous clinical trials have reported that acupoint catgut embedding (ACE) is a useful modality for weight loss. However, no study has specifically investigated the effectiveness and safety of comparing verum and sham ACE in adults with obesity. Thus, this study aimed to evaluate the effectiveness and safety of comparing verum and sham ACE in obese adults. METHODS: A comprehensive literature search was conducted in the electronic databases of PUBMED, EMBASE, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang, China Science and Technology Journal Database, and China Biomedical Literature Service System from inception to April 1, 2022. Randomized clinical trials that focused on evaluating the effectiveness of comparing verum and sham ACE in adults with obesity were included. The primary outcomes included reduction in body weight, body mass index, hip circumference, and waist circumference. The secondary outcomes consisted of a decrease in body fat percentage and the occurrence rate of adverse events. The methodological quality of the included randomized clinical trials was evaluated using the Cochrane Risk-of-bias tool. Statistical analysis was performed using RevMan 5.4 software. RESULTS: Six trials involving 679 adults with obesity were included in this study and entered in the data analysis of systematic review and meta-analysis. Results of the meta-analysis revealed significant reduction in body weight (mean difference [MD]â =â -1.68, 95% confidence intervals (CI) [-2.34, -1.01], I2â =â 51%, Pâ <â .001), body mass index (MDâ =â -0.51, 95% CI [-0.81, -0.21], I2â =â 74%, Pâ <â .001), hip circumference (MDâ =â -1.11, 95% CI [-1.67, -0.55], I2â =â 0%, Pâ <â .001), waist circumference (MDâ =â -2.42, 95% CI [-3.38, -1.45], I2â =â 68%, Pâ <â .001), and decrease in body fat percentage (MDâ =â -0.83, 95% CI [-1.30, -0.36], I2â =â 16%, Pâ <â .001) in comparing verum and sham ACE. However, no significant difference was identified in AEs (odds ratioâ =â 1.53, 95% CI [0.80, 2.95], I2â =â 0%, Pâ =â .20) between the 2 groups. CONCLUSION: ACE is effective in the treatment of obesity in adults with safety profile. Further studies with higher quality and larger sample size are warranted to confirm the current findings.
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Pontos de Acupuntura , Categute , Adulto , Humanos , Categute/efeitos adversos , Ensaios Clínicos Controlados Aleatórios como Assunto , Obesidade/tratamento farmacológico , Peso CorporalRESUMO
With the significant increase in the global prevalence of diabetes mellitus (DM), the occurrence of diabetic peripheral neuropathy (DPN) has become increasingly common complication associated with DM. It is particularly in the peripheral nerves of the hands, legs, and feet. DPN can lead to various adverse consequences that greatly affect the quality of life for individuals with DM. Despite the profound impact of DPN, the specific mechanisms underlying its development and progression are still not well understood. Advancements in magnetic resonance imaging (MRI) technology have provided valuable tools for investigating the central mechanisms involved in DPN. Structural and functional MRI techniques have emerged as important methods for studying the brain structures and functions associated with DPN. Voxel-based morphometry allows researchers to assess changes in the volume and density of different brain regions, providing insights into potential structural alterations related to DPN. Functional MRI investigates brain activity patterns, helping elucidate the neural networks engaged during sensory processing and pain perception in DPN patients. Lastly, magnetic resonance spectroscopy provides information about the neurochemical composition of specific brain regions, shedding light on potential metabolic changes associated with DPN. By synthesizing available literature employing these MRI techniques, this study aims to enhance our understanding of the neural mechanisms underlying DPN and contribute to the improvement of clinical diagnosis.
