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The stability and catalytic activity of acidic oxygen evolution reaction (OER) are strongly determined by the coordination states and spatial symmetry among metal sites at catalysts. Herein, an ultrafast oxygen evaporation technology to rapidly soften the intrinsic covalent bonds using ultrahigh electrical pulses is suggested, in which prospective charged excited states at this extreme avalanche condition can generate a strong electron-phonon coupling to rapidly evaporate some coordinated oxygen (O) atoms, finally leading to a controllable half-metallization feature. Simultaneously, the relative metal (M) site arrays can be orderly locked to delineate some intriguing atom-fingerprints at pyrochlore catalysts, where the coexistence of metallic bonds (MâM) and covalent bonds (MâO) at this symmetry-breaking configuration can partially restrain crystal field effect to generate a particular high-spin occupied state. This half-metallization catalyst can effectively optimize the spin-related reaction kinetics in acidic OER, giving rise to 10.3 times (at 188 mV overpotential) reactive activity than pristine pyrochlores. This work provides a new understanding of half-metallization atom-fingerprints at catalyst surfaces to accelerate acidic water oxidation.
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Chitosan samples were prepared from the shells of marine animals (crab and shrimp) and the cell walls of fungi (agaricus bisporus and aspergillus niger). Fourier-transform infrared spectroscopy (FT-IR) was used to detect their molecular structures, while headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) was employed to analyze their odor composition. A total of 220 volatile organic compounds (VOCs), including esters, ketones, aldehydes, etc., were identified as the odor fingerprinting components of chitosan for the first time. A principal component analysis (PCA) revealed that chitosan could be effectively identified and classified based on its characteristic VOCs. The sum of the first three principal components explained 87% of the total variance in original information. An orthogonal partial least squares discrimination analysis (OPLS-DA) model was established for tracing and source identification purposes, demonstrating excellent performance with fitting indices R2X = 0.866, R2Y = 0.996, Q2 = 0.989 for independent variable fitting and model prediction accuracy, respectively. By utilizing OPLS-DA modeling along with a heatmap-based tracing path study, it was found that 29 VOCs significantly contributed to marine chitosan at a significance level of VIP > 1.00 (p < 0.05), whereas another set of 20 VOCs specifically associated with fungi chitosan exhibited notable contributions to its odor profile. These findings present a novel method for identifying commercial chitosan sources, which can be applied to ensure biological safety in practical applications.
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Pattern recognition based on network connections has recently been applied to the brain-computer interface (BCI) research, offering new ideas for emotion recognition using Electroencephalogram (EEG) signal. However unified standards are currently lacking for selecting emotional signals in emotion recognition research, and potential associations between activation differences in brain regions and network connectivity pattern are often being overlooked. To bridge this technical gap, a data-driven signal auto-segmentation and feature fusion algorithm (DASF) is proposed in this paper. First, the Phase Locking Value (PLV) method was used to construct the brain functional adjacency matrix of each subject, and the dynamic brain functional network across subjects was then constructed. Next, tucker decomposition was performed and the Grassmann distance of the connectivity submatrix was calculated. Subsequently, different brain network states were distinguished and signal segments under emotional states were automatically extract using data-driven methods. Then, tensor sparse representation was adopted on the intercepted EEG signals to effectively extract functional connections under different emotional states. Finally, power-distribution related features (differential entropy and energy feature) and brain functional connection features were effectively combined for classification using the support vector machines (SVM) classifier. The proposed method was validated on ERN and DEAP datasets. The single-feature emotion classification accuracy of 86.57 % and 87.74 % were achieved on valence and arousal dimensions, respectively. The accuracy of the proposed feature fusion method was achieved at 89.14 % and 89.65 %, accordingly, demonstrating an improvement in emotion recognition accuracy. The results demonstrated the superior classification performance of the proposed data-driven signal auto-segmentation and feature fusion algorithm in emotion recognition compared to state-of-the-art classification methods.
