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Brain Sciences Apr 2024The aim of this study was to review the current state of scientific evidence on the effect of extremely low-frequency magnetic fields stimulation (ELF-MFs) on stroke... (Review)
Review
BACKGROUND
The aim of this study was to review the current state of scientific evidence on the effect of extremely low-frequency magnetic fields stimulation (ELF-MFs) on stroke patients.
METHODS
A systematic review of PubMed, ScienceDirect, PeDro and Embase databases was conducted. Only articles published in English, involving adult participants and focusing on individuals who had experienced a stroke, specifically examining the impact of ELF-MFs on post-stroke patients and had well-defined criteria for inclusion and exclusion of participants, were included. The methodological quality of the included studies was assessed using the Quality Assessment Tool for Quantitative Studies (QATQS).
RESULTS
A total of 71 studies were identified through database and reference lists' search, from which 9 were included in the final synthesis. All included studies showed a beneficial effect of ELF-MFs on stroke patients, however seven of the included studies were carried by the same research group. Improvements were observed in domains such as oxidative stress, inflammation, ischemic lesion size, functional status, depressive symptoms and cognitive abilities.
CONCLUSIONS
The available literature suggests a beneficial effect of ELF-MFs on post-stroke patients; however, the current data are too limited to broadly recommend the use of this method. Further research with improved methodological quality is necessary.
PubMed: 38790409
DOI: 10.3390/brainsci14050430 -
Cells May 2024This systematic review aims to gather evidence on the mechanisms triggered by diverse preconditioning strategies for mesenchymal stem cells (MSCs) and their impact on... (Review)
Review
This systematic review aims to gather evidence on the mechanisms triggered by diverse preconditioning strategies for mesenchymal stem cells (MSCs) and their impact on their potential to treat ischemic and traumatic injuries affecting the nervous system. The 52 studies included in this review report nine different types of preconditioning, namely, manipulation of oxygen pressure, exposure to chemical substances, lesion mediators or inflammatory factors, usage of ultrasound, magnetic fields or biomechanical forces, and culture in scaffolds or 3D cultures. All these preconditioning strategies were reported to interfere with cellular pathways that influence MSCs' survival and migration, alter MSCs' phenotype, and modulate the secretome and proteome of these cells, among others. The effects on MSCs' phenotype and characteristics influenced MSCs' performance in models of injury, namely by increasing the homing and integration of the cells in the lesioned area and inducing the secretion of growth factors and cytokines. The administration of preconditioned MSCs promoted tissue regeneration, reduced neuroinflammation, and increased angiogenesis and myelinization in rodent models of stroke, traumatic brain injury, and spinal cord injury. These effects were also translated into improved cognitive and motor functions, suggesting an increased therapeutic potential of MSCs after preconditioning. Importantly, none of the studies reported adverse effects or less therapeutic potential with these strategies. Overall, we can conclude that all the preconditioning strategies included in this review can stimulate pathways that relate to the therapeutic effects of MSCs. Thus, it would be interesting to explore whether combining different preconditioning strategies can further boost the reparative effects of MSCs, solving some limitations of MSCs' therapy, namely donor-associated variability.
Topics: Humans; Mesenchymal Stem Cells; Animals; Mesenchymal Stem Cell Transplantation; Nervous System Diseases
PubMed: 38786067
DOI: 10.3390/cells13100845 -
World Neurosurgery May 2024Access to neuro-oncologic care in Nigeria has grown exponentially since the first reported cases in the mid-1960s. In this systematic review and pooled analysis, we...
OBJECTIVE
Access to neuro-oncologic care in Nigeria has grown exponentially since the first reported cases in the mid-1960s. In this systematic review and pooled analysis, we characterize the growth of neurosurgical oncology in Nigeria and build a reference paper to direct efforts to expand this field.
