Multimodal Identification of Alzheimer's Disease: A Review

Alzheimer's disease is a progressive neurological disorder characterized by cognitive impairment and memory loss. With the increasing aging population, the incidence of AD is continuously rising, making early diagnosis and intervention an urgent need. In recent years, a considerable number of teams have applied computer-aided diagnostic techniques to early classification research of AD. Most studies have utilized imaging modalities such as magnetic resonance imaging (MRI), positron emission tomography (PET), and electroencephalogram (EEG). However, there have also been studies that attempted to use other modalities as input features for the models, such as sound, posture, biomarkers, cognitive assessment scores, and their fusion. Experimental results have shown that the combination of multiple modalities often leads to better performance compared to a single modality. Therefore, this paper will focus on different modalities and their fusion, thoroughly elucidate the mechanisms of various modalities, explore which methods should be combined to better harness their utility, analyze and summarize the literature in the field of early classification of AD in recent years, in order to explore more possibilities of modality combinations

Unlocking the enigma: unraveling multiple cognitive dysfunction linked to glymphatic impairment in early Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) is one of the world’s well-known neurodegenerative diseases, which is related to the balance mechanism of production and clearance of two proteins (amyloid-β and tau) regulated by the glymphatic system. Latest studies have found that AD patients exhibit impairments to their glymphatic system. However, the alterations in the AD disease continuum, especially in the early stages, remain unclear. Moreover, the relationship between the glymphatic system and cognitive dysfunction is still worth exploring.MethodsA novel diffusion tensor image analysis method was applied to evaluate the activity of the glymphatic system by an index for diffusivity along the perivascular space (ALPS-index). Based on this method, the activity of the glymphatic system was noninvasively evaluated in 300 subjects, including 111 normal controls (NC), 120 subjects with mild cognitive impairment (MCI), and 69 subjects with AD. Partial correlation analysis was applied to explore the association between glymphatic system and cognitive impairment based on three domain-general scales and several domain-specific cognitive scales. Receiver operating characteristic curve analysis was used to evaluate the classification performance of ALPS-index along the AD continuum.ResultsALPS-index was significantly different among NC, MCI and AD groups, and ALPS-index decreased with cognitive decline. In addition, ALPS-index was significantly correlated with the scores of the clinical scales (p<0.05, FDR corrected), especially in left hemisphere. Furthermore, combination of ALPS and fractional anisotropy (FA) values achieved better classification results (NC vs. MCI: AUC = 0.6610, NC vs. AD: AUC = 0.8214).ConclusionHere, we show that the glymphatic system is closely associated with multiple cognitive dysfunctions, and ALPS-index can be used as a biomarker for alterations along the AD continuum. This may provide new targets and strategies for the treatment of AD, and has the potential to assist clinical diagnosis

Application of Entity-BERT model based on neuroscience and brain-like cognition in electronic medical record entity recognition

IntroductionIn the medical field, electronic medical records contain a large amount of textual information, and the unstructured nature of this information makes data extraction and analysis challenging. Therefore, automatic extraction of entity information from electronic medical records has become a significant issue in the healthcare domain.MethodsTo address this problem, this paper proposes a deep learning-based entity information extraction model called Entity-BERT. The model aims to leverage the powerful feature extraction capabilities of deep learning and the pre-training language representation learning of BERT(Bidirectional Encoder Representations from Transformers), enabling it to automatically learn and recognize various entity types in medical electronic records, including medical terminologies, disease names, drug information, and more, providing more effective support for medical research and clinical practices. The Entity-BERT model utilizes a multi-layer neural network and cross-attention mechanism to process and fuse information at different levels and types, resembling the hierarchical and distributed processing of the human brain. Additionally, the model employs pre-trained language and sequence models to process and learn textual data, sharing similarities with the language processing and semantic understanding of the human brain. Furthermore, the Entity-BERT model can capture contextual information and long-term dependencies, combining the cross-attention mechanism to handle the complex and diverse language expressions in electronic medical records, resembling the information processing method of the human brain in many aspects. Additionally, exploring how to utilize competitive learning, adaptive regulation, and synaptic plasticity to optimize the model's prediction results, automatically adjust its parameters, and achieve adaptive learning and dynamic adjustments from the perspective of neuroscience and brain-like cognition is of interest.Results and discussionExperimental results demonstrate that the Entity-BERT model achieves outstanding performance in entity recognition tasks within electronic medical records, surpassing other existing entity recognition models. This research not only provides more efficient and accurate natural language processing technology for the medical and health field but also introduces new ideas and directions for the design and optimization of deep learning models

