Sleep stages classification by fusing the time-related synchronization analysis and brain activations.

Sleep staging plays an important role in the diagnosis and treatment of clinical sleep disorders. The sleep staging standard defines every 30 seconds as a sleep period, which may mean that there exist similar brain activity patterns during the same sleep period. Thus, in this work, we propose a novel time-related synchronization analysis framework named time-related multimodal sleep scoring model (TRMSC) to explore the potential time-related patterns of sleeping. In the proposed TRMSC, the time-related synchronization analysis is first conducted on the single channel electrophysiological signal, i.e., Electroencephalogram (EEG) and Electrooculogram (EOG), to explore the time-related patterns, and the spectral activation features are also extracted by spectrum analysis to obtain the multimodal features. With the extracted multimodal features, the feature fusion and selection strategy is utilized to obtain the optimal feature set and achieve robust sleep staging. To verify the effectiveness of the proposed TRMSC, sleep staging experiments were conducted on the Sleep-EDF dataset, and the experimental results indicate that the proposed TRMSC has achieved better performance than other existing strategies, which proves that the time-related synchronization features can make up for the shortcomings of traditional spectrum-based strategies and achieve a higher classification accuracy. The proposed TRMSC model may be helpful for portable sleep analyzers and provide a new analytical method for clinical sleeping research.

EEG based emotion recognition by hierarchical bayesian spectral regression framework.

Spectral regression (SR), a graph-based learning regression model, can be used to extract features from graphs to realize efficient dimensionality reduction. However, due to the SR method remains a regularized least squares problem and being defined in L2-norm space, the effect of artifacts in EEG signals cannot be efficiently resisted. In this work, to further improve the robustness of the graph-based regression models, we propose to utilize the prior distribution estimation in the Bayesian framework and develop a robust hierarchical Bayesian spectral regression framework (named HB-SR), which is designed with the hierarchical Bayesian ensemble strategies. In the proposed HB-SR, the impact of noises can be effectively reduced by the adaptive adjustment approach in model parameters with the data-driven manner. Specifically, in the current work, three different distributions have been elaborately designed to enhance the universality of the proposed HB-SR, i.e., Gaussian distribution, Laplace distribution, and Student-t distribution. To objectively evaluate the performance of the HB-SR framework, we conducted both simulation studies and emotion recognition experiments based on emotional EEG signals. Experimental results have consistently indicated that compared with other existing spectral regression methods, the proposed HB-SR can effectively suppress the influence of noises and achieve robust EEG emotion recognition.

A hybrid graph network model for ASD diagnosis based on resting-state EEG signals.

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder and early diagnosis is crucial for effective treatment. Stable and effective biomarkers are essential for understanding the underlying causes of the disorder and improving diagnostic accuracy. Electroencephalography (EEG) signals have proven to be reliable biomarkers for diagnosing ASD. Extracting stable connectivity patterns from EEG signals helps ensure robustness in ASD diagnostic systems. In this study, we propose a hybrid graph convolutional network framework called Rest-HGCN, which utilizes resting-state EEG signals to capture differential patterns of brain connectivity between normal children and ASD patients using graph learning strategies. The Rest-HGCN combines brain network analysis techniques and data-driven strategies to extract discriminative graph features from resting-state EEG signals. By automatically extracting differential graph patterns from these signals, the Rest-HGCN achieves reliable ASD diagnosis. To evaluate the performance of Rest-HGCN, we conducted ASD diagnosis experiments using k-fold cross-validation on the public ABC-CT resting EEG dataset. The proposed Rest-HGCN model achieved accuracies of 87.12 % and 85.32 % in single-subject and cross-experiment analyses, respectively. The results suggest that Rest-HGCN can effectively capture discriminant graph patterns from resting EEG signals and achieve robust ASD diagnosis. This may provide an effective and convenient tool for clinical ASD diagnosis.

Survival strategies: How tumor hypoxia microenvironment orchestrates angiogenesis.

During tumor development, the tumor itself must continuously generate new blood vessels to meet their growth needs while also allowing for tumor invasion and metastasis. One of the most common features of tumors is hypoxia, which drives the process of tumor angiogenesis by regulating the tumor microenvironment, thus adversely affecting the prognosis of patients. In addition, to overcome unsuitable environments for growth, such as hypoxia, nutrient deficiency, hyperacidity, and immunosuppression, the tumor microenvironment (TME) coordinates angiogenesis in several ways to restore the supply of oxygen and nutrients and to remove metabolic wastes. A growing body of research suggests that tumor angiogenesis and hypoxia interact through a complex interplay of crosstalk, which is inextricably linked to the TME. Here, we review the TME's positive contribution to angiogenesis from an angiogenesis-centric perspective while considering the objective impact of hypoxic phenotypes and the status and limitations of current angiogenic therapies.

