Relationship between the longitudinal trajectory of the triglyceride-glucose index and the development of CKD: an 8-year retrospective longitudinal cohort study.

Background: The triglyceride-glucose (TyG) index, a simple surrogate marker of insulin resistance, is significantly associated with chronic kidney disease (CKD). However, there is limited research on the longitudinal trajectory of TyG index over time and its relationship with CKD. Objective: To analyse the characteristics of the longitudinal trajectory of the TyG index over time and its association with the development of CKD in a health check-up population. Methods: Participants who underwent at least three annual health check-ups at the Health Management Center of Sichuan Provincial People's Hospital from 2015 to 2022 were included in this retrospective cohort study. The TyG index was calculated as ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. The latent class mixed model (LCMM) was used to identify the TyG index trajectory of the study population. A Cox proportional hazard model was used to estimate the CKD incidence risk in different quartile groups and the association of changes in the TyG index trajectory with the development of CKD. Results: A total of 4,921 participants were included in this study, and they were divided into four groups according to the quartiles of the baseline TyG index: Q1 (5.43-6.66), Q2 (6.67-7.04), Q3 (7.05-7.43), and Q4 (7.43-9.97). There was no difference in the risk of CKD occurrence among the TyG groups. Three different TyG index trajectories were identified in this study: a high-level group, middle-level stable group and low-level stable group, respectively. The incidence rate of CKD in the high-level TyG index trajectory group was 2.399 times greater than that in the low-level stable trajectory group (HR=2.399, 95% CI 1.167-4.935). Conclusion: Individuals with long-term exposure to high TyG index levels had a significantly greater risk of CKD. Routine monitoring of the TyG index and its longitudinal trend will aid in the risk stratification of CKD in the general population and will be helpful for CKD prevention and targeted management.

Corrigendum: Relationship between the longitudinal trajectory of the triglyceride-glucose index and the development of CKD: an 8-year retrospective longitudinal cohort study.

[This corrects the article DOI: 10.3389/fendo.2024.1376166.].

Model predictive manipulation of compliant objects with multi-objective optimizer and adversarial network for occlusion compensation.

BACKGROUND: The manipulation of compliant objects by robotic systems remains a challenging task, largely due to their variable shapes and the complex, high-dimensional nature of their interaction dynamics. Traditional robotic manipulation strategies struggle with the accurate modeling and control necessary to handle such materials, especially in the presence of visual occlusions that frequently occur in dynamic environments. Meanwhile, for most unstructured environments, robots are required to have autonomous interactions with their surroundings. METHODS: To solve the shape manipulation of compliant objects in an unstructured environment, we begin by exploring the regression-based algorithm of representing the high-dimensional configuration space of deformable objects in a compressed form that enables efficient and effective manipulation. Simultaneously, we address the issue of visual occlusions by proposing the integration of an adversarial network, enabling guiding the shaping task even with partial observations of the object. Afterwards, we propose a receding-time estimator to coordinate the robot action with the computed shape features while satisfying various performance criteria. Finally, model predictive controller is utilized to compute the robot's shaping motions subject to safety constraints. Detailed experiments are presented to evaluate the proposed manipulation framework. SIGNIFICANT FINDINGS: Our MPC framework utilizes the compressed representation and occlusion-compensated information to predict the object's behavior, while the multi-objective optimizer ensures that the resulting control actions meet multiple performance criteria. Through rigorous experimental validation, our approach demonstrates superior manipulation capabilities in scenarios with visual obstructions, outperforming existing methods in terms of precision and operational reliability. The findings highlight the potential of our integrated approach to significantly enhance the manipulation of compliant objects in real-world robotic applications.

Pattern-Matched Polymer Ligpands Toward Near-Perfect Synergistic Passivation for High-Performance and Stable Br/Cl Mixed Perovskite Light-Emitting Diodes.

Mixed Br/Cl perovskite nanocrystals (PeNCs) exhibit bright pure-blue emission benefiting for fulfilling the Rec. 2100 standard. However, phase segregation remains a significant challenge that severely affects the stability and emission spectrum of perovskite light-emitting diodes (PeLEDs). Here, we demonstrate the optimization of the spacing between polydentate functional groups of polymer ligands to match the surface pattern of CsPbBr1.8Cl1.2 PeNCs, resulting in effective synergistic passivation effect and significant improvements in PeLED performances. The block and alternating copolymers with different inter-functional group spacing are facilely synthesized as ligands for PeNCs. Surprisingly, block copolymers with a higher functional group density do not match PeNCs, while alternating copolymers enable efficient PeNCs with the high photoluminescence intensity, low non-radiative recombination rate and high exciton binding energy. Density functional theory calculations clearly confirm the almost perfect match between alternating copolymers and PeNCs. Finally, pure-blue PeLEDs are achieved with the emission at 467 nm and Commission Internationale de l'Eclairage (CIE) coordinates of (0.131, 0.071), high external quantum efficiency (9.1%) and record spectral and operational stabilities (~ 80 mins) in mixed-halide PeLEDs. Overall, this study contributes to designing the polymer ligands and promoting the development of high-performance and stable pure-color PeLEDs towards display applications.