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Eletroencefalografia , Emoções , Máquina de Vetores de Suporte , Humanos , Emoções/fisiologia , Encéfalo/fisiologia , Adulto , Interfaces Cérebro-Computador , Algoritmos , Feminino , Masculino , Adulto Jovem , Processamento de Sinais Assistido por ComputadorRESUMO
BACKGROUND/PURPOSE: The incidence of inflammatory bowel disease (IBD) rapidly increases in Asia, and western dietary pattern is suspected to be the major risk factor. Despite this, there has been a lack of studies analyzing the relationship between dietary patterns and IBD in Taiwan. This study examines the dietary habits of Taiwanese individuals with and without IBD to inform clinical dietary recommendations for IBD patients. METHODS: We collected baseline characteristics and dietary habits from both IBD patients and healthy controls from February and August 2022 in Chang Gung memorial hospital using a structured and validated food frequency questionnaire. The dietary habits of IBD patients in this study were focused on the six months leading up to their IBD diagnosis. RESULTS: Our study recruited 98 IBD patients and 184 healthy controls. In demographic characteristics, cigarette smoking is more common in IBD group. Besides, distinct dietary patterns were observed between groups. The healthy controls demonstrated a higher consumption of whole foods and antioxidants. By contrast, the IBD group consumed more western-style foods but the difference didn't reach statistical significance. CONCLUSION: Our study found that healthy controls in Taiwan embraced a dietary pattern rich in whole foods that may prevent IBD or reduce IBD disease activity. Nonetheless, a larger sample size is needed to further provide valuable dietary guidance for general population in Taiwan for IBD prevention or for patients with IBD for disease activity control.
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This study introduces two novel sandwich-type tungsten-oxygen cluster compounds synthesized by hydrothermal methods, H4(C6H12N2H2)3{Na(H2O)2[Mn2(H2O)(GeW9O34)]}2 (Compound 1) and H2(C6H12N2H2)3.5{Na3(H2O)4[Co2(H2O)(GeW9O34)]2}·17H2O (Compound 2). The two compounds comprise cluster anions [GeW9O34]10- coordinated with transition metal atoms, either Mn or Co, and are stabilized by organic ligands. These compounds are crystallized in the hexagonal crystal system and P63/m space group. The two compounds were characterized through various techniques. Fourier transform infrared (IR) spectroscopy showed absorption peaks of anionic backbone vibrations of the Keggin cluster at 500-1000â cm-1, IR spectral peaks of δ(N-H) and νas(C-N) of the ligand triethylenediamine at 1000-2000â cm-1, and IR spectral peaks of the ligand νas(N-H) and νas(O-H) of water at 3000-3500â cm-1. Despite similar one-dimensional (1D) IR spectra due to the same cluster anions and similar molecular structures, the two compounds exhibited distinct responses in two-dimensional correlation spectroscopy with IR under magnetic and thermal perturbations. Under magnetic perturbation, Compound 1 showed a strong response peak for νas(W-Ob-W), while Compound 2 exhibited a strong response peak for νas(W=Od), possibly linked to differing magnetic particles. Similarly, Compound 1 displayed a strong response peak under thermal perturbation for νas(W-Oc-W). In contrast, Compound 2 showed a strong response peak for νas(W=Od); these results may be attributed to the different hydrogen bonding connections between the two compounds, which affect the groups in distinct ways through vibration and transmit these vibrations to the W-O bonds. The research presented in this paper expands the theoretical and experimental data of 2D correlation IR spectroscopy.
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Transfer learning (TL) has demonstrated its efficacy in addressing the cross-subject domain adaptation challenges in affective brain-computer interfaces (aBCI). However, previous TL methods usually use a stationary distance, such as Euclidean distance, to quantify the distribution dissimilarity between two domains, overlooking the inherent links among similar samples, potentially leading to suboptimal feature mapping. In this study, we introduced a novel algorithm called multi-source manifold metric transfer learning (MSMMTL) to enhance the efficacy of conventional TL. Specifically, we first selected the source domain based on Mahalanobis distance to enhance the quality of the source domains and then used manifold feature mapping approach to map the source and target domains on the Grassmann manifold to mitigate data drift between domains. In this newly established shared space, we optimized the Mahalanobis metric by maximizing the inter-class distances while minimizing the intra-class distances in the target domain. Recognizing that significant distribution discrepancies might persist across different domains even on the manifold, to ensure similar distributions between the source and target domains, we further imposed constraints on both domains under the Mahalanobis metric. This approach aims to reduce distributional disparities and enhance the electroencephalogram (EEG) emotion recognition performance. In cross-subject experiments, the MSMMTL model exhibits average classification accuracies of 88.83 % and 65.04 % for SEED and DEAP, respectively, underscoring the superiority of our proposed MSMMTL over other state-of-the-art methods. MSMMTL can effectively solve the problem of individual differences in EEG-based affective computing.