GTKO rabbit: A novel animal model for preclinical assessment of decellularized xenogeneic grafts via in situ implantation.

Wild type (WT) animals cannot be used to objectively assess the immunogenicity of animal tissue-derived biomaterials when used as recipients due to difference with human in α-Gal expression. The purpose of this study is to compare the differences of immunological responses between the GGTA1 gene-knockout (GTKO) rabbits and WT rabbits after implantation with animal tissue-derived biomaterials. The porcine-derived decellularized bone matrix (natural bone material, NBM) and fresh porcine cancellous bone (PCB) were implanted in GTKO rabbits and WT rabbits, respectively, and sham operation was used as control (Con). At 2- and 6-week post-implantation, the related immunological items including antibody levels, serum-mediated cell lysis, cytokines, lymphocyte subtypes, and histopathological changes were assessed. GTKO rabbits exhibited more sensitive immune responses than WT rabbits after PCB implantation, resulted from a significant increase of antibodies (except total antibodies) and cytokines levels, cell lysis ratios, CD4/CD8 proportions, and inflammatory cells infiltration. Immunological factors and inflammatory cells infiltrate in GTKO rabbits after NBM implantation were significantly lower than those in the PCB group. Among the three groups, the NBM group showed the highest contents of new bone formation elements. In conclusion, the GTKO rabbit is a more sensitive alternative model than WT rabbit for preclinical study of xenografts via in situ implantation. Studies on multiple gene-edited animals are also necessary for more comprehensively evaluating xenoimmunologen risks of animal tissue-derived biomaterials in the future. Additionally, the immunogenicity of NBM was remarkably decreased compared to PCB.

Immunological Risk Assessment of Xenogeneic Dural Patch by Comparing with Raw Material via GTKO Mice.

OBJECTIVE: In this study, α-Gal epitope-deficient (GGTA1 knockout (GTKO)) mice were used to assess the immunological risks of xenogeneic dural patch by comparing with raw material. METHODS: The xenogeneic dural patch (T2) was prepared from bovine pericardium (T1, raw material) through decellularization and carboxymethyl chitosan (CMCS) coating. Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) were used to characterize the collagen fibers and surface microstructural changes in the T1 and T2 samples. The remnant α-Gal epitopes and DNA of implants were detected by standardized method. T1 and T2 were implanted subcutaneously into GTKO mice for 4 and 12 weeks, respectively, and the negative control group (Con) was only performed sham operation. The total serum antibody, anti-Gal antibody, and splenic lymphocyte subtypes were analyzed by ELISA or flow cytometry, and histological analysis of implant-tissue was performed by H&E and Masson stain. RESULTS: TEM and Sirius red staining showed that the collagen fibers in the dural patch were closely arranged, and SEM showed that a loose three-dimensional structure was successfully constructed on the surface of the dural patch after CMCS coating. The remnant DNA in T2 was 24.64 ± 8.73 ng/mg (dry weight), and clearance of α-Gal epitope was up to 99.83% compared to T1. The significant increases in serum total IgM, anti-Gal IgG, and anti-Gal IgM at 4 weeks and the significant changes in anti-Gal IgG and spleen lymphocyte at 12 weeks were observed in the T1 group, but no significant change was observed in the T2 group, compared to the control group. Histological semiquantitative analysis showed severe cell and tissue responses at 4 weeks and a moderate response at 12 weeks in the T1 group, while a moderate response at 4 weeks and a slight response at 12 weeks in the T2 group. CONCLUSIONS: The results demonstrated that the xenogeneic dural patch has a lower and acceptable immunological risk compared to the raw material and control, respectively. On the other hand, it was suggested that GTKO mice are useful experimental model for immunological risk assessment of animal tissue-derived biomaterials.

α-Gal antigen-deficient rabbits with GGTA1 gene disruption via CRISPR/Cas9.

