Causality of Genetically Determined Metabolites on Chronic Kidney Disease: A Two-Sample Mendelian Randomization Study In Silico.

Introduction: Chronic kidney disease (CKD) is associated with metabolic disorders. However, the evidence for the causality of circulating metabolites to promote or prevent CKD is still lacking. Methods: The two-sample Mendelian randomization (MR) analysis was conducted to evaluate the latent causal relationship between the genetically proxied 486 blood metabolites and CKD. Genome-wide association study (GWAS) data for exposures were derived from 7824 European GWAS on metabolite levels, which have been extensively utilized in the medical field to elucidate the mechanisms underlying disease onset and progression. The random inverse variance weighted (IVW) is the primary analysis for causality analysis while MR-Egger and weighted median as complementary analyses. For the further identification of metabolites, reverse MR and linkage disequilibrium score regression were performed for further evaluation. The drug target for N-acetylornithine was subsequently supplemented into the analysis, with MR and colocalization analysis being utilized. Key metabolic pathways were identified via MetaboAnalyst 4.0 (https://www.metaboanalyst.ca/) online website. Results: N-acetylornithine was identified as a reliable metabolite that increases the susceptibility to estimated glomerular filtration rate (eGFR) decrease (ß = 0.047; 95% confidence interval: -0.068 to -0.026; PIVW = 1.5E-5). The "glyoxylate and dicarboxylate metabolism" pathway showed significant relevance to CKD development (P = 6E-4), whereas the "glycine, serine, and threonine metabolism" pathway was also recognized as associated with CKD by general practitioners (P = 7E-4). Colocalization analysis revealed a robust genetic link between N-acetylornithine and both CKD and eGFR, with 85.1% and 99.4% colocalization rates, respectively. IVW-MR analysis substantiated these findings with a significant positive association for CKD (odds ratio = 1.43, P = 4.7E-5) and a negative correlation with eGFR (b = -0.04, P = 1.13E-31). Conclusions: MR was utilized to explore the potential causal links between 61 genetic serum metabolites and CKD. N-acetylornithine and NAT8 were further explored as a potential therapeutic target for CKD treatment.

In defense of local descriptor-based few-shot object detection.

State-of-the-art image object detection computational models require an intensive parameter fine-tuning stage (using deep convolution network, etc). with tens or hundreds of training examples. In contrast, human intelligence can robustly learn a new concept from just a few instances (i.e., few-shot detection). The distinctive perception mechanisms between these two families of systems enlighten us to revisit classical handcraft local descriptors (e.g., SIFT, HOG, etc.) as well as non-parametric visual models, which innately require no learning/training phase. Herein, we claim that the inferior performance of these local descriptors mainly results from a lack of global structure sense. To address this issue, we refine local descriptors with spatial contextual attention of neighbor affinities and then embed the local descriptors into discriminative subspace guided by Kernel-InfoNCE loss. Differing from conventional quantization of local descriptors in high-dimensional feature space or isometric dimension reduction, we actually seek a brain-inspired few-shot feature representation for the object manifold, which combines data-independent primitive representation and semantic context learning and thus helps with generalization. The obtained embeddings as pattern vectors/tensors permit us an accelerated but non-parametric visual similarity computation as the decision rule for final detection. Our approach to few-shot object detection is nearly learning-free, and experiments on remote sensing imageries (approximate 2-D affine space) confirm the efficacy of our model.

A bias voltage controlled electrode-molecule interface in single-molecule junctions.

Tuning the electrode-molecule interface stands at the heart of functional single-molecule devices. Herein, we report that the electrode-molecule interface of difluoro-substituted benzothiadiazole (FBTZ)-based single-molecule junctions can be modulated by the bias voltage. At low bias voltage (100 mV), the dative Au-N linkage is formed and at high bias voltage (600 mV), a covalent Au-C linkage is constructed. These junctions show distinct conductance. Interestingly, dominant charge carriers in Au-N- and Au-C-based junctions are different, as evidenced by dft calculations. These results provide a new strategy for regulating the electrode-molecule interface, which will advance the development of molecular electronics.

Memristor based on carbon nanotube gelatin composite film as artificial optoelectronic synapse for image processing.

Photoelectric artificial synapses based on memristors is an effective method to realize neuromorphic computation. This study presents an optoelectronic responsive artificial synapse made of a composite material consisting of gelatin and carbon nanotubes. The memristor demonstrates characteristics of analog resistive switching, the ability to store multiple memory states, and impressive retention properties. It has the capability to induce an excitatory post-synaptic current by means of electrical pulses or pulsed light exposure. The excitatory post-synaptic current can be modulated by the number, amplitude and interval of electrical pulses, as well as the action time, interval and light intensity of optical pulses. The artificial synapse showcases the emulation of fundamental Hebbian learning protocols, including spike timing dependent plasticity and spike amplitude dependent plasticity. In addition, the charge transfer in the carbon nanotube gelatin composite optoelectronic memristor is investigated through first-principles calculations, shedding light on its operational mechanism. Experimental results show that these devices have the potential to be utilized for processing image information, resulting in a significant reduction of input data and training expenses when recognizing handwritten numbers. Overall, the optoelectronic synapse exhibits promising image processing prospects in the field of neuromorphic computing.

