Background: MRI is the most commonly used imaging method for diagnosing anterior cruciate ligament (ACL) injuries. However, the interpretation of knee MRI is time-intensive and depends on the clinical experience of the reader. An automated detection system based on a deep-learning algorithm may improve interpretation time and reliability. Purpose: To determine the feasibility of using a deep learning approach to detect ACL injuries within the knee joint on MRI. Study Type: Retrospective. Population: In all, 163 subjects with an ACL tear and 245 subjects with an intact ACL. There were 285, 81, and 42 volumes for training, validation, and test sets, respectively. Field Strength/Sequence: 2D sagittal proton density-weighted spectral attenuated inversion recovery sequences at 1.5T and 3.0T. Assessment: Based on the architecture of 3D DenseNet, we constructed a classification convolutional neural network. We tested this deep learning approach with different inputs and two other algorithms, including VGG16 and ResNet. Then we had both inexperienced radiologists and senior radiologists read the MR images. Statistical Tests: Using arthroscopic results as the reference standard, the performance of three different inputs and three different algorithms, the residents and senior radiologists assessed the classification accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC). Results: The accuracy, sensitivity, specificity, PPV, and NPV of our customized 3D deep learning architecture was 0.957, 0.976, 0.944, 0.940, and 0.976, respectively. The average AUCs were 0.946, 0.859, 0.960 for ResNet, VGG16, and our proposed network, respectively. The diagnostic accuracy of our model, residents, and senior radiologists was 0.957, 0.814, and 0.899, respectively. Data Conclusion: Our study demonstrated the feasibility of using an automated deep-learning-based detection system to evaluate ACL injury. Level of Evidence: 3 Technical Efficacy Stage: 1
Photodynamic therapy (PDT) has been widely used in cancer treatment. However, hypoxia in most solid tumors seriously restricts the efficacy of PDT. To improve the hypoxic microenvironment, we designed a novel mesoporous platinum (mPt) nanoplatform to catalyze hydrogen peroxide (H 2 O 2 ) within the tumor cells in situ without an extra enzyme. During the fabrication, the carboxy terminus of the photosensitizer chlorin e6 (Ce6) was connected to the amino terminus of the bifunctional mercaptoaminopolyglycol (SH-PEG-NH 2 ) by a condensation reaction, and then PEG-Ce6 was modified onto the mPt moiety via the mercapto terminal of SH-PEG-NH 2 . Material, cellular and animal experiments demonstrated that Pt@PEG-Ce6 catalyzed H 2 O 2 to produce oxygen (O 2 ) and that Ce6 transformed O 2 to generate reactive oxygen species (ROS) upon laser irradiation. The Pt@PEG-Ce6 nanoplatform with uniform diameter presented good biocompatibility and efficient tumor accumulation. Due to the high atomic number and good near-infrared absorption for Pt, this Pt@PEG-Ce6 nanoplatform showed computed tomography (CT) and photoacoustic (PA) dual-mode imaging ability, thus providing an important tool for monitoring the tumor hypoxic microenvironment. Moreover, the Pt@PEG-Ce6 nanoplatform reduced the expression of hypoxia-inducible factor-1 α (HIF-1 α ) and programmed death-1 (PD-1) in tumors, discussing the relationship between hypoxia, PD-1, and PDT for the first time.
Alzheimer’s disease (AD) is a neurodegenerative disease caused by neurons damage in the brain, and it poses a serious threat to human life and health. No efficient treatment is available, but early diagnosis, discovery, and intervention are still crucial, effective strategies. In this study, an electrochemical sensing platform based on a superwettable microdroplet array was developed to detect multiple AD biomarkers containing Aβ40, Aβ42, T-tau, and P-tau181 of blood. The platform integrated a superwettable substrate based on nanoAu-modified vertical graphene (VG@Au) into a working electrode, which was mainly used for droplet sample anchoring and electrochemical signal generation. In addition, an electrochemical micro-workstation was used for signals conditioning. This superwettable electrochemical sensing platform showed high sensitivity and a low detection limit due to its excellent characteristics such as large specific surface, remarkable electrical conductivity, and good biocompatibility. The detection limit for Aβ40, Aβ42, T-tau, and P-tau181 were 0.064, 0.012, 0.039, and 0.041 pg/ml, respectively. This study provides a promising method for the early diagnosis of AD.
Lupus nephritis (LN) is a common and refractory inflammation of the kidneys caused by systemic lupus erythematosus. Diagnosis and therapies at this stage are inefficient or have severe side effects. In recent years, nanomedicines show great potential for imaging diagnosis and controlled drug release. Herein, we developed a polydopamine (PDA)-based nanocarrier modified with Fe3O4 and Pt nanoparticles and loaded with necrostatin-1 (Nec-1) for the bimodal imaging and therapy of LN. Results demonstrate that Nec-1/PDA@Pt-Fe3O4 nanocarrier exhibits good biocompatibility. Nec-1, as an inhibitor of receptor-interacting protein 1 kinase, can be used to inhibit receptor-interacting protein 1 kinase activity and then reduces inflammation due to LN. Experiments in vitro and in the LN mouse model confirmed that the nanocarrier can reduce neutrophil extracellular traps (NETs) production by RIPK1 and alleviate the progression of inflammation. Previous studies proved that Pt nanoparticles can catalyze H2O2 to produce oxygen. A blood oxygen graph of mouse photoacoustic tomography confirmed that Nec-1/PDA@Pt-Fe3O4 can generate oxygen to fight against the hypoxic microenvironment of LN. PDA and Fe3O4 are used as photographic developers for photoacoustic or magnetic resonance imaging. The preliminary imaging results support Nec-1/PDA@Pt-Fe3O4 potential for photoacoustic/magnetic resonance dual-mode imaging, which can accurately and non-invasively monitor microscopic changes due to diseases. Nec-1/PDA@Pt-Fe3O4 combining these advantages exhibited outstanding performance in LN imaging and therapy. This work offers valuable insights into LN diagnosis and therapy.
Alzheimer’s disease (AD) is a long-term neurodegenerative disease that poses a serious threat to human life and health. It is very important to develop a portable quantitative device for AD diagnosis and personal healthcare. Herein, we develop a portable electrochemical sensing platform for the point-of-care detection of AD biomarkers in the blood. Such a portable platform integrates nanoAu-modified vertical graphene (VG@Au) into a working electrode, which can significantly improve sensitivity and reduce detection limit due to the large specific surface, excellent electrical conductivity, high stability, and good biocompatibility. The tau protein, as an important factor in the course of AD, is selected as a key AD biomarker. The results show that the linear range of this sensing platform is 0.1 pg/mL to 1 ng/mL, with a detection limit of 0.034 pg/mL (S/N = 3), indicating that this portable sensing platform meets the demand for the detection of the tau protein in the blood. This work offers great potential for AD diagnosis and personal healthcare.
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