Interfacial "Double-Terminal Binding Sites" Catalysts Synergistically Boosting the Electrocatalytic Li2S Redox for Durable Lithium-Sulfur Batteries.

Catalytic conversion of polysulfides emerges as a promising approach to improve the kinetics and mitigate polysulfide shuttling in lithium-sulfur (Li-S) batteries, especially under conditions of high sulfur loading and lean electrolyte. Herein, we present a separator architecture that incorporates double-terminal binding (DTB) sites within a nitrogen-doped carbon framework, consisting of polar Co0.85Se and Co clusters (Co/Co0.85Se@NC), to enhance the durability of Li-S batteries. The uniformly dispersed clusters of polar Co0.85Se and Co offer abundant active sites for lithium polysulfides (LiPSs), enabling efficient LiPS conversion while also serving as anchors through a combination of chemical interactions. Density functional theory calculations, along with in situ Raman and X-ray diffraction characterizations, reveal that the DTB effect strengthens the binding energy to polysulfides and lowers the energy barriers of polysulfide redox reactions. Li-S batteries utilizing the Co/Co0.85Se@NC-modified separator demonstrate exceptional cycling stability (0.042% per cycle over 1000 cycles at 2 C) and rate capability (849 mAh g-1 at 3 C), as well as deliver an impressive areal capacity of 10.0 mAh cm-2 even in challenging conditions with a high sulfur loading (10.7 mg cm-2) and lean electrolyte environments (5.8 µL mg-1). The DTB site strategy offers valuable insights into the development of high-performance Li-S batteries.

Graph Self-Supervised Learning With Application to Brain Networks Analysis.

The less training data and insufficient supervision limit the performance of the deep supervised models for brain disease diagnosis. It is significant to construct a learning framework that can capture more information in limited data and insufficient supervision. To address these issues, we focus on self-supervised learning and aim to generalize the self-supervised learning to the brain networks, which are non-Euclidean graph data. More specifically, we propose an ensemble masked graph self-supervised framework named BrainGSLs, which incorporates 1) a local topological-aware encoder that takes the partially visible nodes as input and learns these latent representations, 2) a node-edge bi-decoder that reconstructs the masked edges by the representations of both the masked and visible nodes, 3) a signal representation learning module for capturing temporal representations from BOLD signals and 4) a classifier used for the classification. We evaluate our model on three real medical clinical applications: diagnosis of Autism Spectrum Disorder (ASD), diagnosis of Bipolar Disorder (BD) and diagnosis of Major Depressive Disorder (MDD). The results suggest that the proposed self-supervised training has led to remarkable improvement and outperforms state-of-the-art methods. Moreover, our method is able to identify the biomarkers associated with the diseases, which is consistent with the previous studies. We also explore the correlation of these three diseases and find the strong association between ASD and BD. To the best of our knowledge, our work is the first attempt of applying the idea of self-supervised learning with masked autoencoder on the brain network analysis.

BrainTGL: A dynamic graph representation learning model for brain network analysis.

Modeling the dynamics characteristics in functional brain networks (FBNs) is important for understanding the functional mechanism of the human brain. However, the current works do not fully consider the potential complex spatial and temporal correlations in human brain. To solve this problem, we propose a temporal graph representation learning framework for brain networks (BrainTGL). The framework involves a temporal graph pooling for eliminating the noisy edges as well as data inconsistency, and a dual temporal graph learning for capturing the spatio-temporal features of the temporal graphs. The proposed method has been evaluated in both tasks of brain disease (ASD, MDD and BD) diagnosis/gender classification (classification task) and subtype identification (clustering task) on the four datasets: Human Connectome Project (HCP), Autism Brain Imaging Data Exchange (ABIDE), NMU-MDD and NMU-BD. A large improvement is achieved for the ASD diagnosis. Specifically, our model outperforms the GroupINN and ST-GCN by an average increase of 4.2% and 8.6% on accuracy, respectively, demonstrating its advantages in comparison to the state-of-the-art methods based on functional connectivity features or learned spatio-temporal features. The results demonstrate that learning the spatial-temporal brain network representation for modeling dynamics characteristics in FBNs can improve the model's performance on both disease diagnosis and subtype identification tasks for multiple disorders. Apart from performance, the improvements of computational efficiency and convergence speed reduce training costs.

Levitt's CO breath test in the differential diagnosis of chronic isolated hyperbilirubinemia.