Development strategies and application of antimicrobial peptides as future alternatives to in-feed antibiotics.

The use of in-feed antibiotics has been widely restricted due to the significant environmental pollution and food safety concerns they have caused. Antimicrobial peptides (AMPs) have attracted widespread attention as potential future alternatives to in-feed antibiotics owing to their demonstrated antimicrobial activity and environment friendly characteristics. However, the challenges of weak bioactivity, immature stability, and low production yields of natural AMPs impede practical application in the feed industry. To address these problems, efforts have been made to develop strategies for approaching the AMPs with enhanced properties. Herein, we summarize approaches to improving the properties of AMPs as potential alternatives to in-feed antibiotics, mainly including optimization of structural parameters, sequence modification, selection of microbial hosts, fusion expression, and industrially fermentation control. Additionally, the potential for application of AMPs in animal husbandry is discussed. This comprehensive review lays a strong theoretical foundation for the development of in-feed AMPs to achieve the public health globally.

High-flow nasal cannula therapy versus conventional oxygen therapy for adult patients after cardiac surgery: A systemic review and meta-analysis.

BACKGROUND: Oxygen therapy constitutes a crucial element of post-cardiac operative care. The study assessed the effectiveness of high-flow nasal cannula (HFNC) in comparison to conventional oxygen therapy (COT). OBJECTIVES: The aim of the study was to assess the effectiveness of HFNC in comparison to COT for adult patients following cardiac surgery. METHODS: We conducted a comprehensive search of Embase, PubMed, Scopus, Cochrane Library, and Web of Science databases from inception until April 18, 2023, to identify randomized controlled trials (RCTs) and crossover studies that compared the efficacy of HFNC with COT in adult patients following cardiac surgery. RESULTS: The meta-analysis included nine studies, consisting of eight RCTs and one crossover study. Compared with COT, HFNC could reduce the need for escalation of respiratory support (RR 0.67, 95% CI: 0.48 to 0.93, P = 0.02), decrease arterial partial pressure of carbon dioxide (PaCO2) levels (MD -3.14, 95% CI: -4.90 to -1.39, P<0.001), and increase forced expiratory volume in 1 second (FEV1) levels (MD 0.08, 95% CI: 0.02 to 0.15, P = 0.02). There was no significant difference between the HFNC and COT groups in terms of mortality, intubation rate, respiratory rate, heart rate, intensive care unit and hospital length of stay, arterial partial pressure of oxygen (PaO2), forced vital capacity, and complications of atrial fibrillation and delirium. CONCLUSION: Compared with COT, HFNC could decrease the need for escalation of respiratory support, lower PaCO2 levels, and elevate FEV1 levels in patients following cardiac surgery.

Free spectral range measurement based on a multi-longitudinal mode laser self-mixing ellipse fitting degree detection technique.

A method by detecting the ellipse fitting degree of the trajectory equation formed by two self-mixing (SM) signals in the multi-longitudinal mode laser SM system with a Wollaston prism is presented to test the free spectral range (FSR) of the laser. By utilizing the orthogonal vector and phase-shift characteristics between adjacent longitudinal modes, the fluctuations in multi-mode SM effects caused by changes in the external cavity length are transformed into alterations in the trajectory composed of two orthogonal SM signals. The FSR is calculated by detecting the difference in external cavity lengths between the two positions, where the trajectory of the two SM signals best fits an ellipse. To achieve an automatic FSR measurement, the ellipse fitting degree is proposed as the criterion for positioning the external cavity mode. Experimental results indicate that the FSR of the laser diode is measured to be 85.23 GHz with a resolution of 0.48 GHz, while the corresponding external cavity resolution is 10 µm, and the resolution of the ellipse fitting degree is less than 1. The compact and straightforward design, coupled with high sensitivity, automated measurements, and immunity to optical feedback, holds significant promise as a robust tool for measuring FSR and assessing laser performance.

Dual-Channel in Spatial-Frequency Domain CycleGAN for perceptual enhancement of transcranial cortical vascular structure and function.

