Integration of Metabolomics, Lipidomics, and Proteomics Reveals the Metabolic Characterization of Nonalcoholic Steatohepatitis.

Metabolic dysfunction is associated with nonalcoholic steatohepatitis (NASH) development. However, omics studies investigating metabolic changes in NASH patients are limited. In this study, metabolomics and lipidomics in plasma, as well as proteomics in the liver, were performed to characterize the metabolic profiles of NASH patients. Moreover, the accumulation of bile acids (BAs) in NASH patients prompted us to investigate the protective effect of cholestyramine on NASH. The liver expression of essential proteins involved in FA transport and lipid droplets was significantly elevated in patients with NASH. Furthermore, we observed a distinct lipidomic remodeling in patients with NASH. We also report a novel finding suggesting an increase in the expression of critical proteins responsible for glycolysis and the level of glycolytic output (pyruvic acid) in patients with NASH. Furthermore, the accumulation of branched chain amino acids, aromatic amino acids, purines, and BAs was observed in NASH patients. Similarly, a dramatic metabolic disorder was also observed in a NASH mouse model. Cholestyramine not only significantly alleviated liver steatosis and fibrosis but also reversed NASH-induced accumulation of BAs and steroid hormones. In conclusion, NASH patients were characterized by perturbations in FA uptake, lipid droplet formation, glycolysis, and accumulation of BAs and other metabolites.

Upgulation of lncRNA GASL1 inhibits atherosclerosis by regulating miR-106a/LKB1 axis.

BACKGROUND: Atherosclerosis (AS) is a common frequently-occurring disease in the clinic and a serious threat to human health. This research aimed to explore the value between GASL1 and AS. METHODS: The expression and values of GASL1 in AS patients were revealed by qRT-PCR and ROC curve. The HUVEC cells were induced by ox-LDL to construct in-vitro models. Cell viability was detected by MTT assay, and apoptosis was detected by flow cytometry. The inflammatory situation was reflected by the ELISA assay. Double luciferase reporter gene assay verified the regulatory relationship between GASL1 and miR-106a, miR-106a and LKB1. RESULTS: The levels of GASL1 was lower in AS group than those in control group. The value of GASL1 in predicting AS patients was also tested by the ROC curve. After HUVEC cells were induced by ox-LDL, the levels of GASL1 and LKB1 decreased significantly, while the level of miR-106a increased significantly. Upregulation of LKB1 reversed the effect of upregulation of GASL1 on viability, apoptosis, and inflammation of HUVEC cells induced by ox-LDL. CONCLUSION: Overexpression of GASL1 might suppress ox-LDL-induced HUVEC cell viability, apoptosis, and inflammation by regulating miR-106a/LKB1 axis.

Active Fault Isolation for Multimode Fault Systems Based on a Set Separation Indicator.

This paper considers the active fault isolation problem for a class of uncertain multimode fault systems with a high-dimensional state-space model. It has been observed that the existing approaches in the literature based on a steady-state active fault isolation method are often accompanied by a large delay in making the correct isolation decision. To reduce such fault isolation latency significantly, this paper proposes a fast online active fault isolation method based on the construction of residual transient-state reachable set and transient-state separating hyperplane. The novelty and benefit of this strategy lies in the embedding of a new component called the set separation indicator, which is designed offline to distinguish the residual transient-state reachable sets of different system configurations at any given moment. Based on the results delivered by the set separation indicator, one can determine the specific moments at which the deterministic isolation is to be implemented during online diagnostics. Meanwhile, some alternative constant inputs can also be evaluated for isolation effects to determine better auxiliary excitation signals with smaller amplitudes and more differentiated separating hyperplanes. The validity of these results is verified by both a numerical comparison and an FPGA-in-loop experiment.

1,2-Difunctionalization of Acetylene Enabled by Light.

Although the direct conversion of gaseous acetylene into value-added liquid commodity chemicals is becoming increasingly attractive, the majority of the established methodologies are focused on cross-coupling, hydro-functionalization, and polymerization. Herein, we describe a 1,2-difunctionalization method that inserts acetylene directly into readily available bifunctional reagents. This method provides access to diverse C2-linked 1,2-bis-heteroatom products in high regio- and stereoselectivity along with opening up previously unexplored synthetic directions. In addition, we demonstrate this method's synthetic potential by converting the obtained products into diverse functionalized molecules and chiral sulfoxide-containing bidentate ligands. Using a combination of experimental and theoretical methods, the mechanism for this insertion reaction was investigated.