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Algoritmos , Interfaces Cérebro-Computador , Eletroencefalografia , Emoções , Aprendizado de Máquina , Humanos , Eletroencefalografia/métodos , Emoções/fisiologia , Processamento de Sinais Assistido por Computador , Masculino , Encéfalo/fisiologia , FemininoRESUMO
Fe2O3 is a promising semiconductor for photoelectrochemical (PEC) water decomposition. However, severe charge recombination problems limit its applications. In this study, a F-Fe2O3-x/MoS2 nanorod array photoanode was designed and prepared to facilitate charge separation. Detailed characterization and experimental results showed that F doping in Fe2O3 regulated the electronic structure to improve the conductivity of Fe2O3 and induced abundant oxygen vacancies to increase the carrier concentration and promote charge separation in bulk. In addition, the internal electric field between F-Fe2O3-x and MoS2 facilitated the qualitative transfer of the photogenerated charge, thus inhibiting their recombination. The synergistic effect between the oxygen vacancy and F-Fe2O3-x/MoS2 heterojunction significantly enhanced the PEC performance of Fe2O3. This study provides a universal strategy for designing other photoanode materials with high-efficiency charge separation.
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BACKGROUND: Transjugular intrahepatic portosystemic shunt (TIPS) placement is a procedure that can effectively treat complications of portal hypertension, such as variceal bleeding and refractory ascites. However, there have been no specific studies on predicting long-term survival after TIPS placement. AIM: To establish a model to predict long-term survival in patients with hepatitis cirrhosis after TIPS. METHODS: A retrospective analysis was conducted on a cohort of 224 patients who underwent TIPS implantation. Through univariate and multivariate Cox regression analyses, various factors were examined for their ability to predict survival at 6 years after TIPS. Consequently, a composite score was formulated, encompassing the indication, shunt reasonability, portal venous pressure gradient (PPG) after TIPS, percentage decrease in portal venous pressure (PVP), indocyanine green retention rate at 15 min (ICGR15) and total bilirubin (Tbil) level. Furthermore, the performance of the newly developed Cox (NDC) model was evaluated in an internal validation cohort and compared with that of a series of existing models. RESULTS: The indication (variceal bleeding or ascites), shunt reasonability (reasonable or unreasonable), ICGR15, postoperative PPG, percentage of PVP decrease and Tbil were found to be independent factors affecting long-term survival after TIPS placement. The NDC model incorporated these parameters and successfully identified patients at high risk, exhibiting a notably elevated mortality rate following the TIPS procedure, as observed in both the training and validation cohorts. Additionally, in terms of predicting the long-term survival rate, the performance of the NDC model was significantly better than that of the other four models [Child-Pugh, model for end-stage liver disease (MELD), MELD-sodium and the Freiburg index of post-TIPS survival]. CONCLUSION: The NDC model can accurately predict long-term survival after the TIPS procedure in patients with hepatitis cirrhosis, help identify high-risk patients and guide follow-up management after TIPS implantation.
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Tensor analysis of electroencephalogram (EEG) can extract the activity information and the potential interaction between different brain regions. However, EEG data varies between subjects, and the existing tensor decomposition algorithms cannot guarantee that the features across subjects are distributed in the same domain, which leads to the non-objectivity of the classification result and analysis, In addition, traditional Tucker decomposition is prone to the explosion of feature dimensions. To solve these problems, combined with the idea of feature transfer, a novel EEG tensor transfer algorithm, Tensor Subspace Learning based on Sparse Regularized Tucker Decomposition (TSL-SRT), is proposed in this paper. In TSL-SRT, new EEG samples are considered as the target domain and original samples as the source domain. The target features can be obtained by projecting the target tensor to the source feature space to ensure that all features are in the same domain. Furthermore, to solve the problem of dimension explosion caused by TSL-SRT, a redundant EEG features screening algorithm is adopted to eliminate the redundant features, and achieves 77.8%, 73.2% and 75.3% accuracy on three BCI datasets. By visualizing the spatial basic matrix of the feature space, it can be seen that TSL-SRT is effective in extracting the features of active brain regions in the BCI task and it can extract the multi-domain features of different subjects in the same domain simultaneously, which provides a new method for the tensor analysis of EEG.
