Brain-X最新文献

In a groundbreaking study, Rezai et al. unveiled a promising avenue for treating Alzheimer's disease (AD) using aducanumab and a cutting-edge delivery method¹ (Figure 1A). The team employed magnetic resonance-guided focused ultrasound (MRgFUS) to transiently open the blood–brain barrier (BBB), facilitating the transport of the drug from the blood circulation to the brain tissue. This resulted in a remarkable reduction in amyloid deposition in the treated cerebral area in three human patients. The study counters the drug delivery barriers of the brain by demonstrating the potential efficacy of this innovative approach in treating Alzheimer's.

MRgFUS stands out as a pivotal modality in brain drug delivery; it offers distinctive advantages, particularly in achieving high spatiotemporal resolution. This technology selectively and reversibly opens the BBB, primarily through the paracellular pathway. This noninvasive methodology presents a compelling approach to increasing the brain parenchyma's permeability to drugs. One key feature lies in the capacity to engineer the volume, shape, and depth of the focal spot in the brain tissue. This engineered precision caters to the specific requirements of treating diverse neurological diseases. The adaptability and precision of MRgFUS open avenues for targeted and efficacious interventions in the intricate landscape of brain-related pathologies.

Beyond the anticipated benefits of enhanced aducanumab (an FDA-approved amyloid beta-directed human monoclonal antibody indicated to treat Alzheimer's disease) delivery to the brain, the study implicated the intricate dynamics of drug/toxic complex diffusion and clearance within the human brain parenchyma. Notably, although the scientific discussion around the benefits of aducanumab is ongoing, ultrasound waves not only facilitate BBB opening but also interact with the brain parenchyma beyond the BBB to induce multiple effects^{2, 3} that could account for the overall benefit (Figure 1B).

Considering the importance of the extracellular space (ECS), perivascular space (PVS), and cerebrospinal fluid flow dynamics in modulating drug diffusion, distribution, and waste clearance,⁴ several questions remain that require further investigation. First, does ultrasound expand the ECS? Second, does it impact the PVS? Third, can ultrasound enhance flow transport, improving the clearance of antibodies and degraded amyloid fragments? Fourth, how does ultrasound interact with brain cells (e.g., neurons, astrocytes, etc.)? Fifth, does any mechanical activation of the signaling pathway have an impact? Finally, how can the technology be translated and extended to increase the efficacy of other treatment modalities enabled by larger particles, such as antibody–drug conjugates, adeno-associated viruses, and lipid nanoparticles?

Some of these aspects have been studied in the preclinical animals' m

Synthetic biomaterials are emerging candidate solutions for treating large bone defects. However, the clinical performances of most synthetic materials are not satisfactory, with the need for improvement in design and synthesis. Although bone is highly innervated, the central role during healing of the peripheral nervous system, and in particular sensory nerves (SNs), has only recently been acknowledged. SNs can improve osteogenic differentiation of bone marrow stem/stromal cells through neurotransmitters and peptides; the interplay between SNs and the vascular system also facilitates vascular network reconstruction, indirectly facilitating bone healing. These factors suggest the importance of SNs in bone healing, a vital point that has been overlooked in bone biomaterial design until very recently. SN regeneration represents a novel direction in the development of biomaterials for bone regeneration. The current perspective paper summarizes the cellular and molecular mechanisms under the regulatory influence of SNs in the bone healing process and outlines the recent advances in biomaterials for innervated bone tissue regeneration. This establishes potential future directions for bone engineering biomaterial design.

Alzheimer's disease (AD) is a type of dementia characterized by a decline in brain function, which leads to the inability to perform activities independently. Many researchers recognize abnormalities related to beta-amyloid as the main cause of the disease (i.e., the beta-amyloid hypothesis), but aging, genetics, coronary heart disease, environmental factors, gender, and other risk factors may also contribute to AD development. Three drugs with different mechanisms are available for AD treatment: cholinesterase inhibitors, N-methyl d-aspartate, and aducanumab. This study reviewed the therapies that are already applied in clinical practice and those that are currently being investigated for clinical use. These therapies include not only pharmacological treatments but also non-pharmacological treatments, such as gut flora therapy and music therapy. A comprehensive understanding of these therapies is necessary to enable early intervention, improve patients' physical and mental conditions, delay the occurrence and development of AD, and extend patients' healthy lifespans.