Constrained Active Fault Tolerant Control Based on Active Fault Diagnosis and Interpolation Optimization.

A new active fault tolerant control scheme based on active fault diagnosis is proposed to address the component/actuator faults for systems with state and input constraints. Firstly, the active fault diagnosis is composed of diagnostic observers, constant auxiliary signals, and separation hyperplanes, all of which are designed offline. In online applications, only a single diagnostic observer is activated to achieve fault detection and isolation. Compared with the traditional multi-observer parallel diagnosis methods, such a design is beneficial to improve the diagnostic efficiency. Secondly, the active fault tolerant control is composed of outer fault tolerant control, inner fault tolerant control and a linear-programming-based interpolation control algorithm. The inner fault tolerant control is determined offline and satisfies the prescribed optimal control performance requirement. The outer fault tolerant control is used to enlarge the feasible region, and it needs to be determined online together with the interpolation optimization. In online applications, the updated state estimates trigger the adjustment of the interpolation algorithm, which in turn enables control reconfiguration by implicitly optimizing the dynamic convex combination of outer fault tolerant control and inner fault tolerant control. This control scheme contributes to further reducing the computational effort of traditional constrained predictive fault tolerant control methods. In addition, each pair of inner fault tolerant control and diagnostic observer is designed integratedly to suppress the robust interaction influences between estimation error and control error. The soft constraint method is further integrated to handle some cases that lead to constraint violations. The effectiveness of these designs is finally validated by a case study of a wastewater treatment plant model.

MEOL: A Maximum-Entropy Framework for Options Learning.

Options, the temporally extended courses of actions that can be taken at varying time scale, have provided a concrete, key framework for learning levels of temporal abstraction in hierarchical tasks. While methods of learning options end-to-end is well researched, how to explore good options and actions simultaneously is still challenging. We address this issue by maximizing reward augmented with entropies of both option and action selection policy in options learning. To this end, we reveal our novel optimization objective by reformulating options learning from perspective of probabilistic inference and propose a soft options iteration method to guarantee convergence to the optimum. In implementation, we propose an off-policy algorithm called the maximum-entropy options critic (MEOC) and evaluate it on series of continuous control benchmarks. Comparative results demonstrate that our method outperforms baselines in efficiency and final result on most benchmarks, and the performance exhibits superiority and robustness especially on complex tasks. Ablated studies further explain that entropy maximization on hierarchical exploration promotes learning performance through efficient options specialization and multimodality in action level.

Feasibility and safety study of advanced prostate biopsy robot system based on MR-TRUS Image flexible fusion technology in animal experiments.

The advanced prostate biopsy robot system has broad application prospects in clinical practice, but due to the deformation and distortion between MR-TRUS (magnetic resonance transrectal ultrasound) images, it poses challenges in biopsy accuracy and safety. The study utilized an advanced prostate biopsy robot system based on MR-TRUS image flexible registration technology and conducted experiments on animal models. Retrospective analysis of the puncture accuracy of 12 animal experiments undergoing prostate puncture using MR-TRUS flexible registration technology from May 2022 to October 2023, and observation of intraoperative and 7-day postoperative complications. The study obtained MR-TRUS images and utilized image processing algorithms for registration to reduce image deformation and distortion. Then, precise positioning and operation are carried out through the robot system to execute the prostate biopsy program. The experimental results indicate that the advanced prostate biopsy robot system based on MR-TRUS image flexible registration technology has demonstrated good feasibility and safety in animal experiments. Image registration technology has successfully reduced image distortion and deformation, improving biopsy accuracy. The precise positioning and operation of robot systems play a crucial role in the biopsy process, reducing the occurrence of complications.

Risk factors and prognostic modeling in bridging extracorporeal membrane oxygenation patients before lung transplantation.

