An Aperiodic-Sampling-Dependent Event-Triggered Control Strategy for Interval Type-2 Fuzzy Systems: New Communication Scheme and Discontinuous Functional.

This article studies the event-triggered control problem of interval type-2 (IT2) fuzzy systems. It proposes a new aperiodic-sampling-dependent event-triggered communication scheme, and introduces an improved sampling-dependent discontinuous functional. First, taking into account that the system is with aperiodic sampling, the weighting matrices used for judgement in the event-triggered scheme are designed to be related to each sampling interval or its upper and lower bounds, according to the sampling interval being predictable or not. This design makes the scheme more flexible, thereby improving control effectiveness. Second, a sampling-dependent discontinuous functional is introduced into event-triggered control, which contains matrix variables depending on the aperiodic sampling, and incorporates an improved discontinuous term and a vector related to event-triggered condition. Thus, the functional reduces the conservativeness of stability and stabilization criteria. Based on the above aperiodic-sampling-dependent strategy, the derived results achieve better event-triggered control effects compared with the recent literature. At the end, two examples are given to validate the theoretical effectiveness and advantages of the results under various parameters.

Disturbance Observer-Based H∞ Control for Interval Type-2 Fuzzy Hidden Markov Jump Systems Subject to Deception Attacks.

This article presents a composite anti-disturbance security control approach for the continuous-time nonlinear hidden Markov jump systems, in which the nonlinearities are characterized by the interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy model. To offset and suppress the influence of multiple disturbances on the system stability, a composite control method based on disturbance observer and H∞ control is established. In addition, considering potential cyber-attacks, this article takes deception attacks as an example, assuming that the attack signal is generated by a nonlinear bounded function, and the Bernoulli distribution is employed to depict whether the attack occurs or not. Then, in accordance with the IT2 T-S fuzzy model, the final composite system is derived. With the help of tools, such as the Lyapunov stability theory and fuzzy theory, the stability of the target system is analysed, and the specific forms of the fuzzy composite controller and disturbance observer are obtained. Finally, the correctness and effectiveness of the control method proposed in this article are verified through two examples.

The Human Phospholipase B-II Precursor (HPLBII-P) in Urine as a Novel Biomarker of Glomerular Activity in COVID-19 and Diabetes Mellitus.

Background: The human phospholipase B-II precursor (HPLBII-P) was originally purified from white blood cells but is also found in other cellular structures, such as kidney glomeruli and tubuli. The objective of this report was to investigate the relationship of HPLBII-P in urine to acute kidney injury in patients with COVID-19. Methods: Urine was collected at admission from 132 patients with COVID-19 admitted to the intensive care units (ICUs) because of respiratory failure. HPLBII-P was measured using a sensitive ELISA. For comparison, human neutrophil lipocalin (HNL) was measured in urine, using the ELISA configured with the monoclonal antibody 763/8F, as a sign of tubular affection in addition to routine biomarkers of kidney disease. Results: Overall, the concentrations of urinary HPLBII-P were almost 3-fold higher in patients with COVID-19 compared to healthy controls (p < 0.0001) and with significantly higher concentrations even in patients with COVID-19 without signs of acute kidney injury (AKI) (p < 0.001). HPLBII-P was further increased in patients with AKI (p < 0.02). HPLBII-P was significantly increased in patients with diabetes mellitus (p = 0.0008) and correlated to plasma glucose (r = 0.29, p = 0.001) and urine albumin concentrations (r = 0.55, p < 0.001). Conclusions: Urine concentrations of HPLBII-P are highly raised in the urine of patients with COVID-19 and relate to AKI and diabetes mellitus. HPLBII-P may reflect glomerular injury and/or increased glomerular cell activity in SARS-CoV-2 infections.

The Human Phospholipase B-II Precursor (HPLBII-P) in Urine as a Novel Biomarker of Increased Glomerular Production or Permeability in Diabetes Mellitus?