METHODS
We performed an initial literature search of several article databases and gray literature sources. We included and subsequently screened articles published between 1962 and 2021. Several variables were extracted from each study, including the affiliated hospital, the number of patients treated, patient sex, tumor pathology, the types of imaging modalities used for diagnosis, and the interventions used for each individual. Change in these variables was assessed using Chi-squared independence tests and univariate linear regression when appropriate.
RESULTS
A total of 147 studies were identified, corresponding to 5,760 patients. Over 4000 cases were reported in the past 2 decades from 21 different Nigerian institutions. The types of tumors reported have increased over time, with increasingly more patients being evaluated via computed tomography (CT) and magnetic resonance imaging (MRI). There is also a prevalent use of radiotherapy, though chemotherapy remains an underreported treatment modality.
CONCLUSIONS
This study highlights key trends regarding the prevalence and management of neuro-oncologic pathologies within Nigeria. Further studies are needed to continue to learn and guide the future growth of this field in Nigeria.
Topics: Nigeria; Humans; Brain Neoplasms; Medical Oncology; Neurosurgery
PubMed: 38741325
DOI: 10.1016/j.wneu.2023.11.071 -
The British Journal of Radiology Jun 2024Prostate cancer ranks among the most prevalent cancers affecting men globally. While conventional MRI serves as a diagnostic tool, its extended acquisition time,...
BACKGROUND
Prostate cancer ranks among the most prevalent cancers affecting men globally. While conventional MRI serves as a diagnostic tool, its extended acquisition time, associated costs, and strain on healthcare systems, underscore the necessity for more efficient methods. The emergence of AI-acceleration in prostate MRI offers promise to mitigate these challenges.
METHODS
A systematic review of studies looking at AI-accelerated prostate MRI was conducted, with a focus on acquisition time along with various qualitative and quantitative measurements.
RESULTS
Two primary findings were observed. Firstly, all studies indicated that AI-acceleration in MRI achieved notable reductions in acquisition times without compromising image quality. This efficiency offers potential clinical advantages, including reduced scan durations, improved scheduling, diminished patient discomfort, and economic benefits. Secondly, AI demonstrated a beneficial effect in reducing or maintaining artefact levels in T2-weighted images despite this accelerated acquisition time. Inconsistent results were found in all other domains, which were likely influenced by factors such as heterogeneity in methodologies, variability in AI models, and diverse radiologist profiles. These variances underscore the need for larger, more robust studies, standardization, and diverse training datasets for AI models.
CONCLUSION
The integration of AI-acceleration in prostate MRI thus far shows some promising results for efficient and enhanced scanning. These advancements may fill current gaps in early detection and prognosis. However, careful navigation and collaborative efforts are essential to overcome challenges and maximize the potential of this innovative and evolving field.
ADVANCES IN KNOWLEDGE
This article reveals overall significant reductions in acquisition time without compromised image quality in AI-accelerated prostate MRI, highlighting potential clinical and diagnostic advantages.
Topics: Humans; Male; Prostatic Neoplasms; Magnetic Resonance Imaging; Prostate; Artificial Intelligence
PubMed: 38718224
DOI: 10.1093/bjr/tqae093 -
Frontiers in Neurology 2024Low Back Pain (LBP) is a pervasive and complex musculoskeletal condition affecting over 80% of the global population. Lumbar Disc Degeneration (LDD) significantly...
BACKGROUND
Low Back Pain (LBP) is a pervasive and complex musculoskeletal condition affecting over 80% of the global population. Lumbar Disc Degeneration (LDD) significantly contributes to LBP, and MRI is crucial for its diagnosis and understanding. This study aimes to provide a comprehensive bibliometric analysis of MRI research on LDD with LBP, shedding light on research patterns, collaborations, and potential knowledge gaps.
METHODS
A comprehensive online search was conducted in the Scopus database to retrieve published literature on LDD with LBP. Bibliometric analysis was conducted to assess publication patterns, co-authorship networks, keyword co-occurrence, and co-citation analysis within the MRI applications for LDD research domain. Bibliometric analysis tools such as VOSviewer and the R package "bibliometrix" were utilized for quantitative assessments.