Background: The increased use of preoperative extracorporeal membrane oxygenation (ECMO) as a life support system before lung transplantation demands a better understanding of the associated prognostic factors. This study aims to discern the critical factors influencing the survival outcomes of ECMO patients and design a prognostic model tailored to this patient group. Methods: We retrospectively gathered and analyzed baseline and clinical data of patients who underwent preoperative bridging ECMO before lung transplantation from the United Network for Organ Sharing (UNOS) database. Univariate and multivariate Cox regression analyses were conducted and a prognostic model was generated to identify the independent factors influencing survival outcomes in these patients. The predictive model was cross-validated using the k-fold method where k=5. Results: Our study included 1,202 patients. Both single and multiple analyses showed that age over 51 years, high body mass index (BMI), a history of dialysis before transplantation, donor hypertension, prolonged cold ischemia time, and high serum total bilirubin are adverse prognostic factors for the survival of ECMO-bridged lung transplant patients. Using the multivariate analysis, we created a prognosis model and a nomogram to predict 1-year post-transplant survival, with a receiver operating characteristic (ROC) curve area of 0.760 in internal validation. The 1-year survival rate calibration curve supported the nomogram's accuracy. Conclusions: This study involved the development of a survival prognosis model for patients undergoing lung transplantation with preoperative ECMO bridging, which was validated through extensive data analysis. The prognosis model exhibited high accuracy and predictive capability, effectively predicting the survival outcomes of patients both pre- and post-surgery.

Persteroid, a new steroid from the marine-derived fungus Penicillium sp. ZYX-Z-143.

A new steroid named persteroid (1) and seven known compounds (2-8) were isolated from the marine-derived fungus Penicillium sp. ZYX-Z-143. The structure of 1 was determined by HRESIMS, NMR, and ECD calculations. Compound 1 showed inhibitory activity against protein tyrosine phosphatase 1B (PTP1B) with IC50 value of 46.31 ± 0.52 µM. Moreover, compound 1 potently suppressed nitric oxide (NO) production on lipopolysaccharide (LPS)-stimulated RAW264.7 macrophages. The cytotoxicity and antibacterial activity of all isolates were tested.

[Development and Validation of A Prognostic Nomogram to Guide Decision-making 
in Lung Large Cell Neuroendocrine Carcinoma].

BACKGROUND: Lung large cell neuroendocrine carcinoma (LCNEC) is a rare and highly malignant lung tumor with a poor prognosis. Currently, most research on LCNEC is based on retrospective studies and lacks validation in the real world. The study aims to identify independent risk factors and establish and validate a predictive model for the prognosis of LCNEC. METHODS: Patient data were extracted from Surveillance, Epidemiology, and End Results (SEER) and our department's hospitalization records from 2010 to 2015 and 2016 to 2020, respectively. Kaplan-Meier analysis was used to evaluate overall survival (OS). OS is defined as the time from diagnosis to death or last follow-up for a patient. Univariate and multivariate Cox regression analyses were performed to identify significant prognostic factors and construct a Nomogram for predicting the prognosis of LCNEC. RESULTS: In total, 1892 LCNEC patients were included and divided into a training cohort (n=1288) and two validation cohorts (n=552, n=52). Univariate Cox regression analysis showed that age, gender, primary tumor site, laterality, T stage, N stage, M stage, surgery, and radiotherapy were factors that could affect the prognosis of LCNEC patients (P<0.05). Multivariate Cox analysis indicated that age, gender, primary tumor site, T stage, N stage, M stage, surgery, and radiotherapy were independent risk factors for the prognosis of LCNEC patients (P<0.05). Calibration curves and the concordance index (internal: 0.744±0.015; external: 0.763±0.020, 0.832±0.055) demonstrated good predictive performance of the model. CONCLUSIONS: Patients aged ≥65 years, male, with advanced tumor-node-metastasis (TNM) staging, and who have not undergone surgery or radiotherapy have a poor prognosis. Nomogram can provide a certain reference for personalized clinical decision-making for patients.

Fuzzy Boundary Control for Nonlinear Delayed DPSs Under Boundary Measurements.

For nonlinear delayed distributed parameter systems (DDPSs), this article considers a fuzzy boundary control (FBC) under boundary measurements (BMs). Initially, we accurately describe the nonlinear DDPS through a Takagi-Sugeno (T-S) fuzzy partial differential-difference equation (PDDE). Then, in accordance with the T-S fuzzy PDDE model, an FBC design under BMs ensuring the exponential stability for closed-loop DDPS is subsequently presented by spatial linear matrix inequalities (SLMIs) via using Wirtinger's inequality, Halanay's inequality, and the Lyapunov direct method, which respects the fast-varying and slow-varying delays. Moreover, we formulate SLMIs as LMIs for solving the fuzzy boundary controller design of nonlinear DDPSs under BMs. Finally, the effectiveness of the proposed FBC strategy is presented via simulation examples.