Background: A previous report showed that the urine output of HPLBII-P in patients with diabetes mellitus and SARS-CoV-2 infection was increased as a sign of glomerular dysfunction. The aim of this report was to investigate the relation of the urine output of HPLBII-P to diabetes mellitus in two large community-based elderly populations, i.e., the ULSAM and PIVUS cohorts. Methods: HPLBII-P was measured by an ELISA in the urine of a community-based cohort of 839 men (ULSAM) collected at 77 years of age and in the urine of a community-based cohort of 75-year-old men, n = 387, and women, n = 401 (PIVUS). KIM-1, NGAL, and albumin were measured in urine and cathepsin S and cystatin C in serum. Results: HPLBII-P was significantly raised among males with diabetes in the ULSAM (p < 0.0001) and PIVUS cohorts (p ≤ 0.02), but not in the female cohort of PIVUS. In the female subpopulation of insulin-treated diabetes, HPLBII-P was raised (p = 0.02) as compared to women treated with oral antidiabetics only. In the ULSAM cohort, HPLBII-P was correlated to NGAL, KIM-1, and albumin in urine both in non-DM (all three biomarkers; p < 0.0001) and in DM (NGAL; p = 0.002, KIM-1; p = 0.02 and albumin; p = 0.01). Plasma glucose and HbA1c in blood showed correlations to U-HPLBII-P (r = 0.58, p < 0.001 and r = 0.42, p = 0.004, respectively). U-HPLBII-P and cathepsin S were correlated in the ULSAM group (r = 0.50, p < 0.001). No correlations were observed between U-HPLBII-P and serum creatinine or cystatin C. Conclusions: The urine measurement of HPLBII-P has the potential to become a novel and useful biomarker in the monitoring of glomerular activity in diabetes mellitus.

LILRB2 promotes immune escape in breast cancer cells via enhanced HLA-A degradation.

PURPOSE: Increased expression of leukocyte immunoglobulin-like receptor subfamily B member 2 (LILRB2) is associated with immune evasion in breast cancer (BC). The aim of this study to elucidate the role of LILRB2 in BC progression. METHODS: LILRB2 expression in tumor tissues was detected by immunohistochemical staining. Human leukocyte antigen A (HLA-A) expression in BC cells was detected by Western blotting, and HLA-A ubiquitination was detected by immunoprecipitation and histidine pulldown assay. An in-situ tumor model was established in nude BALB/c mice to verify the role of LILRB2 in immune escape. Finally, the functions and potential mechanisms of LILRB2 in BC progression were explored using in silico data. RESULTS: LILRB2 was upregulated in BC tissues and cells, and correlated positively with poor prognosis. LILRB2 promoted BC progression by downregulating HLA-A expression. Mechanistically, LILRB2 facilitates the ubiquitination and subsequent degradation of HLA-A by promoting the interaction between the ubiquitin ligase membrane-associated ring finger protein 9 (MARCH9) and HLA-A. In syngeneic graft mouse models, LILRB2-expressing BC cells evaded CD8 + T cells and inhibited the secretion of cytokines by the cytotoxic CD8 + T cells. CONCLUSION: LILRB2 downregulates HLA-A to promote immune evasion in BC cells and is a promising new target for BC treatment.

A Novel Event-Triggered Bipartite Consensus for PDE-Based Multiagent Systems With Switching Topologies and Antagonistic Interactions.

Unlike the traditional studies on multiagent systems (MASs), this article investigates a class of MASs with spatial properties, whose agents are modeled by partial differential equations (PDE), in addition, to make the model more comprehensive, the Markovian switching topology with partially unknown probability is taken into account. The purpose of this article is to achieve the bipartite consensus for the above PDE-based MASs. In fact, the consideration of spatial factors in MASs will exacerbate the network transmission pressure, to overcome this problem, a novel spatiotemporal event-triggered mechanism is developed. Compared with the existing event-triggered mechanism, the proposed one is not only time-dependent but also covers the influence of spatial variables on the trigger conditions, which helps to further reduce the triggering frequency. Finally, three examples are given to verify the validity of the conclusion we proposed.

Neural Preassigned Performance Control for State-Constrained Nonlinear Systems Subject to Disturbances.

This article addresses the finite-time neural predefined performance control (PPC) issue for state-constrained nonlinear systems (NSs) with exogenous disturbances. By integrating the predefined-time performance function (PTPF) and the conventional barrier Lyapunov function (BLF), a new set of time-varying BLFs is designed to constrain the error variables. This establishes conditions for satisfying full-state constraints while ensuring that the tracking error meets the predefined performance indicators (PPIs) within a predefined time. Additionally, the incorporation of the nonlinear disturbance observer technique (NDOT) in the control design significantly enhances the ability of the system to reject disturbances and improves overall robustness. Leveraging recursive design based on dynamic surface control (DSC), a finite-time neural adaptive PPC strategy is devised to ensure that the closed-loop system is semi-globally practically finite-time stable (SPFS) and achieves the desired PPIs. Finally, the simulation results of two practical examples validate the efficacy and viability of the proposed approach.