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Two novel vanadoborate compounds, [Cu(en)2]3[Li(H2O)]4[Li(H2O)3]2[V12B18O50(OH)10(H2O)]2·33.5H2O (1) and (H2en)4[Li(H2O)]4[V12B18O55(OH)5(H2O)]·14H2O (2), were synthesized via hydrothermal synthesis under identical conditions except for temperature. Structural analysis revealed that although both contain [V12B18O60]n- cluster anion, the different countercations potentially lead to variations in the [V12B18O60]n- cluster anion skeletons. In compound 1, the V4+/V5+ ratio was 10:2; while in compound 2 the ratio was 11:1. It is speculated that different countercations may influence the valence states of cluster anions. In this study, quantum chemical calculations revealed that the aromaticity and activity of the two compounds were different, and two-dimensional correlation infrared spectroscopy (2D-COS-IR) under magnetic perturbation confirmed that distinct response peaks of functional group vibrations to the magnetic field due to the different V4+/V5+ ratios and aromaticity of the two compounds. An electrochemical analysis revealed that compound 2 exhibits higher electrocatalytic activity. The results of quantum chemical calculations are aligned not only with the changes in the 2D-COS-IR spectra but also with the conclusions obtained from experiments on electrochemical properties. Overall, this work proposes a novel strategy for interpreting the alteration of vanadoborate anionic skeleton due to the introduction of different countercations by combining 2D-COS-IR with quantum chemical calculations.
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Motor imagery (MI) paradigms have been widely used in neural rehabilitation and drowsiness state assessment. The progress in brain-computer interface (BCI) technology has emphasized the importance of accurately and efficiently detecting motor imagery intentions from electroencephalogram (EEG). Despite the recent breakthroughs made in developing EEG-based algorithms for decoding MI, the accuracy and efficiency of these models remain limited by technical challenges posed by cross-subject heterogeneity in EEG data processing and the scarcity of EEG data for training. Inspired by the optimal transport theory, this study aims to develop a novel three-stage transfer learning (TSTL) method, which uses the existing labeled data from a source domain to improve classification performance on an unlabeled target domain. Notably, the proposed method comprises three components, namely, the Riemannian tangent space mapping (RTSM), source domain transformer (SDT), and optimal subspace mapping (OSM). The RTSM maps a symmetric positive definite matrix from the Riemannian space to the tangent space to minimize the marginal probability distribution drift. The SDT transforms the source domain to a target domain by finding the optimal transport mapping matrix to reduce the joint probability distribution differences. The OSM finally maps the transformed source domain and original target domain to the same subspace to further mitigate the distribution discrepancy. The performance of the proposed method was validated on two public BCI datasets, and the average accuracy of the algorithm on two datasets was 72.24% and 69.29%. Our results demonstrated the improved performance of EEG-based MI detection in comparison with state-of-the-art algorithms.
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Algoritmos , Interfaces Cérebro-Computador , Eletroencefalografia , Humanos , Eletroencefalografia/métodos , Aprendizado de Máquina , Processamento de Sinais Assistido por Computador , Imaginação/fisiologiaRESUMO
OBJECTIVE: To investigate the abnormal radiomics features of the hippocampus in patients with multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) and to explore the clinical implications of these features. METHODS: 752 participants were recruited in this retrospective multicenter study (7 centers), which included 236 MS, 236 NMOSD, and 280 normal controls (NC). Radiomics features of each side of the hippocampus were extracted, including intensity, shape, texture, and wavelet features (N = 431). To identify the variations in these features, two-sample t-tests were performed between the NMOSD vs. NC, MS vs. NC, and NMOSD vs. MS groups at each site. The statistical results from each site were then integrated through meta-analysis. To investigate the clinical significance of the hippocampal radiomics features, we conducted further analysis to examine the correlations between these features and clinical measures such as Expanded Disability Status Scale (EDSS), Brief Visuospatial Memory Test (BVMT), California Verbal Learning Test (CVLT), and Paced Auditory Serial Addition Task (PASAT). RESULTS: Compared with NC, patients with MS exhibited significant differences in 78 radiomics features (P < 0.05/862), with the majority of these being texture features. Patients with NMOSD showed significant differences in 137 radiomics features (P < 0.05/862), most of which were intensity features. The difference between MS and NMOSD patients was observed in 47 radiomics features (P < 0.05/862), mainly texture features. In patients with MS and NMOSD, the most significant features related to the EDSS were intensity and textural features, and the most significant features related to the PASAT were intensity features. Meanwhile, both disease groups observed a weak correlation between radiomics data and BVMT. CONCLUSION: Variations in the microstructure of the hippocampus can be detected through radiomics, offering a new approach to investigating the abnormal pattern of the hippocampus in MS and NMOSD.