Comprehensive Analysis of the miRNA-mRNA Pathological Regulatory Network of Intestinal CD4 + T Cells in Parkinson's Disease.

Infiltration of CD4 + T cells was found in brain tissue samples from PD patients, suggesting their involvement in developing central nervous system (CNS) disease. The idea of the gut-brain axis further corroborates intestinal T cells' activation as the central immune response initiation. However, the specific factors and molecular pathways regulating intestinal T-cell activation are unclear. We used the GSE156287 and GSE145814 datasets from the GEO database to analyze and obtain the miRNAs, which are aberrantly expressed in intestinal CD4 + T cells in PD patients and predict their regulatory target mRNAs. Further, combined with the GSE174473 dataset of CD4 + T cells sequencing in PD patients, we finally clarified the aberrant genes expressed in CD4 + T cells from the intestine of PD patients and constructed a miRNA-mRNA regulatory network. The highlight of our findings showed pathways, networks, biological functions, and key molecules potentially involved in the miRNA-mediated functional effects in CD4 + T cell from the intestine of PD patients. The hsa-miR-3180-3p mediated CBX8, etc. were determined as most effective in enhancing T cell survival. PEG10, etc. regulated by hsa-miR-20a-3p targets were possibly involved in T cell differentiation. The JPT2 regulated by hsa-miR-1281 were involved in influencing T cell infiltration. The discovery of this interaction between miRNA and mRNA in CD4 + T cell has important implications for understanding the intestinal initial of PD pathological molecular and anti-inflammation of T cell activation.

Increased Serum S100ß Concentration is Associated with Depression in Parkinson's Disease.

Purpose: To explore the relationship between the serum level of S100 calcium-binding protein, beta chain (S100ß) and Parkinson's disease (PD) with depression. Patients and Methods: A total of 145 patients with PD and 60 healthy controls matched for sex, age, and years of education in our hospital were selected. Fluorescence quantitative immunochromatography was used to quantify the level of S100ß in serum. Clinical manifestations were assessed by Unified Parkinson's Disease Rating Scale part-III (UPDRS-III), Hoehn & Yahr (H-Y) stage and 17-item Hamilton Rating Scale for Depression (HAMD-17). According to the results of HAMD-17, PD patients were divided into PD with depression group and PD without depression group. The relationship between serum S100ß and HAMD-17 scores in PD patients with depression was investigated through correlation analysis and multivariate regression analysis, and receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of serum S100ß. Results: The level of serum S100ß in PD with depression group was significantly higher than that in PD without depression group and control group. In PD patients with depression, serum S100ß level was positively correlated with UPDRS-III score, H-Y Scale and HAMD-17 score. The HAMD-17 score was positively correlated with the UPDRS-III and H-Y scales, and the increase in the HAMD-17 score was associated with women. Elevated serum S100ß level and UPDRS-III score are independent risk factors for PD with depression. Analysis of receiver operating characteristic (ROC) curves showed that the serum S100ß level with a cutoff of 0.28 ng/mL distinguished patients with PD with or without depression with an area under the ROC curve (AUC) of 0.742, sensitivity of 0.696, and specificity of 0.779. Conclusion: The serum S100ß level could be a biomarker of PD with depression.

Adaptive event-triggered extended dissipative synchronization of delayed reaction-diffusion neural networks under deception attacks.

Under spatially averaged measurements (SAMs) and deception attacks, this article mainly studies the problem of extended dissipativity output synchronization of delayed reaction-diffusion neural networks via an adaptive event-triggered sampled-data (AETSD) control strategy. Compared with the existing ETSD control methods with constant thresholds, our scheme can be adaptively adjusted according to the current sampling and latest transmitted signals and is realized based on limited sensors and actuators. Firstly, an AETSD control scheme is proposed to save the limited transmission channel. Secondly, some synchronization criteria under SAMs and deception attacks are established by utilizing Lyapunov-Krasovskii functional and inequality techniques. Then, by solving linear matrix inequalities (LMIs), we obtain the desired AETSD controller, which can satisfy the specified level of extended dissipativity behaviors. Lastly, one numerical example is given to demonstrate the validity of the proposed method.

