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

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

CAMELLIA SPHAMII (THEACEAE, SECT. PIQUETIA), A NEW TAXON OF YELLOW FLOWER FROM LANGBIANG BIOSPHERE RESERVE, VIETNAM

Camellia sphamii is described and illustrated as a new species of section Piquetia from Hamasin village, D’ran town, Don Duong district, Lam Dong province, Vietnam. C. sphamii is similar to C. proensis (Quach, Luong et al., 2021) but differs from it in several morphological features: mature leaves cordate at base, young leaves purple; pericarp 7–8 mm thick with dense hair on the outer surface, flower buds ovate, ferruginous; sepals 5, hemisphere, concave, finely hairy on the outer surface, sparsely hairy on the inside, petals 7, finely hairy on the outer surface, with translucent margin, concave; style 5, ½ basally united; capsule 5 locular. Information on its phenology, distribution, ecology, and conservation status is also provided

Usporedba enzimske i ultrazvučne ekstrakcije albumina iz praha kondicioniranih sjemenki bundeve (Cucurbita pepo)

In this study, ultrasound- and enzyme-assisted extractions of albumin (water-soluble protein group) from defatted pumpkin (Cucurbita pepo) seed powder were compared. Both advanced extraction techniques strongly increased the albumin yield in comparison with conventional extraction. The extraction rate was two times faster in the ultrasonic extraction than in the enzymatic extraction. However, the maximum albumin yield was 16 % higher when using enzymatic extraction. Functional properties of the pumpkin seed albumin concentrates obtained using the enzymatic, ultrasonic and conventional methods were then evaluated. Use of hydrolase for degradation of cell wall of the plant material did not change the functional properties of the albumin concentrate in comparison with the conventional extraction. The ultrasonic extraction enhanced water-holding, oil-holding and emulsifying capacities of the pumpkin seed albumin concentrate, but slightly reduced the foaming capacity, and emulsion and foam stability.U ovom su radu uspoređena dva postupka izolacije albumina, proteina topljivog u vodi, iz praha kondicioniranih sjemenki bundeve (Cucurbita pepo), i to ekstrakcijom pomoću ultrazvuka te pomoću enzima. U usporedbi s konvencionalnom ekstrakcijom, oba su postupka znatno povećala prinos albumina. Ultrazvučna je ekstrakcija bila dva puta brža od enzimske, međutim, najveći je prinos albumina od 16 % dobiven enzimskom ekstrakcijom. Ispitana su funkcionalna svojstva koncentrata albumina dobivenog iz sjemenki bundeve enzimskom, ultrazvučnom i konvencionalnom ekstrakcijom. Enzimska hidroliza nije utjecala na funkcionalna svojstva koncentrata albumina, za razliku od konvencionalne ekstrakcije. Ultrazvučnom su ekstrakcijom poboljšana svojstva zadržavanja vode i ulja te emulgiranja, a neznatno smanjena svojstva pjenjenja te stabilnost pjene i emulzije koncentrata albumina

Association between ACE I/D genetic polymorphism and the severity of coronary artery disease in Vietnamese patients with acute myocardial infarction

BackgroundThe severity of coronary artery disease is a prognostic factor for major adverse cardiovascular events in patients diagnosed with acute myocardial infarction. ACE I/D polymorphism is one of the genetic factors that may affect the severity of coronary artery disease. This study aimed to investigate the association between ACE I/D genotypes and the severity of coronary artery disease in patients with acute myocardial infarction.Materials and methodsA single-center, prospective, observational study was conducted at the Department of Cardiology and Department of Interventional Cardiology, Cho Ray Hospital, Ho Chi Minh City, Vietnam from January 2020 to June 2021. All participants diagnosed with acute myocardial infarction underwent contrast-enhanced coronary angiography. The severity of coronary artery disease was determined by Gensini score. ACE I/D genotypes were identified in all subjects by using the polymerase chain reaction method.ResultsA total of 522 patients diagnosed with first acute myocardial infarction were recruited. The patients' median Gensini score was 34.3. The II, ID, and DD genotype rates of ACE I/D polymorphism were 48.9%, 36.4%, and 14.7%, respectively. After adjusting for confounding factors, multivariable linear regression analysis showed that the ACE DD genotype was independently associated with a higher Gensini score compared with the II or ID genotypes.ConclusionThe DD genotype of the ACE I/D polymorphism was associated with the severity of coronary artery disease in Vietnamese patients diagnosed with first acute myocardial infarction

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