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Esclerose Múltipla , Neuromielite Óptica , Humanos , Neuromielite Óptica/diagnóstico por imagem , Esclerose Múltipla/diagnóstico por imagem , Radiômica , Estudos Retrospectivos , Estudos Multicêntricos como AssuntoRESUMO
The coupled analysis of corticomuscular function based on physiological electrical signals can identify differences in causal relationships between electroencephalogram (EEG) and surface electromyogram (sEMG) in different motor states. The existing methods are mainly devoted to the analysis in the same frequency band, while ignoring the cross-band coupling, which plays an active role in motion control. Considering the inherent multiscale characteristics of physiological signals, a method combining Ordinal Partition Transition Networks (OPTNs) and Multivariate Variational Modal Decomposition (MVMD) was proposed in this paper. The EEG and sEMG were firstly decomposed on a time-frequency scale using MVMD, and then the coupling strength was calculated by the OPTNs to construct a corticomuscular coupling network, which was analyzed with complex network parameters. Experimental data were obtained from a self-acquired dataset consisting of EEG and sEMG of 16 healthy subjects at different sizes of constant grip force. The results showed that the method was superior in representing changes in the causal link among multichannel signals characterized by different frequency bands and grip strength patterns. Complex information transfer between the cerebral cortex and the corresponding muscle groups during constant grip force output from the human upper limb. Furthermore, the sEMG of the flexor digitorum superficialis (FDS) in the low frequency band is the hub in the effective information transmission between the cortex and the muscle, while the importance of each frequency component in this transmission network becomes more dispersed as the grip strength grows, and the increase in coupling strength and node status is mainly in the γ band (30~60Hz). This study provides new ideas for deconstructing the mechanisms of neural control of muscle movements.
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Eletroencefalografia , Músculo Esquelético , Humanos , Músculo Esquelético/fisiologia , Eletromiografia , Córtex Cerebral/fisiologia , MãosRESUMO
Low-dimensional CsPbBr3 perovskite materials have gained widespread attention, derived from their remarkable properties and potential for numerous optoelectronic applications. Herein, the sample of CsPbBr3 microwires were prepared horizontally onto n-type InGaN film substrate using an in-plane solution growth method. The resulting CsPbBr3 microwire/InGaN heterojunction allows for the achievement of a highly sensitive and broadband photodetector. Particularly for the implementation in a self-supplying manner, the best-performing photodetector can achieve a superior On/Off ratio of 4.6×105, the largest responsivity â¼ 800.0 mA/W, a maximum detectivity surpassing 4.6× 1012 Jones, and a high external quantum efficiency approaching 86.5% upon 405 nm light illumination. A rapid response time (â¼ 4.48 ms/7.68 ms) was also achieved. The as-designed CsPbBr3 microwire/InGaN heterojunction device without any encapsulation exhibits superior comprehensive stability. Besides, the device featuring as a single pixel imaging unit can readily detect simple images under broadband light illumination with a high spatial resolution, acknowledging its outstanding imaging capability. The robust photodetection properties could be derived from the intense absorption of CsPbBr3 MWs and high-efficiency charge carriers transporting toward the in-situ formed CsPbBr3/InGaN heterointerface. The results may offer an available strategy for the in-situ construction of best-performing low-dimensional perovskite heterojunction optoelectronic devices.
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CAR-T targeting CD19 have achieved significant effects in the treatment of B-line leukemia and lymphoma. However, the treated patients frequently relapsed and could not achieve complete remission. Therefore, improving the proliferation and cytotoxicity of CAR-T cells, reducing exhaustion and enhancing infiltration capacity are still issues to be solved. The IL-7 has been shown to enhance the memory characteristics of CAR-T cells, but the specific mechanism has yet to be elaborated. miRNAs play an important role in T cell activity. However, whether miRNA is involved in the activation of CAR-T cells by IL-7 has not yet been reported. Our previous study had established the 3rd generation CAR-T cells. The present study further found that IL-7 significantly increased the proliferation of anti-CD19 CAR-T cells, the ratio of CD4 + CAR + cells and the S phase of cell cycle. In vivo study NAMALWA xenograft model showed that IL-7-stimulated CAR-T cells possessed stronger tumoricidal efficiency. Further we validated that IL-7 induced CAR-T cells had low expression of CDKN1A and high expression of miRNA-98-5p. Additionally, CDKN1A was associated with miRNA-98-5p. Our results, for the first time, suggested IL-7 could conspicuously enhance the proliferation of CAR-T cells through miRNA-98-5p targeting CDKN1A expression, which should be applied to CAR-T production.