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Vascular cognitive impairment not dementia (VCIND) is one of the three subtypes of vascular cognitive impairment (VCI), with cognitive dysfunction and symptoms ranging between normal cognitive function and vascular dementia. The specific mechanisms underlying VCIND are still not fully understood, and there is a lack of specific diagnostic markers in clinical practice. With the rapid development of magnetic resonance imaging (MRI) technology, structural MRI (sMRI) and functional MRI (fMRI) have become effective methods for exploring the neurobiological mechanisms of VCIND and have made continuous progress. This article provides a comprehensive overview of the research progress in VCIND using multimodal MRI, including sMRI, diffusion tensor imaging, resting-state fMRI, and magnetic resonance spectroscopy. By integrating findings from these multiple modalities, this study presents a novel perspective on the neuropathological mechanisms underlying VCIND. It not only highlights the importance of multimodal MRI in unraveling the complex nature of VCIND but also lays the foundation for future research examining the relationship between brain structure, function, and cognitive impairment in VCIND. These new perspectives and strategies ultimately hold the potential to contribute to the development of more effective diagnostic tools and therapeutic interventions for VCIND.
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Vascular cognitive impairment (VCI) is the initial stage of vascular dementia (VaD). Early diagnosis and treatment of VCI are crucial to prevent the progression of VaD. In order to gain a better understanding of VCI, this study aimed to investigate the use of advanced imaging techniques such as structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI). These techniques allow researchers to observe the structural and functional changes in the brain that are associated with VCI. Functional magnetic resonance imaging (fMRI) and sMRI techniques have been widely used in studies focusing on gray matter, brain networks, and functional abnormalities during rest. By searching and summarizing recent literature, this study has provided valuable evidence on the use of advanced imaging techniques in understanding and treating VCI. The findings from this study can aid in the development of early intervention strategies for patients with VCI, potentially slowing down or even halting the progression of VCI to full-blown VaD.
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Subjective cognitive decline (SCD) is the initial stage of Alzheimer's disease (AD). Early identification of SCD and its risk factors is of great importance for targeted interventions and for delaying the onset of AD. We reviewed the relevant literature on structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI), functional magnetic resonance imaging (fMRI), and other techniques regarding SCD research in recent years. This study applied sMRI and fMRI techniques to explore abnormal brain structures and functions, which may help provide a basis for SCD diagnosis.
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AIM: To understand the placebo response of acupuncture and its effect on migraine and optimize the design of future acupuncture clinical trials on migraine treatment. METHODS: Randomized controlled trials with sham acupuncture as a control in migraine treatment were searched in four English databases from inception to September 1, 2022. The primary outcome was placebo response rate. Secondary outcomes were migraine symptoms, emotional condition, and quality of life. Factors associated with placebo response were also explored. Results were combined using risk difference (RD) or standardized mean difference (SMD) and 95% confidence interval (CI) with a random effects model. RESULTS: The final analysis included 21 studies involving 1177 patients. The pooled response rate of sham acupuncture was 0.34 (RD, 95% CI 0.23-0.45, I2 89.8%). The results (SMD [95% CI]) showed significant improvements in migraine symptoms (pain intensity -0.56 [-0.73 to -0.38], and episode conditions -0.55 [-0.75 to -0.35]); emotional condition (anxiety scale -0.49 [-0.90 to -0.08] and depression scale -0.21 [-0.40 to -0.03]); and quality of life on the Migraine-Specific Quality-of-Life Questionnaire (restrictive 0.78 [0.61-0.95]; preventive 0.52 [0.35-0.68]; and emotional 0.45 [0.28-0.62]) and on the Medical Outcomes Study Short-Form (physical 0.48 [0.34-0.62] and mental 0.21 [0.02-0.41]). Only acupuncture treatment frequency had a significant impact on the placebo response rate (RD 0.49 vs. 0.14; p = 0.00). CONCLUSIONS: The effect sizes for placebo response of sham acupuncture varied across migraine treatment trials. Further studies should routinely consider adjusting for a more complete set of treatment factors.