BACKGROUND: Previous studies have identified the carbohydrate epitope Galα1-3Galß1-4GlcNAc-R (termed the α-galactosyl epitope), known as the α-Gal antigen as the primary xenoantigen recognized by the human immune system. The α-Gal antigen is regulated by galactosyltransferase (GGTA1), and α-Gal antigen-deficient mice have been widely used in xenoimmunological studies, as well as for the immunogenic risk evaluation of animal-derived medical devices. The objective of this study was to develop α-Gal antigen-deficient rabbits by GGTA1 gene editing with the CRISPR/Cas9 system. RESULTS: The mutation efficiency of GGTA1 gene-editing in rabbits was as high as 92.3% in F0 pups. Phenotype analysis showed that the α-Gal antigen expression in the major organs of F0 rabbits was decreased by more than 99.96% compared with that in wild-type (WT) rabbits, and the specific anti-Gal IgG and IgM antibody levels in F1 rabbits increased with increasing age, peaking at approximately 5 or 6 months. Further study showed that GGTA1 gene expression in F2-edited rabbits was dramatically reduced compared to that in WT rabbits. CONCLUSIONS: α-Gal antigen-deficient rabbits were successfully generated by GGTA1 gene editing via the CRISPR/Cas9 system in this study. The feasibility of using these α-Gal antigen-deficient rabbits for the in situ implantation and residual immunogenic risk evaluation of animal tissue-derived medical devices was also preliminarily confirmed.

Vertebral Collapse Prevented Following Teriparatide Treatment in Postmenopausal Kümmell's Disease Patients with Severe Osteoporosis.

OBJECTIVE: To compare the preventive effects of teriparatide and alendronate on the progression of vertebral body collapse in postmenopausal single-level Kümmell's disease (KD). METHODS: From March 2013 to December 2020, the medical records for 53 postmenopausal single-level KD patients who received conservative treatment with teriparatide (25 patients, teriparatide group) or alendronate (28 patients, alendronate group) were retrospectively reviewed. Midsagittal computed tomography (CT) images were analyzed by ImageJ to assess the intravertebral bone formation (mineralized bone) by calculating the ratio of area of intravertebral mineralized bone (AIMB) to the area of fractured vertebral body (AFVB). The changes in radiological parameters of the fractured vertebral body including kyphosis angle (KA), anterior and posterior border heights (ABH and PBH) and spinal canal diameter (SCD), bone turnover biomarkers (BTMs), and bone mineral density (BMD) were analyzed to evaluate the therapeutic effect. RESULTS: At month 12, the ratio of AIMB to AFVB was significantly greater in teriparatide group (54.28% ± 15.30%) than in alendronate group (35.57% ± 17.61%) (P < 0.001). Sagittal CT substantiated the formation of bone bridge in 16 patients in teriparatide group. No bone bridge was detected in alendronate group. The KA was significantly smaller and the ABH, PBH, and SCD was greater in teriparatide group than in alendronate group (all P < 0.001). The KA increments were significantly smaller in teriparatide group (3.98° ± 1.30°) than in alendronate group (11.43° ± 3.73°) (P < 0.001). The ABH and PBH decrement were significantly lower in teriparatide group (11.96% ± 1.93% and 2.80% ± 2.52%) than in alendronate group (37.04% ± 8.00% and 19.50% ± 8.22%) (both P < 0.001). The BTMs and BMD were significantly greater in the teriparatide group than in the alendronate group. In teriparatide group, KA increment was negatively correlated with the change in PINP (r = -0.781, P < 0.001) and the ratio of AIMB to AFVB (r = -0.592, P = 0.002) from baseline to month 12. The ABH decrement was negatively correlated with the change in PINP (r = -0.612, P = 0.001) and the ratio of AIMB to AFVB (r = -0.806, P < 0.001) from baseline to month 12. CONCLUSIONS: In postmenopausal single-level KD patients, conservative treatment with teriparatide was better than alendronate at preventing the progressive vertebral collapse.

[Evaluation of the acute toxicity of pharmaceutical wastewater to luminescent bacteria].

Acute toxicity of wastewater from 5 nodes of technological process in the pharmaceutical factory sewage treatment station was studied by luminescent bacteria tests. The EC50, TUa and LID of the wastewater in underground regulating tanks was 3.44%, 29 and 625, respectively, indicating the water was extremely/highly toxic; for the wastewater in surface regulating tanks, the EC50, TUa and LID was 2.46%, 41 and 244, respectively, also extremely/highly toxic; for the wastewater in middle sediment tanks, the EC50 > 100% and LID was 10, which was moderately toxic; for the wastewater in secondary sediment tanks and the final effluents, the EC50 was above 100% and LID was 1, with no observed toxicity. The results indicated that the existing treatment process effectively reduced the acute toxicity of the pharmaceutical wastewater to luminescent bacteria, the effluents showed no observed toxicity to luminescent bacteria, which was lower than the relative effluent limits of pharmaceutical wastewater. The wastewater in lower concentration did not inhibit the luminosity, but enhanced the luminosity.