Applications of nanobodies in brain diseases

Frontiers in Immunology, Journal Year: 2022, Volume and Issue: 13

Published: Nov. 8, 2022

Nanobodies are antibody fragments derived from camelids, naturally endowed with properties like low molecular weight, high affinity and immunogenicity, which contribute to their effective use as research tools, but also diagnostic therapeutic agents in a wide range of diseases, including brain diseases. Also, the success Caplacizumab, first approved nanobody drug was established first-in-class medication treat acquired thrombotic thrombocytopenic purpura, nanobody-based therapy has received increasing attention. In current review, we briefly introduce characterization manufacturing nanobodies. Then, discuss issue crossing brain-blood-barrier (BBB) by nanobodies, making natural methods BBB penetration, passive diffusion, active efflux carriers (ATP-binding cassette transporters), carrier-mediated influx via solute transcytosis (including receptor-mediated transport, adsorptive mediated transport) well various physical chemical or even more complicated such genetic viral vectors deliver nanobodies brain. Next, give an extensive overview research, applications brain-related emphasis on Alzheimer’s disease, Parkinson’s tumors. Thanks advance engineering modification technologies, can be linked toxins conjugated radionuclides, photosensitizers nanoparticles, according different requirements. Finally, provide several perspectives that may facilitate future studies whereby versatile offer promising for advancing our knowledge about disorders, hopefully yielding solutions.

Language: Английский

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Development and validation of a deep-learning model for detecting brain metastases on 3D post-contrast MRI: a multi-center multi-reader evaluation study

Neuro-Oncology, Journal Year: 2022, Volume and Issue: 24(9), P. 1559 - 1570

Published: Jan. 27, 2022

Accurate detection is essential for brain metastasis (BM) management, but manual identification laborious. This study developed, validated, and evaluated a BM (BMD) system.Five hundred seventy-three consecutive patients (10 448 lesions) with newly diagnosed BMs 377 without were retrospectively enrolled to develop multi-scale cascaded convolutional network using 3D-enhanced T1-weighted MR images. BMD was validated prospective validation set comprising an internal (46 349 lesions; 44 BMs) three external sets (102 717 108 BMs). The lesion-based sensitivity the number of false positives (FPs) per patient analyzed. reading time trainees experienced radiologists from hospitals set.The FPs 95.8% 0.39 in test set, 96.0% 0.27 ranged 88.9% 95.5% 0.29 0.66 sets. system achieved higher (93.2% [95% CI, 91.6-94.7%]) than all (ranging 68.5% 65.7-71.3%] 80.4% 78.0-82.8%], P < .001). Radiologist improved BMD, reaching 92.7% 95.0%. mean reduced by 47% 32% assisted relative that BMD.BMD enables accurate detection. Reading improves radiologists' reduces their times.

Language: Английский

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Deep Learning for Detecting Brain Metastases on MRI: A Systematic Review and Meta-Analysis

Cancers, Journal Year: 2023, Volume and Issue: 15(2), P. 334 - 334

Published: Jan. 4, 2023

Since manual detection of brain metastases (BMs) is time consuming, studies have been conducted to automate this process using deep learning. The purpose study was conduct a systematic review and meta-analysis the performance learning models that use magnetic resonance imaging (MRI) detect BMs in cancer patients. A search MEDLINE, EMBASE, Web Science until 30 September 2022. Inclusion criteria were: patients with BMs; MRI images applied sufficient data were present terms detective performance; original research articles. Exclusion reviews, letters, guidelines, editorials, or errata; case reports series less than 20 patients; overlapping cohorts; insufficient machine used articles not written English. Quality Assessment Diagnostic Accuracy Studies-2 Checklist for Artificial Intelligence Medical Imaging assess quality. Finally, 24 eligible identified quantitative analysis. pooled proportion patient-wise lesion-wise detectability 89%. Articles should adhere checklists more strictly. Deep algorithms effectively BMs. Pooled analysis false positive rates could be estimated due reporting differences.

Language: Английский

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Choroid plexus mast cells drive tumor-associated hydrocephalus

Cell, Journal Year: 2023, Volume and Issue: 186(26), P. 5719 - 5738.e28

Published: Dec. 1, 2023

Language: Английский

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Breast Cancer with Brain Metastasis: Molecular Insights and Clinical Management

Genes, Journal Year: 2023, Volume and Issue: 14(6), P. 1160 - 1160

Published: May 26, 2023

Breast cancer is the most frequently diagnosed malignancy worldwide and leading cause of cancer-related death among women. Brain metastases are a primary contributor to mortality, as they often go undetected until late stages due their dormant nature. Moreover, clinical management brain complicated by relevant issue blood-brain barrier penetration. The molecular pathways involved in formation, progression, colonization breast tumors subsequent diverse, posing significant hurdles heterogeneous nature subtypes. Despite advancements treatments, prognosis for patients with remains poor. In this review, we aim highlight biological mechanisms evaluating multi-step genetic discuss currently available emerging treatment strategies propose prospective overview complex disease.

Language: Английский

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