RESULTS
A total of 1,619 publications related to MRI and LDD were analyzed. The analysis indicated a consistent annual growth rate of 4.62% in publications related to MRI and lumbar disc degeneration, reflecting a steady increase in research output over the past two decades. The USA, China, and Japan emerged as leading contributors. "SPINE", "European Spine Journal", and "Spine Journal" were the most productive journals in this domain. Key research themes identified included lumbar spine, low back pain, and magnetic resonance imaging. Network visualization shows that low back pain and magnetic resonance imaging were the most widely used keywords.
CONCLUSION
The comprehensive bibliometric analysis of MRI applications for Lumbar Disc Degeneration offers insights into prevailing research patterns, highlights key contributors and journals, and identifies significant research themes. This study provides a foundation for future research efforts and clinical practices in the field, ultimately contributing to the advancement of patient care for individuals suffering from LDD and associated Low Back Pain.
PubMed: 38694782
DOI: 10.3389/fneur.2024.1360091 -
Critical Reviews in Oncogenesis 2024Deep learning (DL) is poised to redefine the way medical images are processed and analyzed. Convolutional neural networks (CNNs), a specific type of DL architecture, are...
Deep learning (DL) is poised to redefine the way medical images are processed and analyzed. Convolutional neural networks (CNNs), a specific type of DL architecture, are exceptional for high-throughput processing, allowing for the effective extraction of relevant diagnostic patterns from large volumes of complex visual data. This technology has garnered substantial interest in the field of neuro-oncology as a promising tool to enhance medical imaging throughput and analysis. A multitude of methods harnessing MRI-based CNNs have been proposed for brain tumor segmentation, classification, and prognosis prediction. They are often applied to gliomas, the most common primary brain cancer, to classify subtypes with the goal of guiding therapy decisions. Additionally, the difficulty of repeating brain biopsies to evaluate treatment response in the setting of often confusing imaging findings provides a unique niche for CNNs to help distinguish the treatment response to gliomas. For example, glioblastoma, the most aggressive type of brain cancer, can grow due to poor treatment response, can appear to grow acutely due to treatment-related inflammation as the tumor dies (pseudo-progression), or falsely appear to be regrowing after treatment as a result of brain damage from radiation (radiation necrosis). CNNs are being applied to separate this diagnostic dilemma. This review provides a detailed synthesis of recent DL methods and applications for intratumor segmentation, glioma classification, and prognosis prediction. Furthermore, this review discusses the future direction of MRI-based CNN in the field of neuro-oncology and challenges in model interpretability, data availability, and computation efficiency.
Topics: Humans; Glioma; Prognosis; Brain Neoplasms; Neural Networks, Computer; Deep Learning; Magnetic Resonance Imaging; Image Processing, Computer-Assisted
PubMed: 38683153
DOI: 10.1615/CritRevOncog.2023050852 -
Reviews in the Neurosciences Apr 2024Cognitive disorders such as major depressive disorder and bipolar disorder severely compromise brain function and neuronal activity. Treatments to restore cognitive... (Review)
Review
Cognitive disorders such as major depressive disorder and bipolar disorder severely compromise brain function and neuronal activity. Treatments to restore cognitive abilities can have severe side effects due to their intense and excitatory nature, in addition to the fact that they are expensive and invasive. Low-field magnetic stimulation (LFMS) is a novel non-invasive proposed treatment for cognitive disorders. It repairs issues in the brain by altering deep cortical areas with treatments of low-intensity magnetic stimulation. This paper aims to summarize the current literature on the effects and results of LFMS in cognitive disorders. We developed a search strategy to identify relevant studies utilizing LFMS and systematically searched eight scientific databases. Our review suggests that LFMS could be a viable and effective treatment for multiple cognitive disorders, especially major depressive disorder. Additionally, longer, more frequent, and more personalized LFMS treatments tend to be more efficacious.