m6A modification patterns and tumor immune landscape in clear cell renal carcinoma

Background Recent studies have focused on the correlation between N6-methyladenosine (m6A) modification and specific tumor-infiltrating immune cells. However, the potential roles of m6A modification in the tumor immune landscape remain elusive.Methods We comprehensively evaluated the m6A modification patterns and tumor immune landscape of 513 clear cell renal cell carcinoma (ccRCC) patients, and correlated the m6A modification patterns with the immune landscape. The m6Ascore was established using principal component analysis. Multivariate Cox regression analysis was performed to evaluate the prognostic value of the m6Ascore.Results We identified three m6Aclusters—characterized by differences in Th17 signature, extent of intratumor heterogeneity, overall cell proliferation, aneuploidy, expression of immunomodulatory genes, overall somatic copy number alterations, and prognosis. The m6Ascore was established to quantify the m6A modification pattern of individual ccRCC patients. Further analyses revealed that the m6Ascore was an independent prognostic factor of ccRCC. Finally, we verified the prognostic value of the m6Ascore in the programmed cell death protein 1 (PD-1) blockade therapy of patients with advanced ccRCC.Conclusions This study demonstrated the correlation between m6A modification and the tumor immune landscape in ccRCC. The comprehensive evaluation of m6A modification patterns in individual ccRCC patients enhances our understanding of the tumor immune landscape and provides a new approach toward new and improved immunotherapeutic strategies for ccRCC patients

Characterization of a novel hemolytic activity of human IgG fractions arising from diversity in protein and oligosaccharide components.

Human IgG is a well-established multifunctional antigen specific immunoglobulin molecule of the adaptive immune system. However, an antigen nonspecific immunological function of human IgG has never been reported. In this study, human IgG was isolated using ammonium sulfate fractional precipitation and diethylaminoethanol (DEAE) cellulose 52 ion exchange chromatography, from which h-IgG and hs-IgG fractions were purified on the basis of their differential binding to rabbit anti-shrimp hemocyanin antibody (h) and rabbit anti-shrimp hemocyanin's small subunit antibody (hs), respectively. We found that h-IgG had a higher hemolytic activity than hs-IgG against erythrocytes from humans, rabbits, mice and chickens, whereas the control IgG showed negligible activity. h-IgG could interact directly with erythrocyte membranes, and this interaction was suppressed by high molecular weight osmoprotectants, showing that it may follow a colloid-osmotic mechanism. In comparative proteomics and glycomics studies, h-IgG and hs-IgG yielded 20 and 5 significantly altered protein spots, respectively, on a 2-D gel. The mean carbohydrate content of h-IgG and hs-IgG was approximately 3.6- and 2-fold higher than that of IgG, respectively, and the α-d-mannose/α-d-glucose content was in the order of h-IgG>hs-IgG>IgG. In this study, a novel antigen nonspecific immune property of human IgG was investigated, and the diversity in the protein constituents and glycosylation levels may have functional signficance

Litopenaeus vannamei hemocyanin exhibits antitumor activity in S180 mouse model in vivo.

