A reproducible 3D convolutional neural network with dual attention module (3D-DAM) for Alzheimer's disease classification

Alzheimer's disease is one of the most common types of neurodegenerative disease, characterized by the accumulation of amyloid-beta plaque and tau tangles. Recently, deep learning approaches have shown promise in Alzheimer's disease diagnosis. In this study, we propose a reproducible model that utilizes a 3D convolutional neural network with a dual attention module for Alzheimer's disease classification. We trained the model in the ADNI database and verified the generalizability of our method in two independent datasets (AIBL and OASIS1). Our method achieved state-of-the-art classification performance, with an accuracy of 91.94% for MCI progression classification and 96.30% for Alzheimer's disease classification on the ADNI dataset. Furthermore, the model demonstrated good generalizability, achieving an accuracy of 86.37% on the AIBL dataset and 83.42% on the OASIS1 dataset. These results indicate that our proposed approach has competitive performance and generalizability when compared to recent studies in the field

Association of factor XIII Val34Leu polymorphism and coronary artery disease: A meta-analysis

Background: Factor XIII plays an important role in the stabilization of the linkage between fibrins and in the pathophysiology of coronary artery disease (CAD). The association between factor XIII Val34Leu polymorphism and CAD risk remains controversial. Methods: We conducted a meta-analysis of 36 studies involving 26,940 cases and 34,694 controls. Subgroup analyses were performed with division of data into disease (myocardial infarction [MI], CAD without MI), age, and sex. Results: Factor XIII Val34Leu polymorphism was significantly associated with ove all CAD risk (odds ratio [OR] = 1.09, 95% confidence interval [CI] = 1.03–1.06, p = 0.004) and MI risk (OR = 1.15, 95% CI 1.07–1.25, p = 0.0003), but not with CAD without MI risk (OR = 1.00, 95% CI 0.87–1.15, p = 0.96). In the subgroup analysis by age and sex, there was no association between Val34Leu polymorphism and CAD. Conclusions: This meta-analysis found that factor XIII Val34Leu polymorphism was associated with CAD risk, especially MI, but not with CAD without MI. In addition, age and sex did not affect the relationship between factor XIII Val34Leu polymorphism and CAD risk.

Utilization of a combined EEG/NIRS system to predict driver drowsiness

The large number of automobile accidents due to driver drowsiness is a critical concern of many countries. To solve this problem, numerous methods of countermeasure have been proposed. However, the results were unsatisfactory due to inadequate accuracy of drowsiness detection. In this study, we introduce a new approach, a combination of EEG and NIRS, to detect driver drowsiness. EEG, EOG, ECG and NIRS signals have been measured during a simulated driving task, in which subjects underwent both awake and drowsy states. The blinking rate, eye closure, heart rate, alpha and beta band power were used to identify subject’s condition. Statistical tests were performed on EEG and NIRS signals to find the most informative parameters. Fisher’s linear discriminant analysis method was employed to classify awake and drowsy states. Time series analysis was used to predict drowsiness. The oxy-hemoglobin concentration change and the beta band power in the frontal lobe were found to differ the most between the two states. In addition, these two parameters correspond well to an awake to drowsy state transition. A sharp increase of the oxy-hemoglobin concentration change, together with a dramatic decrease of the beta band power, happened several seconds before the first eye closure

Vision transformers for the prediction of mild cognitive impairment to Alzheimer’s disease progression using mid-sagittal sMRI

BackgroundAlzheimer’s disease (AD) is one of the most common causes of neurodegenerative disease affecting over 50 million people worldwide. However, most AD diagnosis occurs in the moderate to late stage, which means that the optimal time for treatment has already passed. Mild cognitive impairment (MCI) is an intermediate state between cognitively normal people and AD patients. Therefore, the accurate prediction in the conversion process of MCI to AD may allow patients to start preventive intervention to slow the progression of the disease. Nowadays, neuroimaging techniques have been developed and are used to determine AD-related structural biomarkers. Deep learning approaches have rapidly become a key methodology applied to these techniques to find biomarkers.MethodsIn this study, we aimed to investigate an MCI-to-AD prediction method using Vision Transformers (ViT) to structural magnetic resonance images (sMRI). The Alzheimer’s Disease Neuroimaging Initiative (ADNI) database containing 598 MCI subjects was used to predict MCI subjects’ progression to AD. There are three main objectives in our study: (i) to propose an MRI-based Vision Transformers approach for MCI to AD progression classification, (ii) to evaluate the performance of different ViT architectures to obtain the most advisable one, and (iii) to visualize the brain region mostly affect the prediction of deep learning approach to MCI progression.ResultsOur method achieved state-of-the-art classification performance in terms of accuracy (83.27%), specificity (85.07%), and sensitivity (81.48%) compared with a set of conventional methods. Next, we visualized the brain regions that mostly contribute to the prediction of MCI progression for interpretability of the proposed model. The discriminative pathological locations include the thalamus, medial frontal, and occipital—corroborating the reliability of our model.ConclusionIn conclusion, our methods provide an effective and accurate technique for the prediction of MCI conversion to AD. The results obtained in this study outperform previous reports using the ADNI collection, and it suggests that sMRI-based ViT could be efficiently applied with a considerable potential benefit for AD patient management. The brain regions mostly contributing to prediction, in conjunction with the identified anatomical features, will support the building of a robust solution for other neurodegenerative diseases in future