PubMed: 38671560
DOI: 10.1515/revneuro-2024-0023 -
Cancer Medicine Apr 2024Thyroid cancer (TC) is the predominant malignancy within the endocrine system. However, the standard method for TC diagnosis lacks the capability to identify the... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Thyroid cancer (TC) is the predominant malignancy within the endocrine system. However, the standard method for TC diagnosis lacks the capability to identify the pathological condition of all thyroid lesions. The metabolomics approach has the potential to manage this problem by identifying differential metabolites.
AIMS
This study conducted a systematic review and meta-analysis of the NMR-based metabolomics studies in order to identify significant altered metabolites associated with TC.
METHODS
A systematic search of published literature in any language in three databases including Embase, PubMed, and Scopus was conducted. Out of 353 primary articles, 12 studies met the criteria for inclusion in the systematic review. Among these, five reports belonging to three articles were eligible for meta-analysis. The correlation coefficient of the orthogonal partial least squares discriminant analysis, a popular model in the multivariate statistical analysis of metabolomic data, was chosen for meta-analysis. The altered metabolites were chosen based on the fact that they had been found in at least three studies.
RESULTS
In total, 49 compounds were identified, 40 of which were metabolites. The increased metabolites in thyroid lesions compared normal samples included lactate, taurine, alanine, glutamic acid, glutamine, leucine, lysine, phenylalanine, serine, tyrosine, valine, choline, glycine, and isoleucine. Lipids were the decreased compounds in thyroid lesions. Lactate and alanine were increased in malignant versus benign thyroid lesions, while, myo-inositol, scyllo-inositol, citrate, choline, and phosphocholine were found to be decreased. The meta-analysis yielded significant results for three metabolites of lactate, alanine, and citrate in malignant versus benign specimens.
DISCUSSION
In this study, we provided a concise summary of 12 included metabolomic studies, making it easier for future researchers to compare their results with the prior findings.
CONCLUSION
It appears that the field of TC metabolomics will experience notable advancement, leading to the discovery of trustworthy diagnostic and prognostic biomarkers.
Topics: Humans; Thyroid Neoplasms; Metabolomics; Metabolome; Biomarkers, Tumor; Thyroid Gland; Magnetic Resonance Spectroscopy
PubMed: 38646957
DOI: 10.1002/cam4.7184 -
Environment International May 2024The technological applications of radiofrequency electromagnetic fields (RF-EMF) have been steadily increasing since the 1950s exposing large proportions of the... (Meta-Analysis)
Meta-Analysis
BACKGROUND
The technological applications of radiofrequency electromagnetic fields (RF-EMF) have been steadily increasing since the 1950s exposing large proportions of the population. The World Health Organization (WHO) is assessing the potential health effects of exposure to RF-EMF.
OBJECTIVES
To systematically assess the effects of exposure to RF-EMF on self-reported non-specific symptoms in human subjects and to assess the accuracy of perceptions of presence or absence of RF-EMF exposure.
METHODS
Eligibility criteria: experimental studies carried out in the general population and in individuals with idiopathic environmental intolerance attributed to EMF (IEI-EMF), in any language.
INFORMATION SOURCES
Medline, Web of Science, PsycInfo, Cochrane Library, Epistemonikos, Embase and EMF portal, searched till April 2022. Risk of Bias (ROB): we used the RoB tool developed by OHAT adapted to the topic of this review.
SYNTHESIS OF RESULTS
we synthesized studies using random effects meta-analysis and sensitivity analyses, where appropriate.
RESULTS
Included studies: 41 studies were included, mostly cross over trials and from Europe, with a total of 2,874 participants.