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Terapia por Acupuntura , Transtornos de Enxaqueca , Humanos , Qualidade de Vida , Terapia por Acupuntura/métodos , Transtornos de Enxaqueca/prevenção & controle , Avaliação de Resultados em Cuidados de Saúde , Efeito Placebo , Ensaios Clínicos Controlados Aleatórios como AssuntoRESUMO
Background: Uveal melanoma (UVM) is a primary intraocular malignancy that poses a significant threat to patients' visual function and life. The basement membrane (BM) is critical for establishing and maintaining cell polarity, adult function, embryonic and organ morphogenesis, and many other biological processes. Some basement membrane protein genes have been proven to be prognostic biomarkers for various cancers. This research aimed to develop a novel risk assessment system based on BMRGs that would serve as a theoretical foundation for tailored and accurate treatment. Methods: We used gene expression profiles and clinical data from the TCGA-UVM cohort of 80 UVM patients as a training set. 56 UVM patients from the combined cohort of GSE84976 and GSE22138 were employed as an external validation dataset. Prognostic characteristics of basement membrane protein-related genes (BMRGs) were characterized by Lasso, stepwise multifactorial Cox. Multivariate analysis revealed BMRGs to be independent predictors of UVM. The TISCH database probes the crosstalk of BMEGs in the tumor microenvironment at the single-cell level. Finally, we investigated the function of ITGA5 in UVM using multiple experimental techniques, including CCK8, transwell, wound healing assay, and colony formation assay. Results: There are three genes in the prognostic risk model (ADAMTS10, ADAMTS14, and ITGA5). After validation, we determined that the model is quite reliable and accurately forecasts the prognosis of UVM patients. Immunotherapy is more likely to be beneficial for UVM patients in the high-risk group, whereas the survival advantage may be greater for UVM patients in the low-risk group. Knockdown of ITGA5 expression was shown to inhibit the proliferation, migration, and invasive ability of UVM cells in vitro experiments. Conclusion: The 3-BMRGs feature model we constructed has excellent predictive performance which plays a key role in the prognosis, informing the individualized treatment of UVM patients. It also provides a new perspective for assessing pre-immune efficacy.
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Background: Amnestic mild cognitive impairment (aMCI) is an early stage of Alzheimer's disease (AD). Regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) are employed to explore spontaneous brain function in patients with aMCI. This study applied ALFF and ReHo indicators to analyze the neural mechanism of aMCI by resting-state functional magnetic resonance imaging (rs-fMRI). Methods: Twenty-six patients with aMCI were included and assigned to the aMCI group. The other 26 healthy subjects were included as a healthy control (HC) group. Rs-fMRI was performed for all participants in both groups. Between-group comparisons of demographic data and neuropsychological scores were analyzed using SPSS 25.0. Functional imaging data were analyzed using DPARSF and SPM12 software based on MATLAB 2017a. Gender, age, and years of education were used as covariates to obtain ALFF and ReHo indices. Results: Compared with HC group, ALFF decreased in the left fusiform gyrus, left superior temporal gyrus, and increased in the left cerebellum 8, left inferior temporal gyrus, left superior frontal gyrus (BA11), and right inferior temporal gyrus (BA20) in the aMCI group (p < 0.05, FWE correction). In addition, ReHo decreased in the right middle temporal gyrus and right anterior cuneiform lobe, while it increased in the left middle temporal gyrus, left inferior temporal gyrus, cerebellar vermis, right parahippocampal gyrus, left caudate nucleus, right thalamus, and left superior frontal gyrus (BA6) (p < 0.05, FWE correction). In the aMCI group, the ALFF of the left superior frontal gyrus was negatively correlated with Montreal Cognitive Assessment (MoCA) score (r = -0.437, p = 0.026), and the ALFF of the left superior temporal gyrus was positively correlated with the MoCA score (r = 0.550, p = 0.004). The ReHo of the right hippocampus was negatively correlated with the Mini-Mental State Examination (MMSE) score (r = -0.434, p = 0.027), and the ReHo of the right middle temporal gyrus was positively correlated with MMSE score (r = 0.392, p = 0.048). Conclusion: Functional changes in multiple brain regions rather than in a single brain region have been observed in patients with aMCI. The abnormal activity of multiple specific brain regions may be a manifestation of impaired central function in patients with aMCI.