Fuzzy Boundary Sampled-Data Control for Nonlinear Parabolic DPSs.

For a nonlinear parabolic distributed parameter system (DPS), a fuzzy boundary sampled-data (SD) control method is introduced in this article, where distributed SD measurement and boundary SD measurement are respected. Initially, this nonlinear parabolic DPS is represented precisely by a Takagi-Sugeno (T-S) fuzzy parabolic partial differential equation (PDE) model. Subsequently, under distributed SD measurement and boundary SD measurement, a fuzzy boundary SD control design is obtained via linear matrix inequalities (LMIs) on the basis of the T-S fuzzy parabolic PDE model to guarantee exponential stability for closed-loop parabolic DPS by using inequality techniques and a LF. Furthermore, respecting the property of membership functions, we present some LMI-based fuzzy boundary SD control design conditions. Finally, the effectiveness of the designed fuzzy boundary SD controller is demonstrated via two simulation examples.

Pinning Spatiotemporal Sampled-Data Synchronization of Coupled Reaction-Diffusion Neural Networks Under Deception Attacks.

In this article, we investigate the pinning spatiotemporal sampled-data (SD) synchronization of coupled reaction-diffusion neural networks (CRDNNs), which are directed networks with SD in time and space communications under random deception attacks. In order to handle with the random deception attacks, we establish a directed CRDNN model, which respects the impacts of variable sampling and random deception attacks within a unified framework. Through the designed pinning spatiotemporal SD controller, sufficient conditions are obtained by linear matrix inequalities (LMIs) that guarantee the mean square exponential stability of the synchronization error system (SES) derived by utilizing inequality techniques, the stochastic analysis technique, and Lyapunov-Krasovskii functional (LKF). Finally, a numerical example is utilized to support the presented pinning spatiotemporal SD synchronization method.

Different nodal upstaging rates and prognoses for patients with clinical T1N0M0 lung adenocarcinoma classified according to the presence of solid components in the lung and mediastinal windows.

Background: Little is known about the correlation between nodal upstaging and pulmonary nodules classified according to the presence of solid components in the lung and mediastinal windows. This study thus aimed to analyze the risk factors of nodal upstaging and prognosis based on different imaging features, clinical characteristics, and pathological results from patients with clinical stage T1N0M0 lung adenocarcinoma. Methods: A total of 340 patients between January 2016 and June 2017 were selected from the Affiliated Hospital of Qingdao University database. Imaging features, clinical characteristics, and pathological results were collected for survival and analysis of nodal upstaging risk factors. We used logistic regression models to identify important metastatic risk factors for nodal upstaging. Survival rates were calculated using Kaplan-Meier (KM) survival curves and compared with the log-rank test. Significant prognostic risk factors were identified using the Cox proportional hazards model. Results: A total of 340 patients, with an average age of 64.89 (±8.775) years, were enrolled. Among them, nonnodal upstaging occurred both in 77 (22.6%) patients with pure ground-glass nodules (pGGNs) and in 30 (8.8%) patients with heterogenous ground-glass nodules (hGGNs). Compared to the 92 (27.1%) patients with real part-solid nodules (rPSNs), the 141 (41.5%) patients with solid nodules were significantly different in terms of in nodal upstaging (P<0.001). Moreover, preoperative carcinoembryonic antigen (CEA) level >3.4 µg/L [odds ratio (OR): 2.931; 95% confidence interval (CI): 1.511-5.688; P=0.001], imaging tumor size >18.3 mm (OR, 3.482; 95% CI: 1.609-7.535; P=0.002), and consolidation tumor ratio (CTR) >0.788 (OR 8.791; 95% CI: 3.570-21.651; P<0.001) were independent risk factors for nodal upstaging. The KM survival curve results showed that patients with pGGNs and those with hGGNs had a much better 5-year disease-free survival (DFS) and 5-year overall survival (OS) than did those with rPSNs and those with solid nodules (DFS: 98.7% vs. 100% vs. 81.4% vs. 73.7%, P<0.001; OS: 97.4% vs. 100% vs. 90.2% vs. 83.7%, P=0.003). In the multivariate Cox regression analysis of patients with rPSNs and solid nodules, tumor location and pathological lymph node grade were found to be independent risk factors for DFS and OS. Conclusions: Patients with pGGNs and those with hGGNs were more likely to be free of nodal upstaging and had better prognosis than did those with clinical stage IA rPSNs and solid nodules. The patients with pGGNs or hGGNs with preoperative CEA level <3.4 µg/L, imaging tumor size <18.3 mm, and CTR <0.788 can choose systematic lymph node sampling (SLNS) or decline lymph node dissection to avoid postoperative complications.