Suppressing the Conductance of Single-Molecule Junctions Fabricated by sp2 C-H Bond Metalation.

High-conducting single-molecule junctions have attracted a great deal of attention, but insulating single-molecule junctions, which are critical in molecular circuits, have been less investigated due to the long-standing challenges. Herein, the in situ formation of a Au-C linker via electrical-potential-mediated sp2 C-H bond metalation of polyfluoroarenes with the assistance of scanning tunneling microscope-based break junction technique is reported. This metalation process is bias-dependent and occurs with an electropositive electrode, and the formed junction is highly oriented. Surprisingly, these polyfluoroarenes exhibit unexpected low conductance even under short molecular lengths and are superior molecular insulators. Flicker noise analysis and DFT calculations confirm that the insulating properties of polyfluoroarenes are ascribed to their multiple fluorine substituents. Our results pave a way for constructing oriented asymmetric molecular junctions and provide an efficient strategy to suppress the single-molecule conductance, which will aid in the design of molecular insulators and advance the development of self-integrating functional molecular circuits.

[Establishment of a Predictive Model for Chronic Cough after Pulmonary Resection].

BACKGROUND: Chronic cough after pulmonary resection is one of the most common complications, which seriously affects the quality of life of patients after surgery. Therefore, the aim of this study is to explore the risk factors of chronic cough after pulmonary resection and construct a prediction model. METHODS: The clinical data and postoperative cough of 499 patients who underwent pneumonectomy or pulmonary resection in The First Affiliated Hospital of University of Science and Technology of China from January 2021 to June 2023 were retrospectively analyzed. The patients were randomly divided into training set (n=348) and validation set (n=151) according to the principle of 7:3 randomization. According to whether the patients in the training set had chronic cough after surgery, they were divided into cough group and non-cough group. The Mandarin Chinese version of Leicester cough questionnare (LCQ-MC) was used to assess the severity of cough and its impact on patients' quality of life before and after surgery. The visual analog scale (VAS) and the self-designed numerical rating scale (NRS) were used to evaluate the postoperative chronic cough. Univariate and multivariate Logistic regression analysis were used to analyze the independent risk factors and construct a model. Receiver operator characteristic (ROC) curve was used to evaluate the discrimination of the model, and calibration curve was used to evaluate the consistency of the model. The clinical application value of the model was evaluated by decision curve analysis (DCA). RESULTS: Multivariate Logistic analysis screened out that preoperative forced expiratory volume in the first second/forced vital capacity (FEV1/FVC), surgical procedure, upper mediastinal lymph node dissection, subcarinal lymph node dissection, and postoperative closed thoracic drainage time were independent risk factors for postoperative chronic cough. Based on the results of multivariate analysis, a Nomogram prediction model was constructed. The area under the ROC curve was 0.954 (95%CI: 0.930-0.978), and the cut-off value corresponding to the maximum Youden index was 0.171, with a sensitivity of 94.7% and a specificity of 86.6%. With a Bootstrap sample of 1000 times, the predicted risk of chronic cough after pulmonary resection by the calibration curve was highly consistent with the actual risk. DCA showed that when the preprobability of the prediction model probability was between 0.1 and 0.9, patients showed a positive net benefit. CONCLUSIONS: Chronic cough after pulmonary resection seriously affects the quality of life of patients. The visual presentation form of the Nomogram is helpful to accurately predict chronic cough after pulmonary resection and provide support for clinical decision-making.

Fundamental, mechanism and development of hydration lubrication: From bio-inspiration to artificial manufacturing.

Friction and lubrication are ubiquitous in all kinds of movements and play a vital role in the smooth operation of production machinery. Water is indispensable both in the lubrication systems of natural organisms and in hydration lubrication systems. There exists a high degree of similarity between these systems, which has driven the development of hydration lubrication from biomimetic to artificial manufacturing. In particular, significant advancements have been made in the understanding of the mechanisms of hydration lubrication over the past 30 years. This enhanced understanding has further stimulated the exploration of biomimetic inspiration from natural hydration lubrication systems, to develop novel artificial hydration lubrication systems that are cost-effective, easily transportable, and possess excellent capability. This review summarizes the recent experimental and theoretical advances in the understanding of hydration-lubrication processes. The entire paper is divided into three parts. Firstly, surface interactions relevant to hydration lubrication are discussed, encompassing topics such as hydrogen bonding, hydration layer, electric double layer force, hydration force, and Stribeck curve. The second part begins with an introduction to articular cartilage in biomaterial lubrication, discussing its compositional structure and lubrication mechanisms. Subsequently, three major categories of bio-inspired artificial manufacturing lubricating material systems are presented, including hydrogels, polymer brushes (e.g., neutral, positive, negative and zwitterionic brushes), hydration lubricant additives (e.g., nano-particles, polymers, ionic liquids), and their related lubrication mechanism is also described. Finally, the challenges and perspectives for hydration lubrication research and materials development are presented.