SimCalib: Graph Neural Network Calibration based on Similarity between Nodes

Graph neural networks (GNNs) have exhibited impressive performance in modeling graph data as exemplified in various applications. Recently, the GNN calibration problem has attracted increasing attention, especially in cost-sensitive scenarios. Previous work has gained empirical insights on the issue, and devised effective approaches for it, but theoretical supports still fall short. In this work, we shed light on the relationship between GNN calibration and nodewise similarity via theoretical analysis. A novel calibration framework, named SimCalib, is accordingly proposed to consider similarity between nodes at global and local levels. At the global level, the Mahalanobis distance between the current node and class prototypes is integrated to implicitly consider similarity between the current node and all nodes in the same class. At the local level, the similarity of node representation movement dynamics, quantified by nodewise homophily and relative degree, is considered. Informed about the application of nodewise movement patterns in analyzing nodewise behavior on the over-smoothing problem, we empirically present a possible relationship between over-smoothing and GNN calibration problem. Experimentally, we discover a correlation between nodewise similarity and model calibration improvement, in alignment with our theoretical results. Additionally, we conduct extensive experiments investigating different design factors and demonstrate the effectiveness of our proposed SimCalib framework for GNN calibration by achieving state-of-the-art performance on 14 out of 16 benchmarks

A novel endurance prediction method of series connected lithium-ion batteries based on the voltage change rate and iterative calculation.

High-power lithium-ion battery packs are widely used in large and medium-sized unmanned aerial vehicles and other fields, but there is a safety hazard problem with the application that needs to be solved. The generation mechanism and prevention measurement research is carried out on the battery management system for the unmanned aerial vehicles and the lithium-ion battery state monitoring. According to the group equivalent modeling demand of the battery packs, a new idea of compound equivalent circuit modeling is proposed and the model constructed to realize the accurate description of the working characteristics. In order to realize the high-precision state prediction, the improved unscented Kalman feedback correction mechanism is introduced, in which the simplified particle transforming is introduced and the voltage change rate is calculated to construct a new endurance prediction model. Considering the influence of the consistency difference between battery cells, a novel equilibrium state evaluation idea is applied, the calculation results of which are embedded in the equivalent modeling and iterative calculation to improve the prediction accuracy. The model parameters are identified by the Hybrid Pulse Power Characteristic test, in which the conclusion is that the mean value of the ohm internal resistance is 20.68mΩ. The average internal resistance is 1.36mΩ, and the mean capacitance value is 47747.9F. The state of charge prediction error is less than 2%, which provides a feasible way for the equivalent modeling, battery management system design and practical application of pack working lithium-ion batteries

Overexpression Cathepsin D Contributes to Perineural Invasion of Salivary Adenoid Cystic Carcinoma

Objective: Cathepsin D (CTSD) is a pivotal orchestrator in the occurrence and development of tumors. Recently, CTSD was detected in salivary adenoid cystic carcinoma (SACC). However, its functional role in perineural invasion (PNI) of SACC remained elusive. We conducted the present study to detect the expression of CTSD in SACC, analyze the correlation between CTSD expression and prognosis of SACC patients and elucidate the role of CTSD in occurrence of PNI in SACC to lay the foundation for further studies.Methods: Immunohistochemical analysis was conducted to assess CTSD and Ki67 expression in 158 SACC samples and 20 normal salivary gland samples adjacent to carcinoma. Meanwhile, the correlation between CTSD and PNI of SACC specimens was analyzed using Wilcoxon test. QRT-PCR, immunofluorescence and western blot analysis were used to examine the levels of CTSD mRNA and protein in SACC-LM cell line. SiRNA-mediated CTSD silence was performed. Scratch wound healing assay, transwell invasion assay and DRG co-culture assay of PNI was used to detect the ability of migration, invasion and PNI. FITC-phalloidin was used to detect cytoskeletal organization.Results: Our data demonstrated that the positive expression of CTSD was observed in 74.1% (117/158) of SACC cases, and the expression of CTSD was significantly correlated with the PNI (p < 0.05). The ability of migration, invasion, and PNI could be inhibited significantly by siRNA-mediated CTSD silence (p < 0.01). Furthermore, siRNA-mediated CTSD silence inhibited cytoskeletal organization and pseudo foot formation in SACC-LM cells.Conclusion: Our results suggested that an association between PNI and expression of CTSD existed. CTSD may promote PNI of SACC accompanied by cytoskeletal organization and pseudo foot formation

A screening identifies harmine as a novel antibacterial compound against Ralstonia solanacearum

Ralstonia solanacearum, the causal agent of bacterial wilt, is a devastating plant pathogenic bacterium that infects more than 450 plant species. Until now, there has been no efficient control strategy against bacterial wilt. In this study, we screened a library of 100 plant-derived compounds for their antibacterial activity against R. solanacearum. Twelve compounds, including harmine, harmine hydrochloride, citral, vanillin, and vincamine, suppressed bacterial growth of R. solanacearum in liquid medium with an inhibition rate higher than 50%. Further focus on harmine revealed that the minimum inhibitory concentration of this compound is 120 mg/L. Treatment with 120 mg/L of harmine for 1 and 2 h killed more than 90% of bacteria. Harmine treatment suppressed the expression of the virulence-associated gene xpsR. Harmine also significantly inhibited biofilm formation by R. solanacearum at concentrations ranging from 20 mg/L to 60 mg/L. Furthermore, application of harmine effectively reduced bacterial wilt disease development in both tobacco and tomato plants. Collectively, our results demonstrate the great potential of plant-derived compounds as antibacterial agents against R. solanacearum, providing alternative ways for the efficient control of bacterial wilt

Liquid biopsy-based single-cell metabolic phenotyping of lung cancer patients for informative diagnostics.