A key component of the differential diagnosis of isolated hyperbilirubinemia (HB) is distinguishing between hemolytic and non-hemolytic types. Routine hemolysis screening markers have unsatisfactory sensitivity and specificity. Erythrocyte (RBC) lifespan shortening, the gold standard marker of hemolysis, is seldomly measured due to the cumbersome and protracted nature of standard methods. A new Levitt's CO breath test method may enable simple, rapid RBC lifespan measurement. In this pilot prospective diagnostic study, Levitt's CO breath test was evaluated to discriminate hemolytic from non-hemolytic HB in adults. One hundred and thirty eligible non-smoking adult patients who were aged 18 or older, referred for chronic (>6 months) isolated HB or had a known diagnosis of isolated HB of a rare cause, were recruited, including 77 with non-hemolytic HB and 53 with hemolytic HB. ROC curve analysis was applied to determine the optimal cutoff for discriminating between hemolytic and non-hemolytic HB, and the performance was calculated. Results showed that the mean RBC lifespan in non-hemolytic HB (93 ± 26 d) was reduced (p= 0.001 vs. normal reference value of 126 d), but longer than that in hemolytic HB (36 ± 17 d;p= 0.001). RBC lifespans did not differ significantly between 26 patients with simple hemolytic HB (32 ± 14 d) and 27 patients with a Gilbert syndrome comorbidity (40 ± 18 d). ROC curve analysis revealed an optimal lifespan cutoff for discriminating between hemolytic and non-hemolytic HB of 60 d (AUC = 0.982), with a diagnostic accuracy of 95.4%, 94.3% sensitivity and 96.1% specificity respectively. These results indicate that Levitt's CO breath test seems to be very sensitive and specific for detecting hemolysis in adult patients with chronic isolated HB, and could enable simple, rapid, and reliable differential diagnosis of isolated HB. A large-scale validation study of the method is warranted.

Studies on the regulatory mechanism of isocitrate dehydrogenase 2 using acetylation mimics.

Mitochondrial isocitrate dehydrogenase 2 (IDH2) converts NADP+ to NADPH and promotes regeneration of reduced glutathione (GSH) by supplying NADPH to glutathione reductase or thioredoxin reductase. We have previously shown that under calorie restriction, mitochondrial deacetylase Sirt3 deacetylates and activates IDH2, thereby regulating the mitochondrial glutathione antioxidant defense system in mice. To investigate the regulatory mechanism of mIDH2 (mouse mitochondrial IDH2), we used lysine-to-glutamine (KQ) mutants to mimic acetylated lysines and screened 15 KQ mutants. Among these mutants, the activities of the K256Q and K413Q proteins were less than 50% of the wild-type value. We then solved the crystal structures of the wild-type mIDH2 and the K256Q mutant proteins, revealing conformational changes in the substrate-binding pocket. Structural data suggested that positively charged Lys256 was important in stabilizing the pocket because it repelled a lysine cluster on the other side. Glutamine (or acetylated lysine) was neutral and thus caused the pocket size to decrease, which might be the main reason for the lower activity of the K256Q mutant. Together, our data provide the first structure of an acetylation mimic of mIDH2 and new insights into the regulatory mechanism of acetylation of mIDH2.

[The clinical research of primary bilateral neck dissection in the head and neck tumors].

OBJECTIVE: To explore the head and neck tumors underwent primary tumor resection and bilateral neck dissection in the same period in the safety, indications, and surgical difficulty. METHOD: Retrospective analysis of 134 cases received primary tumor resection and bilateral neck dissection for head and neck cancer, the way of bilateral neck dissection were: one side was radical neck dissection and another was functional neck dissection (29 cases), one side was radical neck dissection and another was lateral neck dissection (34 cases), bilateral functional neck dissection (14 cases), one side was functional neck dissection and another was lateral neck dissection (48 cases), bilateral sides of lateral neck dissection (6 cases). RESULT: There was no operative death in 134 cases, complications for the wound bleeding in 3 cases, chylous leakage in 4 cases, pharyngeal fistula and infection in 1 case, stress ulcer in 5 cases, 1 case died, cerebral infarction in 1 case. CONCLUSION: The head and neck tumors underwent simultaneous bilateral neck dissection is safe. Appropriate cleaning method selection to reduce cervical lymph node metastasis could reduce the suffering of patients.

[Serum leptin level in patients with obstructive sleep apnea-hypopnea syndrome].

OBJECTIVE: To investigate the effect of uvulopalatopharyngoplasty on changes of serum leptin levels in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS). METHODS: Sixty-one patients with OSAHS diagnosed by polysomnography were treated with uvulopalatopharyngoplasty. Pretreatment and post-uppp serum leptin concentrations in patients with OSAHS and in BMI-matched controls were measured by radioimmunoassay. Correlations between leptin concentrations and AHI, BMI were analyzed. RESULTS: The concentrations of leptin in patients with OSAHS were higher than that in controls (P < 0.05). Mean levels (x+/-s) of leptin were (9.8+/-2.1) microg/L, (14.2+/-6.7) microg/L, and (19.3+/-7.9) microg/L in patients with severe, mediate and mild obstructive sleep apnea, respectively. Serum leptin levels correlated positively with the degree of OSAHS as reflected by AHI (r = 0. 68, P < 0.01). The leptin concentration of 51 responders after 6 months were significantly decreased (P < 0.01) than that of pre-operation. However, the difference of leptin concentration between pre-operation and post operation was not significant in 9 nonresponders (P > 0.05). CONCLUSIONS: There are higher leptin concentrations in patients with OSAHS, which are significantly correlated to the severity of disease. Serum leptin levels in responders decreased significantly after uvulopalatopharyngoplasty. OSAHS may influence the leptin system, resulting in increased serum leptin level.