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Amnestic mild cognitive impairment (aMCI) is a stage between normal aging and Alzheimer disease (AD) where individuals experience a noticeable decline in memory that is greater than what is expected with normal aging, but dose not meet the clinical criteria for AD. This stage is considered a transitional phase that puts individuals at a high risk for developing AD. It is crucial to intervene during this stage to reduce the changes of AD development. Recently, advanced multimodal magnetic resonance imaging techniques have been used to study the brain structure and functional networks in individuals with aMCI. Through the use of structural magnetic resonance imaging, diffusion tensor imaging, and functional magnetic resonance imaging, abnormalities in certain brain regions have been observed in individuals with aMCI. Specifically, the default mode network, salience network, and executive control network have been found to show abnormalities in both structure and function. This review aims to provide a comprehensive understanding of the brain structure and functional networks associated with aMCI. By analyzing the existing literature on multimodal magnetic resonance imaging and aMCI, this study seeks to uncover potential biomarkers and gain insight into the underlying pathogenesis of aMCI. This knowledge can then guide the development of future treatments and interventions to delay or prevent the progression of aMCI to AD.
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Doença de Alzheimer , Disfunção Cognitiva , Humanos , Imagem de Tensor de Difusão , Imageamento por Ressonância Magnética , Encéfalo/diagnóstico por imagem , Função Executiva , Doença de Alzheimer/diagnóstico por imagem , Disfunção Cognitiva/diagnóstico por imagemRESUMO
This study aimed to investigate the research hotspots and global trends of acupuncture in the treatment of headaches from 1974 to 2022. The Web of Science core collection database and literature related to acupuncture for headache treatment were retrieved. The CiteSpace (version 5.1.R8) and VOSviewer (version 1.6.19) software perform collaborative network analysis on the information of countries, academic institutions, authors, and co-occurrence network analysis on keywords, co-cited journals, and references. A total of 841 studies were included. Overall, the number of publications has increased over the past 5 decades. We identified and analyzed the countries, institutions, authors, and journals that were most active in the domain of acupuncture treatment for headaches. The most productive countries were the United States and China. Chengdu University of Traditional Chinese Medicine was the most productive institution and Linde Klaus was the most productive author. Cephalalgia was the most productive and co-cited journal, whereas Lancet had the highest impact factor. The research hotspots mainly focus on headache, migraine, tension headache, electroacupuncture, and acupuncture. Research trends have mainly focused on acupuncture therapy and its curative effects, migraine without aura, paroxysmal migraine, and the mechanism of acupuncture treatment. The main research hotspots and frontier trends were the therapeutic effect and mechanism of acupuncture for headaches. The mechanism of acupuncture in the treatment of headache mainly focused on the neural mechanism by multimodal MRI.
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Terapia por Acupuntura , Transtornos de Enxaqueca , Cefaleia do Tipo Tensional , Humanos , Bibliometria , Cefaleia/terapiaRESUMO
Background: Pancreatic cancer (PC) is a lethal malignancy that ranks seventh in terms of global cancer-related mortality. Despite advancements in treatment, the five-year survival rate remains low, emphasizing the urgent need for reliable early detection methods. MicroRNAs (miRNAs), a group of non-coding RNAs involved in critical gene regulatory mechanisms, have garnered significant attention as potential diagnostic and prognostic biomarkers for pancreatic cancer (PC). Their suitability stems from their accessibility and stability in blood, making them particularly appealing for clinical applications. Methods: In this study, we analyzed serum miRNA expression profiles from three independent PC datasets obtained from the Gene Expression Omnibus (GEO) database. To identify serum miRNAs associated with PC incidence, we employed three machine learning algorithms: Support Vector Machine-Recursive Feature Elimination (SVM-RFE), Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest. We developed an artificial neural network model to assess the accuracy of the identified PC-related serum miRNAs (PCRSMs) and create a nomogram. These findings were further validated through qPCR experiments. Additionally, patient samples with PC were classified using the consensus clustering method. Results: Our analysis revealed three PCRSMs, namely hsa-miR-4648, hsa-miR-125b-1-3p, and hsa-miR-3201, using the three machine learning algorithms. The artificial neural network model demonstrated high accuracy in distinguishing between normal and pancreatic cancer samples, with verification and training groups exhibiting AUC values of 0.935 and 0.926, respectively. We also utilized the consensus clustering method to classify PC samples into two optimal subtypes. Furthermore, our investigation into the expression of PCRSMs unveiled a significant negative correlation between the expression of hsa-miR-125b-1-3p and age. Conclusion: Our study introduces a novel artificial neural network model for early diagnosis of pancreatic cancer, carrying significant clinical implications. Furthermore, our findings provide valuable insights into the pathogenesis of pancreatic cancer and offer potential avenues for drug screening, personalized treatment, and immunotherapy against this lethal disease.