Alzheimer's disease (AD) is a neurodegenerative disease and the most common cause of dementia, accounting for around 60%–70% dementia cases.¹ Normal pressure hydrocephalus (NPH) is one of the few reversible causes of dementia, accounting for approximately 6% of all dementias, among which, idiopathic normal pressure hydrocephalus (iNPH) happens mostly in elder people.² Due to the similarity of their symptoms, it is important to differentiate between iNPH and AD.³ In this paper, we reported a case who were originally diagnosed with iNPH and were finally found to be an AD patient via multimodality diagnostic approaches.

A 57-year-old woman, who got a short-term memory decline 2 years ago, was admitted to Tianjin Medical University General Hospital (Tianjin, China) in October 2023. Her speech, numeracy, and social networking ability also declined. She went to a local hospital 2 years ago and was diagnosed with iNPH. She was admitted to our hospital as a result of her symptoms progressively getting worse over the past few months and her gait deteriorating. The doctors suspected her as an iNPH or AD patient, thus arranging magnetic resonance imaging (MRI), cerebrospinal fluid tap test (CSF TT), Infusion study, phase-contrast magnetic resonance imaging (PC-MRI) on the admission day.

As shown in Figure 1, the MRI showed significant ventricular dilation, with an Evans index (EI) of 0.38. However, her Callosal Angle was 90.6°, and presented a negative DESH sign (disproportionately enlarged subarachnoid space hydrocephalus). Obvious atrophies were found in temporal lobe and parahippocampal gyrus. The PC-MRI shows enhanced cerebrospinal fluid flow signals in the ventricular system, with thinning of cerebral white matter. The imaging manifestations didn't quite match the main features of iNPH, she looks more like a dementia or an AD patient.

The CSF TT is a clinical tool for the diagnosis of iNPH, and has been regarded as an important prediction tool of shunt effectiveness in patients with suspected iNPH.⁴ During CSF TT, 30–50 mL CSF was released through a lumbar puncture, and patient's gait balance ability, bladder function, cognitive function was evaluated before and 24/48/72 h after CSF TT. No significant improvement was found after the CSF TT test.

Infusion study has been a well-defined method to assess the necessity of proceeding into shunt for iNPH patients. It offers several advantages and alternatives compared to traditional CSF TT, including short-testing duration, calculation of resistance to CSF outflow (Rout) and elasticity.⁵ For this patient, the infusion study showed an opening pressure of 9 mmHg, and resistance of CSF was 3.53 mmHg × min/mL, which indicates smooth CSF circulation (Supporting Information S1).

The patient declared slight alleviation after the CSF TT, however, the clinical assessm

Sepsis is a life-threatening organ dysfunction syndrome caused by the host's dysregulated response to infection. The leading causes of death in critically ill patients are sepsis-associated encephalopathy (SAE), respiratory dysfunction, circulatory dysfunction, and other multi-organ dysfunctions. SAE is among the most common serious complications of sepsis and is associated with a poor prognosis and long-term cognitive dysfunction. Its clinical manifestations vary, and there are still no unified diagnostic criteria. The incidence of SAE varies from 9% to 71% in critically ill patients due to therapeutic interventions such as sedation, mechanical ventilation, and muscle relaxants. Advances in medical technology have significantly increased the survival rate of patients with sepsis, but up to 21% now experience long-term sequelae or cognitive impairment. The lack of specific early diagnostic and treatment methods leads to increased SAE-associated mortality and complications in patients, which also impose heavy economic burdens. This article reviews the pathogenesis and diagnostic methods of SAE and progress in its treatment, aiming to reduce the mortality and hospitalization lengths of patients with SAE and improve their survival rate and quality of life through early detection, diagnosis, and effective treatment.