Non-invasive measurement of hemodynamic change during 8 MHz transcranial focused ultrasound stimulation using near-infrared spectroscopy

Background: Transcranial focused ultrasound (tFUS) attracts wide attention in neuroscience as an effective noninvasive approach to modulate brain circuits. In spite of this, the effects of tFUS on the brain is still unclear, and further investigation is needed. The present study proposes to use near-infrared spectroscopy (NIRS) to observe cerebral hemodynamic change caused by tFUS in a noninvasive manner. Results: The results show a transient increase of oxyhemoglobin and decrease of deoxyhemoglobin concentration in the mouse model induced by ultrasound stimulation of the somatosensory cortex with a frequency of 8 MHz but not in sham. In addition, the amplitude of hemodynamics change can be related to the peak intensity of the acoustic wave. Conclusion: High frequency 8 MHz ultrasound was shown to induce hemodynamic changes measured using NIRS through the intact mouse head. The implementation of NIRS offers the possibility of investigating brain response noninvasively for different tFUS parameters through cerebral hemodynamic change. © 2019 The Author(s).1

Transantral Orbital Floor Fracture Repair Using a Folded Silastic Tube

ObjectivesThe purpose of this study was to evaluate the advantages and limitations of using a silicon tube to support the fractured orbital floor by a transantral approach.MethodsA retrospective study was conducted from January 2000 to December. 2011 in 51 patients with pure orbital floor fractures. The patients underwent reduction surgery via a transantral approach for inserting a folded silastic tube to support the fractured orbital floor in the maxillary sinus. A chart review of preoperative and postoperative ocular symptoms, operation records, and complications was maintained.ResultsIn 18 out of 25 patients with diplopia, postoperative improvement was seen. In 13 out of 15 patients with extraocular muscle limitation, postoperative improvement was seen. Enophthalmos resolved postoperatively in four of five patients. Postsurgical complications occurred in three patients: an overcorrection, an infection in the maxillary sinus, and an implant extrusion, all of which were resolved by revision surgeries.ConclusionDuring the course of the study, we sensed reduction using a folded silastic tube via a transantral approach as an easy and effective technique with good postoperative results, and minimal implant related complications. This novel procedure is recommended as a surgical option for the reduction of orbital floor fractures

Low-Cost Compact Diffuse Speckle Contrast Flowmeter Using Small Laser Diode and Bare Charge-Coupled-Device

We report a low-cost compact diffuse speckle contrast flowmeter (DSCF) consisting of a small laser diode and a bare charge-coupled-device (CCD) chip, which can be used for contact measurements of blood flow variations in relatively deep tissues (up to ∼8  mm). Measurements of large flow variations by the contact DSCF probe are compared to a noncontact CCD-based diffuse speckle contrast spectroscopy and a standard contact diffuse correlation spectroscopy in tissue phantoms and a human forearm. Bland–Altman analysis shows no significant bias with good limits of agreement among these measurements: 96.5% ± 2.2% (94.4% to 100.0%) in phantom experiments and 92.8% in the forearm test. The relatively lower limit of agreement observed in the in vivo measurements (92.8%) is likely due to heterogeneous reactive responses of blood flow in different regions/volumes of the forearm tissues measured by different probes. The low-cost compact DSCF device holds great potential to be broadly used for continuous and longitudinal monitoring of blood flow alterations in ischemic/hypoxic tissues, which are usually associated with various vascular diseases

Difference in the Cobb Angle Between Standing and Supine Position as a Prognostic Factor After Vertebral Augmentation in Osteoporotic Vertebral Compression Fractures