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Background: Alzheimer's disease (AD) is a common, progressive, irreversible, and fatal neurodegenerative disorder with rapidly increasing worldwide incidence. Although much research on magnetic resonance imaging (MRI) of the white matter (WM) in AD has been published, no bibliometric analysis study has investigated this issue. Thus, this study aimed to provide an overview of the current status, hotspots, and trends in MRI of WM in AD. Methods: We searched for records related to MRI studies of WM in AD from 1990 to 2022 in the Web of Science Core Collection (WOSCC) database. CiteSpace (version 5.1.R8) and VOSviewer (version 1.6.19) software were used for bibliometric analyses. Results: A total of 2,199 articles were obtained from this study. From 1990 to 2022, the number of published articles showed exponential growth of y = 4.1374e0.1294x, with an average of 17.9 articles per year. The top country and institutions were the United States and the University of California Davis, accounting for 44.52 and 5.32% of the total studies, respectively. The most productive journal was Neurology, and the most co-cited journal was Lancet Neurology. Decarli C was the most productive author. The current research frontier trend focuses on the association between small vessel disease and AD, the clinical application and exploration of diffusion MRI, and related markers. Conclusion: This study provides an in-depth overview of publications on MRI of WM in AD, identifying the current research status, hotspots, and frontier trends in the field.
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This study aimed to identify abnormal brain regions and imaging indices of vascular cognitive impairment (VCI) and explore specific imaging diagnostic markers of VCI. In this study, 24 patients with VCI were allocated to the VCI group and 25 healthy subjects were assigned to the healthy control (HC) group. Demographic data and neuropsychological test scores were compared using SPSS 25.0. The structural and functional imaging data were post-processed and statistically analyzed using CAT12, DPARSF and SPM12 software, based on the MATLAB platform. The structural and functional indices of gray matter volume (GMV) and regional homogeneity (ReHo) were obtained, and inter-group data were analyzed using an independent-sample t test. Sex, age, years of education, and total brain volume were used as covariates. Compared to the HC group, the GMV of VCI in the VCI group decreased significantly in the rectus muscles of the bilateral gyrus, left superior temporal gyrus, left supplementary motor area (SMA), right insula, right superior temporal gyrus, right anterior cuneiform lobe, and right anterior central gyrus (PRECG) (P < .05, FWE correction), without GMV enlargement in the brain area. ReHo decreased in the right inferior temporal gyrus (ITG), right parahippocampal gyrus, and left temporal pole (middle temporal gyrus, right lingual gyrus, left posterior central gyrus, and right middle temporal gyrus), the areas of increased ReHo were the left caudate nucleus, left rectus gyrus, right anterior cingulate gyrus and lateral cingulate gyrus (P < .05, FWE correction). Correlation analysis showed that the GMV of the left superior temporal gyrus was positively correlated with the Montreal Cognitive Assessment (MoCA) score (P < .05), and the GMV of the right insula was positively correlated with the MESE and long delayed memory scores (P < .05). There was a significant positive correlation between the ReHo and short-term delayed memory scores in the middle temporal gyrus of the left temporal pole (P < .05). The volume of GMV and ReHo decreased in VCI patients, suggesting that impairment of brain structure and function in specific regions is the central mechanism of cognitive impairment in these patients. Meanwhile, the functional indices of some brain regions were increased, which may be a compensatory mechanism for the cognitive impairment associated with VCI.