This easy-to-follow handbook offers a straightforward guide to electroencephalogram (EEG) analysis using Python, aimed at all EEG researchers in cognitive neuroscience and related fields. It spans from single-subject data preprocessing to advanced multisubject analyses. This handbook contains four chapters: Preprocessing Single-Subject Data, Basic Python Data Operations, Multiple-Subject Analysis, and Advanced EEG Analysis. The Preprocessing Single-Subject Data chapter provides a standardized procedure for single-subject EEG data preprocessing, primarily using the MNE-Python package. The Basic Python Data Operations chapter introduces essential Python operations for EEG data handling, including data reading, storage, and statistical analysis. The Multiple-Subject Analysis chapter guides readers on performing event-related potential and time-frequency analyses and visualizing outcomes through examples from a face perception task dataset. The Advanced EEG Analysis chapter explores three advanced analysis methodologies, Classification-based decoding, Representational Similarity Analysis, and Inverted Encoding Model, through practical examples from a visual working memory task dataset using NeuroRA and other powerful packages. We designed our handbook for easy comprehension to be an essential tool for anyone delving into EEG data analysis with Python (GitHub website: https://github.com/ZitongLu1996/Python-EEG-Handbook; For Chinese version: https://github.com/ZitongLu1996/Python-EEG-Handbook-CN).

Idiopathic normal pressure hydrocephalus (iNPH) is a disease caused by the accumulation of cerebrospinal fluid, leading to ventricular enlargement and manifesting as gait disorders, cognitive impairment, and urinary incontinence. The current diagnostic methods mainly rely on the patient's clinical symptoms, cerebrospinal fluid drainage response, and imaging results. A definitive diagnosis is suggested by significant symptom improvement post-drainage or when imaging shows an Evan's index (EI) > 0.3. Although these diagnostic methods have been widely used for many years, misdiagnoses still occur. Therefore, multimodal approaches are crucial for accurate diagnosis and treatment in complex cases. This paper reports a case of iNPH with an EI < 0.3 but with increased temporal angle width and pronounced clinical symptoms.

A 68-year-old male patient was admitted to the Tianjin Medical University General Hospital (Tianjin, China) with progressive unbalanced gait, leg weakness, urinary incontinence, and memory decline. One year ago, he underwent a head magnetic resonance imaging (MRI) at a local hospital due to trembling hands and changes in temperament; the result showed no abnormalities. Following a fall 1 month ago, he was readmitted to the same hospital for a cervical vertebra MRI examination, but no treatment was prescribed. More recently, his symptoms deteriorated, and he was admitted to our hospital for further diagnosis and treatment. He had no history of hypertension, diabetes, or coronary heart disease. On the day of his admission, the doctors arranged for an MRI, a tap test, and an infusion study due to suspected iNPH.

As shown in Figure 1, the MRI results allow for the calculation of several parameters for diagnosing iNPH, including EI, z-Evans index (z-EI), Brain/Ventricle Ratio (BVR), Corpus Callosum Angle (CA), and disproportionate enlargement of the subarachnoid space (DESH). According to current diagnostic criteria, an EI value ≥ 0.3 is an important indicator of ventricular dilation (Figure 1A).¹ In cases where EI < 0.3, a z-EI > 0.42 or a BVR < 1 also suggests ventricular dilation. The presence of DESH indicates a high likelihood of iNPH (Figure 1C).¹ In addition, a CA value < 90° suggests iNPH (Figure 1B).² In this reported case, the EI, z-EI, BVR, and CA did not meet the diagnostic criteria for iNPH, and there were no obvious DESH signs on the MRI. However, the patient's temporal horns of the lateral ventricles were significantly widened, and he demonstrated significant clinical symptoms of iNPH.