Hemocyanin is a multifunctional glycoprotein, which also plays multiple roles in immune defense. While it has been demonstrated that hemocyanin from some mollusks can induce potent immune response and is therefore undergoing clinical trials to be used in anti-tumor immunotherapy, little is currently known about how hemocyanin from arthropods affect tumors. In this study we investigated the anti-tumor activity of hemocyanin from Litopenaeus vannamei on Sarcoma-180 (S180) tumor-bearing mice model. Eight days treatment with 4mg/kg bodyweight of hemocyanin significantly inhibited the growth of S180 up to 49% as compared to untreated. Similarly, histopathology analysis showed a significant decrease in tumor cell number and density in the tissues of treated mice. Moreover, there was a significant increase in immune organs index, lymphocyte proliferation, NK cell cytotoxic activity and serum TNF-α level, suggesting that hemocyanin could improve the immunity of the S180 tumor-bearing mice. Additionally, there was a significant increase in superoxide dismutase (SOD) activity and a decrease in the level of malondialdehyde (MDA) in serum and liver, which further suggest that hemocyanin improved the anti-oxidant ability of the S180 tumor-bearing mice. Collectively, our data demonstrated that L. vannamei hemocyanin had a significant antitumor activity in mice

Reliability of nephrolithometric nomograms in patients treated with minimally invasive percutaneous nephrolithotomy: A precision study

Objectives: The study aimed to evaluate quality of nephrolithometric nomograms to predict stone-free rates (SFRs) and complication rates (CRs) in case of minimally invasive percutaneous nephrolithotomy (PNL). In the last decade, nomograms have been introduced to estimate the SFRs and CRs of PNL. However, no data are available regarding their reliability in case of utilization of miniaturized devices. Herein we present a prospective multicentric study to evaluate reliability of Guy’s stone score (GSS), the stone size, tract length, obstruction, number of involved calyces, and essence of stone (S.T.O.N.E.) nephrolithometry score and Clinical Research Office of the Endourological Society (CROES) score in patients treated with minimally invasive PNL. Methods: We evaluated SFRs and CRs of 222 adult patients treated with miniaturized PNL. Patients were considered stone-free if no residual fragments of any size at post-operative unenhanced computed tomography scan. Patients demographics, SFRs, and CRs were reported and analyzed. Performances of nomograms were evaluated with the area under the curve (AUC). Results: We included 222 patients, the AUCs of GSS, CROES score, and S.T.O.N.E. nephrolithometry score were 0.69 (95% confidence interval [CI] 0.61–0.78), 0.64 (95% CI 0.56–0.73), and 0.62 (95% CI 0.52–0.71), respectively. Regarding SFRs, at multivariate binomial logistic regression, only the GSS had significance with an odds ratio of 0.53 (95% CI 0.31–0.95, p=0.04). We did not find significant correlation with complications, with only a trend for GSS. Conclusion: This is the first study evaluating nomograms in miniaturized PNL. They still show good reliability; however, our data showed lower performances compared to standard PNL. We emphasize the need of further studies to confirm this trend. A dedicated nomogram for minimally invasive PNL may be necessary

Osmotic protection against hemolysis by various osmoprotectants.

<p>0.9-IgG (0.01 mg/ml) was incubated with 0.3 ml of 0.5% (v/v) chicken erythrocytes at 37°C for 1 h in the presence of various osmoprotectants. h-IgG incubated with chicken erythrocytes without osmoprotectant was used as a 100% hemolysis control. Data are expressed as means ± SD (n≥3). ** indicates a significant difference as compared to the control (<i>P</i><0.01).</p

Hemolysis of inhomogeneous erythrocytes by different human IgG fractions.

<p>These data represent the mean ± SD of at least three separate experiments. We incubated 0.9 ml of 0.01 mg/ml IgG fractions with 0.3 ml of 0.5% (v/v) erythrocyte suspension at 37°C for 1 h.</p>**<p>indicates a significant difference as compared to the control IgG (<i>P</i><0.01).</p

Multiple amino acid sequence alignments between human IgG and hemolysins.

<p>Black and gray show 100% and above 50% homology, respectively. GenBank accession numbers are: human IgG (AAA02914), hemolysin from <i>Serratia marcescens</i> (AAA50323), hemolysin from <i>Edwardsiella tarda</i> (ZP_06713740) and hemolysin from <i>Xenorhabdus bovienii</i> (YP_003466207).</p