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Mapeamento Encefálico , Disfunção Cognitiva , Humanos , Encéfalo/patologia , Imageamento por Ressonância Magnética/métodos , Substância Cinzenta/diagnóstico por imagem , Substância Cinzenta/patologiaRESUMO
Background: Clear cell renal carcinoma (ccRCC) stands as the prevailing subtype among kidney cancers, making it one of the most prevalent malignancies characterized by significant mortality rates. Notably,mitochondrial permeability transition drives necrosis (MPT-Driven Necrosis) emerges as a form of cell death triggered by alterations in the intracellular microenvironment. MPT-Driven Necrosis, recognized as a distinctive type of programmed cell death. Despite the association of MPT-Driven Necrosis programmed-cell-death-related lncRNAs (MPTDNLs) with ccRCC, their precise functions within the tumor microenvironment and prognostic implications remain poorly understood. Therefore, this study aimed to develop a novel prognostic model that enhances prognostic predictions for ccRCC. Methods: Employing both univariate Cox proportional hazards and Lasso regression methodologies, this investigation distinguished genes with differential expression that are intimately linked to prognosis.Furthermore, a comprehensive prognostic risk assessment model was established using multiple Cox proportional hazards regression. Additionally, a thorough evaluation was conducted to explore the associations between the characteristics of MPTDNLs and clinicopathological features, tumor microenvironment, and chemotherapy sensitivity, thereby providing insights into their interconnectedness.The model constructed based on the signatures of MPTDNLs was verified to exhibit excellent prediction performance by Cell Culture and Transient Transfection, Transwell and other experiments. Results: By analyzing relevant studies, we identified risk scores derived from MPTDNLs as an independent prognostic determinant for ccRCC, and subsequently we developed a Nomogram prediction model that combines clinical features and associated risk assessment. Finally, the application of experimental techniques such as qRT-PCR helped to compare the expression of MPTDNLs in healthy tissues and tumor samples, as well as their role in the proliferation and migration of renal clear cell carcinoma cells. It was found that there was a significant correlation between CDK6-AS1 and ccRCC results, and CDK6-AS1 plays a key role in the proliferation and migration of ccRCC cells. Impressive predictive results were generated using marker constructs based on these MPTDNLs. Conclusions: In this research, we formulated a new prognostic framework for ccRCC, integrating mitochondrial permeability transition-induced necrosis. This model holds significant potential for enhancing prognostic predictions in ccRCC patients and establishing a foundation for optimizing therapeutic strategies.
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BACKGROUND: Acupuncture and moxibustion (AM) are utilized to treat Alzheimer's disease (AD). However, no bibliometric analysis has explored this issue. Thus, this study investigated the status, hotspots and trends of AM in the treatment of AD. METHODS: CiteSpace and VOSviewer softwares were used to analyze the literature on the AM for AD in the Web of Science Core Collection database. We analyzed the data of countries/regions, institutions, journals, authors, keywords, and cited references. RESULTS: After removing duplicates, 193 articles were retrieved. The number of publications on this topic has increased gradually. The most productive and collaborative country was China (143 documents), followed by South Korea (19). The top 3 active academic institutions were Beijing University of Chinese Medicine, Capital Medicine University, and Guangzhou University of Chinese Medicine. The most productive journal was Evidence-based Complementary and Alternative Medicine (13 documents), followed by the Frontiers in Aging Neuroscience (10), Medicine (10), and Neural Regeneration Research (10). The top 3 co-cited journals were Evidence-based Complementary and Alternative Medicine (156 citations), Acupuncture Electro-therapeutics Research (152), and Acupuncture in Medicine (146). The research hotspots in this domain are dementia, memory, hippocampus, mouse models, and Parkinson's disease. Major frontiers are comparing the therapeutic effects of acupuncture and donepezil and electroacupuncture at different frequencies in this field. CONCLUSION: This bibliometric study identified relevant hotspots and trends in research on AM in the treatment of AD, which can provide researchers with key information in this domain and help further explore new research directions.