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MicroRNAs , Receptores de Antígenos Quiméricos , Humanos , Receptores de Antígenos Quiméricos/metabolismo , Imunoterapia Adotiva/métodos , Interleucina-7/genética , Interleucina-7/metabolismo , MicroRNAs/genética , Proliferação de Células , Antígenos CD19/genética , Antígenos CD19/metabolismo , Inibidor de Quinase Dependente de Ciclina p21/metabolismoRESUMO
Contingent on stereo compatibility, two images presented dichoptically can lead to either binocular integration, thus generating stable stereopsis, or interocular suppression that induces binocular rivalry with bistable perception that alternates between the two images. The relationship between binocular integration and interocular suppression concerns how our brain processes binocular inputs to form unified visual awareness but remains unclear. Here, a series of psychophysical experiments were conducted to address this question, revealing that these collaborative and competitive binocular interactions are interconnected and would mediate one another according to their strength. Specifically, Experiments 1a and 1b showed that the presence of binocular rivalry inhibited peripheral stereopsis, significantly elevating the stereo threshold, with higher elevation resulting from increasing rivalry contrast. Experiments 2a and 2b showed that existing stereopsis with increasing binocular disparity balanced the dynamics of peripheral binocular rivalry, rendering more equivalent eye dominance. Based on these interactions, we suggest that binocular integration and interocular suppression may mediate one another through an overlapping mechanism for regulating eye dominance, with strong stereo percepts tending to reduce eye dominance and strong rivalry tending to increase eye dominance.
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Percepção de Profundidade , Visão Binocular , Humanos , Encéfalo , Dominância Ocular , Disparidade VisualRESUMO
We aim to develop a nomogram to predict overt hepatic encephalopathy (OHE) after transjugular intrahepatic portosystemic shunt (TIPS) in patients with portal hypertension, according to demographic/clinical indicators such as age, creatinine, blood ammonia, indocyanine green retention rate at 15 min (ICG-R15) and percentage of Portal pressure gradient (PPG) decline. In this retrospective study, 296 patients with portal hypertension who received elective TIPS in Beijing Shijitan Hospital from June 2018 to June 2020 were included. These patients were randomly divided into a training cohort (n = 207) and a validation cohort (n = 89). According to the occurrence of OHE, patients were assigned to OHE group and non-OHE group. Both univariate and multivariate analyses were performed to determine independent variables for predicting OHE after TIPS. Accordingly, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to compare the accuracy and superiority of a novel model with conventional Child-Pugh and MELD scoring model. Age (OR 1.036, 95% CI 1.002-1.070, p = 0.037), Creatinine (OR 1.011, 95% CI 1.003-1.019, p = 0.009), Blood ammonia (OR 1.025, 95% CI 1.006-1.044, p = 0.011), ICG-R15 (OR 1.030, 95% CI 1.009-1.052, p = 0.004) and Percentage decline in PPG (OR 1.068, 95% CI 1.029-1.109, p = 0.001) were independent risk factors for OHE after TIPS using multifactorial analysis. A nomogram was constructed using a well-fit calibration curve for each of these five covariates. When compared to Child-Pugh and MELD score, this new nomogram has a better predictive value (C-index = 0.828, 95% CI 0.761-0.896). Consistently, this finding was reproduceable in validation cohort and confirmed with DCA. A unique nomogram was developed to predict OHE after TIPS in patients with PHT, with a high prediction sensitivity and specificity performance than commonly applied scoring systems.