Combined metabolomic and lipidomic analysis uncovers metabolic profile and biomarkers for papillary thyroid carcinoma.

Papillary thyroid carcinoma (PTC) is the most common endocrine malignancy with a rapidly increasing incidence. The pathogenesis of PTC is unclear, but metabolic and lipidomic reprogramming may play a role in tumor growth. We applied ultra-performance liquid chromatography-tandem mass spectrometry to perform widely targeted metabolomics and lipidomics on plasma samples from 94 patients with PTC and 100 healthy controls. We identified 113 differential metabolites and 236 differential lipids, mainly involved in branched-chain amino acid metabolism, glutamate and glutamine metabolism, tricarboxylic acid cycle, and lipid metabolism. We also screened three potential metabolite biomarkers: sebacic acid, L-glutamine, and indole-3-carboxaldehyde. These biomarkers showed excellent diagnostic performance for PTC in both discovery and validation cohorts, with areas under the receiver operating characteristic curves of 0.994 and 0.925, respectively. Our findings reveal distinct metabolic and lipidomic features of PTC and provide novel targets for diagnosis and treatment.

Randomized Trial of Modified Chest Tube Placement vs Routine Placement After Lung Resection.

BACKGROUND: Chest tube placement after pulmonary resection is usually considered a mandatory procedure. However, peritubular leakage of pleural fluid and intrathoracic air is frequent after surgery. Therefore, we separated the chest tube from the intercostal space as a modified placement strategy. METHODS: Patients undergoing robotic and video-assisted lung resection were enrolled in this study at our medical center between February 2021 and August 2021. All patients were randomly divided into either the modified group (n = 98) or the routine group (n = 101). The incidence of peritubular leakage of pleural fluid and peritubular air leaking or entering after surgery were the primary end points of the study. RESULTS: A total of 199 patients were randomized. Patients in the modified group had lower incidence of peritubular leakage of pleural fluid (after surgery, 39.6% vs 18.4% [P = .001]; after chest tube removal, 26.7% vs 11.2% [P = .005]), lower incidence of peritubular air leaking or entering (14.9% vs 5.1% [P = .022]), and fewer dressing changes (5.02 ± 2.30 vs 3.48 ± 0.94 [P < .001]). In patients undergoing lobectomy and segmentectomy, the type of chest tube placement was associated with the severity of peritubular pleural fluid leakage (P < .05). CONCLUSIONS: The modified chest tube placement was safe and had better clinical efficacy than the routine type. The reduction of postoperative peritubular leakage of pleural fluid resulted in better wound recovery. This modified strategy should be popularized, especially in patients undergoing pulmonary lobectomy or segmentectomy.

Thiol-Yne click chemistry of acetylene-enabled macrocyclization.

Macrocycles have fascinated scientists for over half a century due to their aesthetically appealing structures and broad utilities in chemical, material, and biological research. However, the efficient preparation of macrocycles remains an ongoing research challenge in organic synthesis because of the high entropic penalty involved in the ring-closing process. Herein we report a photocatalyzed thiol-yne click reaction to forge diverse sulfur-containing macrocycles (up to 35-membered ring) and linear C2-linked 1,2-(S-S/S-P/S-N) functionalized molecules, starting from the simplest alkyne, acetylene. Preliminary mechanistic experiments support a visible light-mediated radical-polar crossover dihydrothiolation process. This operationally straightforward reaction is also amenable to the synthesis of organometallic complexes, bis-sulfoxide ligand and a pleuromutilin antibiotic drug Tiamulin, which provides a practical route to synthesize highly valued compounds from the feedstock acetylene gas.