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Terapia por Acupuntura , Acupuntura , Doença de Alzheimer , Moxibustão , Doença de Alzheimer/terapia , Animais , Donepezila , CamundongosRESUMO
BACKGROUND: This study aimed to analyze and summarize the research hotspots and trends in neuroimaging biomarkers (NMBM) in Parkinson disease (PD) based on the Web of Science core collection database and provide new references for future studies. METHODS: Literature regarding NMBM in PD from 1998 to 2022 was analyzed using the Web of Science core collection database. We utilized CiteSpace software (6.1R2) for bibliometric analyses of countries/institutions/authors, keywords, keyword bursts, references, and their clusters. RESULTS: A total of 339 studies were identified with a continually increasing annual trend. The most productive country and collaboration was the United States. The top research hotspot is PD cognitive disorder. NMBM and artificial intelligence medical imaging have been applied in the clinical diagnosis, differential diagnosis, treatment, and prognosis of PD. The trends in this field include research on T1 weighted structure magnetic resonance imaging in accordance with voxel-based morphometry, PD cognitive disorder, and neuroimaging features of Lewy body dementia and Alzheimer disease. CONCLUSION: The development of NMBM in PD will be effectively promoted by drawing on international research hotspots and cutting-edge technologies, emphasizing international collaboration and institutional cooperation at the national level, and strengthening interdisciplinary research.
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Doença de Parkinson , Inteligência Artificial , Bibliometria , Biomarcadores , Humanos , Neuroimagem , Doença de Parkinson/diagnóstico por imagem , Doença de Parkinson/terapia , Estados UnidosRESUMO
BACKGROUND: Multimodality magnetic resonance imaging (MRI) is widely used to detect vascular cognitive impairment (VCI). However, a bibliometric analysis of this issue remains unknown. Therefore, this study aimed to explore the research hotspots and trends of multimodality MRI on VCI over the past 12 years based on the Web of Science core collection using CiteSpace Software (6.1R2). METHODS: Literature related to multimodality MRI for VCI from 2010 to 2021 was identified and analyzed from the Web of Science core collection database. We analyzed the countries, institutions, authors, cited journals, references, keyword bursts, and clusters using CiteSpace. RESULTS: In total, 587 peer-reviewed documents were retrieved, and the annual number of publications showed an exponential growth trend over the past 12 years. The most productive country was the USA, with 182 articles, followed by China with 134 papers. The top 3 active academic institutions were Capital Medical University, Radboud UNIV Nijmegen, and UNIV Toronto. The most productive journal was the Journal of Alzheimer's Disease (33 articles). The most co-cited journal was Neurology, with the highest citations (492) and the highest intermediary centrality (0.14). The top-ranked publishing author was De Leeuw FE (17 articles) with the highest intermediary centrality of 0.04. Ward Law JM was the most cited author (123 citations) and Salat Dh was the most centrally cited author (0.24). The research hotspots of multimodal MRI for VCI include Alzheimer disease, vascular cognitive impairment, white matter intensity, cerebrovascular disease, dementia, mild cognitive impairment, neurovascular coupling, acute ischemic stroke, depression, and cerebral ischemic stroke. The main frontiers in the keywords are fMRI, vascular coupling, and cerebral ischemic stroke, and current research trends include impact, decline, and classification. CONCLUSIONS: The findings from this bibliometric study provide research hotspots and trends for multimodality MRI for VCI over the past 12 years, which may help researchers identify hotspots and explore cutting-edge trends in this field.