Accurate prediction of chemo- or targeted therapy responses for patients with similar driver oncogenes through a simple and least-invasive assay represents an unmet need in the clinical diagnosis of non-small cell lung cancer. Using a single-cell on-chip metabolic cytometry and fluorescent metabolic probes, we show metabolic phenotyping on the rare disseminated tumor cells in pleural effusions across a panel of 32 lung adenocarcinoma patients. Our results reveal extensive metabolic heterogeneity of tumor cells that differentially engage in glycolysis and mitochondrial oxidation. The cell number ratio of the two metabolic phenotypes is found to be predictive for patient therapy response, physiological performance, and survival. Transcriptome analysis reveals that the glycolytic phenotype is associated with mesenchymal-like cell state with elevated expression of the resistant-leading receptor tyrosine kinase AXL and immune checkpoint ligands. Drug targeting AXL induces a significant cell killing in the glycolytic cells without affecting the cells with active mitochondrial oxidation

Improved Breath Phase and Continuous Adventitious Sound Detection in Lung and Tracheal Sound Using Mixed Set Training and Domain Adaptation

Previously, we established a lung sound database, HF_Lung_V2 and proposed convolutional bidirectional gated recurrent unit (CNN-BiGRU) models with adequate ability for inhalation, exhalation, continuous adventitious sound (CAS), and discontinuous adventitious sound detection in the lung sound. In this study, we proceeded to build a tracheal sound database, HF_Tracheal_V1, containing 11107 of 15-second tracheal sound recordings, 23087 inhalation labels, 16728 exhalation labels, and 6874 CAS labels. The tracheal sound in HF_Tracheal_V1 and the lung sound in HF_Lung_V2 were either combined or used alone to train the CNN-BiGRU models for respective lung and tracheal sound analysis. Different training strategies were investigated and compared: (1) using full training (training from scratch) to train the lung sound models using lung sound alone and train the tracheal sound models using tracheal sound alone, (2) using a mixed set that contains both the lung and tracheal sound to train the models, and (3) using domain adaptation that finetuned the pre-trained lung sound models with the tracheal sound data and vice versa. Results showed that the models trained only by lung sound performed poorly in the tracheal sound analysis and vice versa. However, the mixed set training and domain adaptation can improve the performance of exhalation and CAS detection in the lung sound, and inhalation, exhalation, and CAS detection in the tracheal sound compared to positive controls (lung models trained only by lung sound and vice versa). Especially, a model derived from the mixed set training prevails in the situation of killing two birds with one stone.Comment: To be submitted, 31 pages, 6 figures, 5 table

Robust single divacancy defects near stacking faults in 4H-SiC under resonant excitation

Color centers in silicon carbide (SiC) have demonstrated significant promise for quantum information processing. However, the undesirable ionization process that occurs during optical manipulation frequently causes fluctuations in the charge state and performance of these defects, thereby restricting the effectiveness of spin-photon interfaces. Recent predictions indicate that divacancy defects near stacking faults possess the capability to stabilize their neutral charge states, thereby providing robustness against photoionization effects. In this work, we present a comprehensive protocol for the scalable and targeted fabrication of single divacancy arrays in 4H-SiC using a high-resolution focused helium ion beam. Through photoluminescence emission (PLE) experiments, we demonstrate long-term emission stability with minimal linewidth shift ($\sim$ 50 MHz over 3 hours) for the single c-axis divacancies within stacking faults. By measuring the ionization rate for different polytypes of divacancies, we found that the divacancies within stacking faults are more robust against resonant excitation. Additionally, angle-resolved PLE spectra reveal their two resonant-transition lines with mutually orthogonal polarizations. Notably, the PLE linewidths are approximately 7 times narrower and the spin-coherent times are 6 times longer compared to divacancies generated via carbon-ion implantation. These findings highlight the immense potential of SiC divacancies for on-chip quantum photonics and the construction of efficient spin-to-photon interfaces, indicating a significant step forward in the development of quantum technologies.Comment: 11 pages, 4 figure

Dual Targeting of 3-Hydroxy-3-methylglutaryl Coenzyme A Reductase and Histone Deacetylase as a Therapy for Colorectal Cancer

AbstractStatins are 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase (HMGR) inhibitors decreasing serum cholesterol and have shown promise in cancer prevention. In this study, we demonstrated the oncogenic role of HMGR in colorectal cancer (CRC) by disclosing increased HMGR activity in CRC patients and its enhancement of anti-apoptosis and stemness. Our previous studies showed that statins containing carboxylic acid chains possessed activity against histone deacetylases (HDACs), and strengthened their anti-HDAC activity through designing HMGR-HDAC dual inhibitors, JMF compounds. These compounds exerted anti-cancer effect in CRC cells as well as in AOM-DSS and ApcMin/+ CRC mouse models. JMF mostly regulated the genes related to apoptosis and inflammation through genome-wide ChIP-on-chip analysis, and Ingenuity Pathways Analysis (IPA) predicted their respective regulation by NR3C1 and NF-κB. Furthermore, JMF inhibited metastasis, angiogenesis and cancer stemness, and potentiated the effect of oxaliplatin in CRC mouse models. Dual HMGR-HDAC inhibitor could be a potential treatment for CRC