Reviews in the Neurosciences最新文献

Peripheral nerve injury (PNI) is one of the most serious causes of disability and loss of work capacity of younger individuals. Although PNS has a certain degree of regeneration, there are still challenges like disordered growth, neuroma formation, and incomplete regeneration. Regarding the management of PNI, conventional methods such as surgery, pharmacotherapy, and rehabilitative therapy. Treatment strategies vary depending on the severity of the injury. While for the long nerve defect, autologous nerve grafting is commonly recognized as the preferred surgical approach. Nevertheless, due to lack of donor sources, neurological deficits and the low regeneration efficiency of grafted nerves, nerve guide conduits (NGCs) are recognized as a future promising technology in recent years. This review provides a comprehensive overview of current treatments for PNI, and discusses NGCs from different perspectives, such as material, design, fabrication process, and composite function.

Intravenous thrombolysis (IT) and mechanical thrombectomy (MD) are the two interventional approaches that have changed the outcome of patients with acute ischemic stroke (AIS). Ipsilateral and contralateral carotid stenosis (ICS, CCS) play an important role in regulating cerebral hemodynamics, both in chronic and acute situations such as AIS. Several studies have explored their role in the incidence and severity of stroke, but very few have investigated the possible impact of ICS and CCS on the efficacy of interventional procedures. The purpose of this review was to I) highlight the incidence and prevalence of carotid stenosis (CS); II) assess the impact of ICS and CCS on cerebral hemodynamics; III) evaluate the effect of carotid stenosis on the efficacy of interventional therapies (IT and MT) for AIS; and IV) report therapeutic complications related to CS. We searched PubMed/Medline for case reports, reviews, and original research articles on English-language review topics during the period from January 1, 2000 to October 1, 2023. CS is associated with 15-20 % of the total number of AIS. ICS and CCS had a negative influence on both cerebral hemodynamics before AIS and outcome after interventional procedures (IT, MT alone or in bridging). Available data on cerebral hemodynamics and efficacy of interventional therapies for AIS suggest a negative role of CS. Therefore, early diagnosis of CS may be considered relevant to preventive and post-stroke treatment strategies.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with a poor prognosis leading to death. The diagnosis and treatment of ALS are inherently challenging due to its complex pathomechanism. Long noncoding RNAs (lncRNAs) are transcripts longer than 200 nucleotides involved in different cellular processes, incisively gene expression. In recent years, more studies have been conducted on lncRNA classes and interference in different disease pathologies, showing their promising contribution to diagnosing and treating neurodegenerative diseases. In this review, we discussed the role of lncRNAs like NEAT1 and C9orf72-as in ALS pathogenesis mechanisms caused by mutations in different genes, including TAR DNA-binding protein-43 (TDP-43), fused in sarcoma (FUS), superoxide dismutase type 1 (SOD1). NEAT1 is a well-established lncRNA in ALS pathogenesis; hence, we elaborate on its involvement in forming paraspeckles, stress response, inflammatory response, and apoptosis. Furthermore, antisense lncRNAs (as-lncRNAs), a key group of transcripts from the opposite strand of genes, including ZEB1-AS1 and ATXN2-AS, are discussed as newly identified components in the pathology of ALS. Ultimately, we review the current standing of using lncRNAs as biomarkers and therapeutic agents and the future vision of further studies on lncRNA applications.

Since Cajal introduced dendritic spines in the 19th century, they have attained considerable attention, especially in neuropsychiatric and neurologic disorders. Multiple roles of dendritic spine malfunction and pathology in the progression of various diseases have been reported. Thus, it is inevitable to consider these structures as new therapeutic targets for treating neuropsychiatric and neurologic disorders such as autism spectrum disorders, schizophrenia, dementia, Down syndrome, etc. Therefore, we attempted to prepare a narrative review of the literature regarding the role of dendritic spines in the pathogenesis of aforementioned diseases and to shed new light on their pathophysiology.

Post-stroke depression (PSD) and post-stroke cognitive impairment (PSCI) are common complications following a stroke, significantly impacting the quality of life and survival time of survivors. Currently, the comorbidity of PSCI and PSD is receiving increasing attention, as they share some common clinical characteristics, mechanisms, risk factors, radiological features, and treatment strategies. They influence each other, with the clinical prevalence of PSD comorbid with PSCI reaching as high as 26.15 %. The prevention, screening, diagnosis, and treatment of PSD and PSCI require collaboration across clinical, radiological, and neuropsychological evaluations. This paper aims to summarize the common radiological features of both conditions from a radiological perspective, which may aid in identifying early screening and predictive imaging biomarkers.