Objective We retrospectively analyzed patients with osteoporotic vertebral compression fracture (OVCF) undergoing vertebral augmentation to compare the Cobb angle changes in the supine and standing positions and the clinical outcomes. Methods We retrospectively extracted the data of OVCF patients who underwent vertebral augmentation. Back pain was assessed using a visual analogue scale (VAS). Supine and standing radiographs were assessed before treatment to determine the Cobb angle and compression ratio. Receiver operating characteristic curve analysis was performed to determine the optimal cutoff to predict favorable outcomes after vertebral augmentation. Results A total of 249 patients were included. We observed a statistically significant increase in the VAS score change with increasing Cobb angle and compression ratio (p < 0.001), and multivariate logistic regression analysis showed that a difference in the Cobb angle (odds ratio [OR], 1.27) and compression ratio (OR, 1.12) were the independent risk factors for predicting short-term favorable outcomes after vertebral augmentation. In addition, we found that the difference in the Cobb angle (OR, 1.05) was the only factor for predicting midterm favorable outcomes after vertebral augmentation. The optimal cutoff value of the difference in the Cobb angle for predicting midterm favorable outcomes was 35.526°. Conclusion We found that the midterm clinical outcome after vertebral augmentation was better when there was a difference of approximately 35% or more in the Cobb angle between the standing and supine positions. Surgeons should pay attention to the difference in the Cobb angle depending on the posture when deciding to perform vertebral augmentation in patients with OVCFs

Refracture after locking compression plate removal in displaced midshaft clavicle fractures after bony union: a retrospective study

Background A midshaft clavicle fracture is a common fracture that typically responds well to open reduction and internal fixation (ORIF). However, refracture can occur after implant removal (IR). This study aimed to analyze the rate of refracture and related factors after removal of the locking compression plate (LCP) for displaced midshaft clavicle fractures. Methods We retrospectively reviewed the medical records of 201 patients who had undergone ORIF with LCP for midshaft clavicle fractures after IR after bony union from January 2011 to May 2018 at our institute. We evaluated basic demographic characteristics and radiographic parameters. All patients were treated with an LCP for primary fracture. The patients were divided into two groups: a refracture group that experienced a second fracture within 1 year after IR and a no-fracture group. Results There were four cases (1.99%) of refracture; three were treated conservatively, while one was treated surgically. All patients achieved bony union. The average interval between refracture and IR was 64 days (range, 6–210 days). There was a significant difference in classification of fractures (AO Foundation/Orthopaedic Trauma Association [AO/OTA] classification) between the two groups. However, other patient demographics and radiographic measurements between refracture and IR, such as bone diameter, showed no significant difference between the two groups. Conclusions This study showed that one in 50 patients suffered from refracture after removal of the LCP. Thus, if patients desire IR, the surgeon should explain that there is a relatively higher possibility of refracture for cases with simple or segmental fractures than for other types of fracture

Effects of transcranial ultrasound stimulation pulsed at 40 Hz on A beta plaques and brain rhythms in 5xFAD mice

Background: Alzheimer’s disease (AD) is the most common cause of dementia, and is characterized by amyloid-β (Aβ) plaques and tauopathy. Reducing Aβ has been considered a major AD treatment strategy in pharmacological and non-pharmacological approaches. Impairment of gamma oscillations, which play an important role in perception and cognitive function, has been shown in mouse AD models and human patients. Recently, the therapeutic effect of gamma entrainment in AD mouse models has been reported. Given that ultrasound is an emerging neuromodulation modality, we investigated the effect of ultrasound stimulation pulsed at gamma frequency (40 Hz) in an AD mouse model. Methods: We implanted electroencephalogram (EEG) electrodes and a piezo-ceramic disc ultrasound transducer on the skull surface of 6-month-old 5×FAD and wild-type control mice (n = 12 and 6, respectively). Six 5×FAD mice were treated with two-hour ultrasound stimulation at 40 Hz daily for two weeks, and the other six mice received sham treatment. Soluble and insoluble Aβ levels in the brain were measured by enzyme-linked immunosorbent assay. Spontaneous EEG gamma power was computed by wavelet analysis, and the brain connectivity was examined with phase-locking value and cross-frequency phase-amplitude coupling. Results: We found that the total Aβ42 levels, especially insoluble Aβ42, in the treatment group decreased in pre- and infra-limbic cortex (PIL) compared to that of the sham treatment group. A reduction in the number of Aβ plaques was also observed in the hippocampus. There was no increase in microbleeding in the transcranial ultrasound stimulation (tUS) group. In addition, the length and number of microglial processes decreased in PIL and hippocampus. Encelphalographic spontaneous gamma power was increased, and cross-frequency coupling was normalized, implying functional improvement after tUS stimulation. Conclusion: These results suggest that the transcranial ultrasound-based gamma-band entrainment technique can be an effective therapy for AD by reducing the Aβ load and improving brain connectivity. © 2021, The Author(s).1