SYNTHESIS OF RESULTS
considering the primary outcomes, we carried out meta-analyses of 10 exposure-outcomes pairs. All evidence suggested no or small non-significant effects of exposure on symptoms with high (three comparisons), moderate (four comparisons), low (one comparison) and very low (two comparisons) certainty of evidence. The effects (standard mean difference, where positive values indicate presence of symptom being exposed) in the general population for head exposure were (95% confidence intervals) 0.08 (-0.07 to 0.22) for headache, -0.01 (-0.22 to 0.20) for sleeping disturbances and 0.13 (-0.51 to 0.76) for composite symptoms; and for whole-body exposure: 0.09 (-0.35 to 0.54), 0.00 (-0.15 to 0.15) for sleeping disturbances and -0.05 (-0.17 to 0.07) for composite symptoms. For IEI-EMF individuals SMD ranged from -0.19 to 0.11, all of them with confidence intervals crossing the value of zero. Further, the available evidence suggested that study volunteers could not perceive the EMF exposure status better than what is expected by chance and that IEI-EMF individuals could not determine EMF conditions better than the general population.
DISCUSSION
Limitations of evidence: experimental conditions are substantially different from real-life situations in the duration, frequency, distance and position of the exposure. Most studies were conducted in young, healthy volunteers, who might be more resilient to RF-EMF than the general population. The outcomes of interest in this systematic review were symptoms, which are self-reported. The available information did not allow to assess the potential effects of exposures beyond acute exposure and in elderly or in chronically ill people. It cannot be ruled out that a real EMF effect in IEI-EMF groups is masked by a mix with insensitive subjects. However, studies on symptoms reporting and/or field perceptions did not find any evidence that there were particularly vulnerable individuals in the IEI-EMF group, although in open provocation studies, when volunteers were informed about the presence or absence of EMF exposure, such differences were consistently observed.
INTERPRETATION
available evidence suggests that acute RF-EMF below regulatory limits does not cause symptoms and corresponding claims in the everyday life are related to perceived and not to real EMF exposure status.
Topics: Humans; Electromagnetic Fields; Self Report; Environmental Exposure; Radio Waves
PubMed: 38640611
DOI: 10.1016/j.envint.2024.108612 -
Neurological Research May 2024To analyze the effects of transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS) on the cognitive function of individuals with... (Meta-Analysis)
Meta-Analysis
Effect of transcranial direct current stimulation and transcranial magnetic stimulation on the cognitive function of individuals with Alzheimer's disease: a systematic review with meta-analysis and meta-regression.
OBJECTIVE
To analyze the effects of transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS) on the cognitive function of individuals with Alzheimer's disease (AD).
METHODS
This systematic review with meta-analysis and meta-regression included randomized clinical trials published until 05/2022. We included studies conducted with individuals with AD of both sexes, aged between 55 and 85 years, treated with tDCS, TMS, or both.
RESULTS
Twenty-one studies were included in the systematic review and sixteen in the meta-analysis. Meta-regression suggested a significant influence of anodic tDCS with current intensity of 1.5 mA on cognitive function. Significant results were found with treatment frequencies of three and five days a week for two weeks. Subgroup analysis found that anodic tDCS influences cognitive function, regardless of AD stage. Similar was observed for TMS using a frequency of 20 Hz and current intensity of 90% of the resting motor threshold.
DISCUSSION
Anodal tDCS and 20 Hz TMS have demonstrated the ability to improve cognitive function in AD by modulating neural activity. These therapies are safe and well-tolerated, offering promise as adjuncts to available pharmacological treatments. Studies with greater methodological rigor and parameter standardization are warranted. Comprehensive investigations involving neuroimaging techniques may provide a better understanding of the interaction between induced electrical fields and the complex neural networks affected in AD, paving the way for more personalized and effective neurostimulation approaches.
Topics: Aged; Aged, 80 and over; Female; Humans; Middle Aged; Alzheimer Disease; Cognition; Transcranial Direct Current Stimulation; Transcranial Magnetic Stimulation
PubMed: 38634361
DOI: 10.1080/01616412.2024.2321779