Amyotrophic lateral sclerosis (ALS) is a rare neurodegenerative disease which damages upper and lower motor neurons (UMN and LMN) innervating the muscles of the trunk, extremities, head, neck and face in cerebrum, brain stem and spinal cord, which results in the progressive weakness, atrophy and fasciculation of muscle innervated by the related UMN and LMN, accompanying with the pathological signs leaded by the cortical spinal lateral tract lesion. The pathogenesis about ALS is not fully understood, and no specific drugs are available to cure and prevent the progression of this disease at present. In this review, we reviewed the structure and associated functions of copper-zinc superoxide dismutase 1 (SOD1), discuss why SOD1 is crucial to the pathogenesis of ALS, and outline the pathogenic mechanisms of SOD1 in ALS that have been identified at recent years, including glutamate-related excitotoxicity, mitochondrial dysfunction, endoplasmic reticulum stress, oxidative stress, axonal transport disruption, prion-like propagation, and the non-cytologic toxicity of glial cells. This review will help us to deeply understand the current progression in this field of SOD1 pathogenic mechanisms in ALS.

An extensive review is presented on mitochondrial structure and function, mitochondrial proteins, the outer and inner membranes, cristae, the role of F₁F_O-ATP synthase, the mitochondrial contact site and cristae organizing system (MICOS), the sorting and assembly machinery morphology and function, and phospholipids, in particular cardiolipin. Aspects of mitochondrial regulation under physiological and pathological conditions are outlined, in particular the role of dysregulated MICOS protein subunit Mic60 in Parkinson's disease, the relations between mitochondrial quality control and proteins, and mitochondria as signaling organelles. A mathematical modeling approach of cristae and MICOS using mechanical beam theory is introduced and outlined. The proposed modeling is based on the premise that an optimization framework can be used for a better understanding of critical mitochondrial function and also to better map certain experiments and clinical interventions.

Childhood epilepsy affects up to 1 % of children. It has been shown that 30 % of patients are resistant to drug treatments, making further investigation of other potential treatment strategies necessary. One such approach is the ketogenic diet (KD) showing promising results and potential benefits beyond the use of current antiepileptic drugs. This study aims to investigate the effects of KD on inflammation and oxidative stress, as one of the main suggested mechanisms of neuroprotection, in children with epilepsy. This narrative review was conducted using the Medline and Google Scholar databases, and by searching epilepsy, drug-resistant epilepsy, child, children, ketogenic, ketogenic diet, diet, ketogenic, keto, ketone bodies (BHB), PUFA, gut microbiota, inflammation, inflammation mediators, neurogenic inflammation, neuroinflammation, inflammatory marker, adenosine modulation, mitochondrial function, MTOR pathway, Nrf2 pathway, mitochondrial dysfunction, PPARɣ, oxidative stress, ROS/RNS, and stress oxidative as keywords. Compelling evidence underscores inflammation and oxidative stress as pivotal factors in epilepsy, even in cases with genetic origins. The ketogenic diet effectively addresses these factors by reducing ROS and RNS, enhancing antioxidant defenses, improving mitochondrial function, and regulating inflammatory genes. Additionally, KD curbs pro-inflammatory cytokine and chemokine production by dampening NF-κB activation, inhibiting the NLRP3 inflammasome, increasing brain adenosine levels, mTOR pathway inhibition, upregulating PPARɣ expression, and promoting a healthy gut microbiota while emphasizing the consumption of healthy fats. KD could be considered a promising therapeutic intervention in patients with epilepsy particularly in drug-resistant epilepsy cases, due to its targeted approach addressing oxidative stress and inflammatory mechanisms.

Functional near-infrared spectroscopy (fNIRS) and its interaction with machine learning (ML) is a popular research topic for the diagnostic classification of clinical disorders due to the lack of robust and objective biomarkers. This review provides an overview of research on psychiatric diseases by using fNIRS and ML. Article search was carried out and 45 studies were evaluated by considering their sample sizes, used features, ML methodology, and reported accuracy. To our best knowledge, this is the first review that reports diagnostic ML applications using fNIRS. We found that there has been an increasing trend to perform ML applications on fNIRS-based biomarker research since 2010. The most studied populations are schizophrenia (n = 12), attention deficit and hyperactivity disorder (n = 7), and autism spectrum disorder (n = 6) are the most studied populations. There is a significant negative correlation between sample size (>21) and accuracy values. Support vector machine (SVM) and deep learning (DL) approaches were the most popular classifier approaches (SVM = 20) (DL = 10). Eight of these studies recruited a number of participants more than 100 for classification. Concentration changes in oxy-hemoglobin (ΔHbO) based features were used more than concentration changes in deoxy-hemoglobin (ΔHb) based ones and the most popular ΔHbO-based features were mean ΔHbO (n = 11) and ΔHbO-based functional connections (n = 11). Using ML on fNIRS data might be a promising approach to reveal specific biomarkers for diagnostic classification.

Artificial intelligence (AI) is increasingly being used in the medical field, specifically for brain cancer imaging. In this review, we explore how AI-powered medical imaging can impact the diagnosis, prognosis, and treatment of brain cancer. We discuss various AI techniques, including deep learning and causality learning, and their relevance. Additionally, we examine current applications that provide practical solutions for detecting, classifying, segmenting, and registering brain tumors. Although challenges such as data quality, availability, interpretability, transparency, and ethics persist, we emphasise the enormous potential of intelligent applications in standardising procedures and enhancing personalised treatment, leading to improved patient outcomes. Innovative AI solutions have the power to revolutionise neuro-oncology by enhancing the quality of routine clinical practice.