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Encefalopatia Hepática , Hipertensão Portal , Derivação Portossistêmica Transjugular Intra-Hepática , Humanos , Encefalopatia Hepática/etiologia , Amônia , Creatinina , Nomogramas , Derivação Portossistêmica Transjugular Intra-Hepática/efeitos adversos , Estudos Retrospectivos , Hipertensão Portal/etiologia , Hipertensão Portal/cirurgia , Verde de IndocianinaRESUMO
Depression is highly prevalent and easily relapses. Psychological interventions are effective for the prevention of depression relapse. This systematic review and network meta-analysis aimed to compare the efficacy at the same follow-up time points of psychological interventions in depression. We searched PubMed, Embase, and PsycINFO via OVID, and the Cochrane Library published up to December 12, 2021, and PubMed up to July 1, 2022. The primary outcome was depression relapse, considering the same time points that were extracted on survival curves or relapse curves. The study protocol was registered with PROSPERO, CRD42022343327. A total of 2,871 patients were included from 25 RCTs. Mindfulness-based cognitive therapy (MBCT) was significantly better than placebo at the 3 months, the 6 months, and the 9 months at follow-up. Cognitive behavioral therapy (CBT) was significantly better than treatment as usual at the 3 months, the 9 months, the 12 months, and the 15 months at follow-up. CBT was significantly better than placebo at the 21 months and the 24 months at follow-up. Behavioral activation therapy was significantly better than placebo at the 21 months and the 24 months at follow-up. Interpersonal psychotherapy was significantly better than placebo at the 24-month follow-up. All psychological interventions included in the study were significantly better than supportive counseling most of the time. The results were robust in various sensitivity and subgroup analyses. In conclusion, MBCT had a continuous effect in preventing relapse of depression. CBT had the longest but not continuous effect in preventing relapse of depression. The effects of behavioral activation therapy and interpersonal therapy for the prevention of depression appeared late. All psychological interventions included in the study were more effective than supportive counseling. More evidence is needed from large comparative trials that provide long-term follow-up data.
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Depressão , Intervenção Psicossocial , Humanos , Metanálise em Rede , Depressão/prevenção & controle , Terapia Comportamental , Doença Crônica , RecidivaRESUMO
BACKGROUND: No single endoscopic feature can reliably predict the pathological nature of colorectal tumors (CRTs). AIM: To establish and validate a simple online calculator to predict the pathological nature of CRTs based on white-light endoscopy. METHODS: This was a single-center study. During the identification stage, 530 consecutive patients with CRTs were enrolled from January 2015 to December 2021 as the derivation group. Logistic regression analysis was performed. A novel online calculator to predict the pathological nature of CRTs based on white-light images was established and verified internally. During the validation stage, two series of 110 images obtained using white-light endoscopy were distributed to 10 endoscopists [five highly experienced endoscopists and five less experienced endoscopists (LEEs)] for external validation before and after systematic training. RESULTS: A total of 750 patients were included, with an average age of 63.6 ± 10.4 years. Early colorectal cancer (ECRC) was detected in 351 (46.8%) patients. Tumor size, left semicolon site, rectal site, acanthosis, depression and an uneven surface were independent risk factors for ECRC. The C-index of the ECRC calculator prediction model was 0.906 (P = 0.225, Hosmer-Lemeshow test). For the LEEs, significant improvement was made in the sensitivity, specificity and accuracy (57.6% vs 75.5%; 72.3% vs 82.4%; 64.2% vs 80.2%; P < 0.05), respectively, after training with the ECRC online calculator prediction model. CONCLUSION: A novel online calculator including tumor size, location, acanthosis, depression, and uneven surface can accurately predict the pathological nature of ECRC.
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Faces contain rich information and play a pivotal role in human daily social interactions. Previous studies have provided evidence for the left-visual-field-advantage in face perception. The current study investigated lateralisation when face stimuli were unconsciously presented using interocular suppression methods. The results showed that when an unconscious face stimulus was presented in one side of the visual field without other face stimuli, the unconscious face in the right visual field could break through interocular suppression faster than that in the left (Experiments 1 and 2). However, this right visual field processing advantage reversed to the left when a face stimulus either with (Experiment 2) or without (Experiment 3) visual awareness was presented concurrently with or prior to (Experiment 4) the unconscious face stimuli. These results showed that the unconscious face might have a different processing pattern compared with the conscious face. The relationship between this novel behavioural observation and known functional lateralisation of the fusiform face areas is discussed, suggesting a dynamic interaction between the two cortical hemispheres may underlie the formation of visual awareness for faces. The current study expands our understanding of face processing lateralisation and provided evidence on the asymmetric inter-hemisphere interaction patterns in forming visual awareness.