We conducted a CSF tap test (CSF-TT) and an infusion study (CSF-IT) to assess the CSF fluid circulation pathway. The CSF-TT is considered a simple, safe, and effective clinical tool for diagnosing iNPH in patients.³ During the procedure, 30–50 mL of CSF is released through a lumbar puncture. We then evaluate whe

In this article, we present the case for the adoption of a neurodiversity paradigm as an essential framework within the brain and behavioral sciences. We challenge the deficit-focused medical model by advocating for the recognition of neurocognitive variances—including autism, ADHD, dyslexia, schizophrenia, and bipolar disorder—as natural representations of human diversity. We call for a shift in research and practice towards valuing neurodivergent individuals' unique strengths and contributions and promoting inclusivity and empathy. In critiquing the tendency to pathologize cognitive differences, we argue for a re-evaluation of therapeutic goals to reflect a more nuanced understanding of neurodiversity. Highlighting the socio-ethical implications of therapy-focused research, we urge an appreciation of the potential for innovation and problem-solving that neurodivergent individuals bring to society. The conclusion is a call to action for an integrated approach in research, policy, and societal attitudes that affirms neurodiversity, fostering an environment in which all forms of cognitive functioning are celebrated as part of human advancement.

Parkinson's disease (PD) is a multifaceted neurodegenerative disorder characterized by a prolonged prodromal phase followed by the onset of clinical motor symptoms. The development of reliable biomarkers for individuals at risk of developing PD during this prodromal phase is a central focus of research in the field, to enable early interventions that could potentially modify the disease progression and improve patient outcomes.^{1, 2}

Yan et al., have made significant progress by examining the potential of serum L1CAM-positive extracellular vesicle (L1EV) associated α-synuclein as a biomarker for identification of at-risk individuals for developing PD.³ Their cross-sectional study involved a cohort of 576 subjects (from the Parkinson's Progression Markers Initiative (PPMI) and a German cohort) and aimed to evaluate the efficacy of serum L1EV derived α-synuclein in distinguishing individuals at risk of developing PD from healthy control (HC) subjects.

The findings of this study were encouraging, revealing the potential of serum L1EV α-synuclein as a promising indicator for screen out the ones with high risk of developing PD. By carefully establishing a threshold for serum L1EV α-synuclein levels, the researchers were able to distinguish subjects with independent rapid eye movement and sleep behavior disorder (iRBD) from healthy subjects with an impressive degree of accuracy, as demonstrated by an area under the curve (AUC) value of 0.88 using receiver operating characteristic (ROC) model. Furthermore, when applying the method to a multicenter cohort, this biomarker differentiated individuals with over 80% probability of occurrence of prodromal PD from individuals with <5% probability of developing prodromal PD or healthy controls, both with AUC values of 0.80. The robust predictive power of α-synuclein from L1EV for distinguishing high-risk subjects from healthy controls was further underscored by an AUC value of 0.90.³

In addition, the study demonstrated that subjects with multiple prodromal markers expressed higher levels of L1EV derived α-synuclein, especially in those with an abnormal dopamine transporter single-photon emission computed tomography (DAT- SPECT), suggesting that the simultaneous measurement of L1EV α-synuclein and specific prodromal markers could improve the stratification of at-risk individuals. Remarkably, the study also found that approximately 80% of the cases that eventually phenoconverted to PD or related Lewy body diseases exhibited L1EV α-synuclein levels higher than the derived threshold, further emphasizing the potential utility of this biomarker to discover the individuals at the highest risk of developing PD.

In addition to its diagnostic potential, the study highlighted the positive correlation between increased L1EV α-synuclein levels and positive results

High-density neural recordings with superior spatiotemporal resolution powerfully unveil cellular-scale neural communication, showing great promise in neural science, translational medicine, and clinical applications. To achieve such, many design and fabrication innovations enhanced the electrode, chip, or both for biocompatibility improvement, electrical performance upgrade, and size miniaturization, offering several thousands of recording sites. However, an enormous gap exists along the trajectory toward billions of recording sites for brain scale resolution, posing many more design challenges. This review tries to find possible insight into mitigating the gap by discussing the latest progress in high-density electrodes and chips for neural recordings. It emphasizes the design, fabrication, bonding techniques, and in vivo performance optimization of high-density electrodes. It discusses the promising opportunities for circuit-level and architecture-level multi-channel chip design innovations. We expect that joint effort and close collaboration between high-density electrodes and chips will pave the way to high-resolution neural recording tools supporting cutting-edge neuroscience discoveries and applications.