Observing cortical vascular structures and functions using laser speckle contrast imaging (LSCI) at high resolution plays a crucial role in understanding cerebral pathologies. Usually, open-skull window techniques have been applied to reduce scattering of skull and enhance image quality. However, craniotomy surgeries inevitably induce inflammation, which may obstruct observations in certain scenarios. In contrast, image enhancement algorithms provide popular tools for improving the signal-to-noise ratio (SNR) of LSCI. The current methods were less than satisfactory through intact skulls because the transcranial cortical images were of poor quality. Moreover, existing algorithms do not guarantee the accuracy of dynamic blood flow mappings. In this study, we develop an unsupervised deep learning method, named Dual-Channel in Spatial-Frequency Domain CycleGAN (SF-CycleGAN), to enhance the perceptual quality of cortical blood flow imaging by LSCI. SF-CycleGAN enabled convenient, non-invasive, and effective cortical vascular structure observation and accurate dynamic blood flow mappings without craniotomy surgeries to visualize biodynamics in an undisturbed biological environment. Our experimental results showed that SF-CycleGAN achieved a SNR at least 4.13 dB higher than that of other unsupervised methods, imaged the complete vascular morphology, and enabled the functional observation of small cortical vessels. Additionally, the proposed method showed remarkable robustness and could be generalized to various imaging configurations and image modalities, including fluorescence images, without retraining.

Resilient exponential tracking for disturbed systems with communication links faults.

Resilience is to appraise the ability of disturbed systems to recover cooperative performance after suffering from failures or disturbances. In this paper, the improvement on the exponential tracking resilience for disturbed Euler-Lagrange systems is explored by settling the unknown time-variant faults imposed on the communication interaction between agents. First, we transform the resilient exponential tracking problem into designing the trajectory and velocity observers for leaders, and showcase that the proposed observers are resilient to communication interaction malfunctions. Second, a disturbance observer is manifested to estimate disturbances precisely, which is needless to know the upper bound of disturbance. The reliable observers and estimator are incorporated into the resilient tracking control frame. Further, the global exponential stabilization of the tracking systems is performed by utilizing the Lyapunov theory. Moreover, benefiting from feasible and reliable observation and estimation results, the proposed control framework enables to realize a satisfactory resilient exponential tracking performance even in the case of communication links faults (CLFs) and disturbances. Comprehensive studies are executed on a group of satellite systems, and the simulations results verify the effectiveness of the proposed resilient approaches in a time-variant tracking case.

Cyclocarya paliurus leaves alleviate high-sucrose diet-induced obesity by improving intestinal metabolic disorders.

High-sucrose diets are common in daily life but harmful to human health. Cyclocarya paliurus leaves (CPL) are a kind of tea used to alleviate metabolic diseases and are widely used in China. However, the effects of CPL on high-sucrose-induced obesity are unknown. This study aimed to describe the changes in gut metabolism induced by a high-sucrose diet and to reveal the potential mechanisms through which CPL alleviate high-sucrose diet-induced obesity. A high-sucrose-induced obesity model was generated in C57BL/6J and KM mice. The effects of CPL on obese mice were evaluated, and changes in the gut microbiota and intestinal metabolites induced by CPL treatment were observed. Furthermore, the fecal microbiota transplantation (FMT) method was used to prove that the effects of CPL on high-sucrose induced obesity depend on the changes of gut microbiota. The results of the C57BL/6J mouse experiment revealed that high-sucrose intake induced fat deposition and altered the gut microbiota. CPL treatment decreased fat deposition and alleviated disorders of the gut microbiota. Furthermore, CPL treatment increased the utilization of amnio acids, long fatty acids and saccharides and produced more bile acids, indole derivatives and less trimethylamine (TMA). A confirmatory experiment in KM mice also revealed that CPL can alleviate obesity, ameliorate intestinal metabolic disorders, and upregulate the expression of tight junction proteins in the intestinal mucosa. These results demonstrated that CPL could prevent high sucrose-induced obesity and generate more beneficial intestinal microbial metabolites but less harmful intestinal microbial metabolites.

A unique circulating microRNA pairs signature serves as a superior tool for early diagnosis of pan-cancer.

Cancer remains a major burden globally and the critical role of early diagnosis is self-evident. Although various miRNA-based signatures have been developed in past decades, clinical utilization is limited due to a lack of precise cutoff value. Here, we innovatively developed a signature based on pairwise expression of miRNAs (miRPs) for pan-cancer diagnosis using machine learning approach. We analyzed miRNA spectrum of 15832 patients, who were divided into training, validation, test, and external test sets, with 13 different cancers from 10 cohorts. Five different machine-learning (ML) algorithms (XGBoost, SVM, RandomForest, LASSO, and Logistic) were adopted for signature construction. The best ML algorithm and the optimal number of miRPs included were identified using area under the curve (AUC) and youden index in validation set. The AUC of the best model was compared to previously published 25 signatures. Overall, Random Forest approach including 31 miRPs (31-miRP) was developed, proving highly efficient in cancer diagnosis across different datasets and cancer types (AUC range: 0.980-1.000). Regarding diagnosis of cancers at early stage, 31-miRP also exhibited high capacities, with AUC ranging from 0.961 to 0.998. Moreover, 31-miRP exhibited advantages in differentiating cancers from normal tissues (AUC range: 0.976-0.998) as well as differentiating cancers from corresponding benign lesions. Encouragingly, comparing to previously published 25 different signatures, 31-miRP also demonstrated clear advantages. In conclusion, 31-miRP acts as a powerful model for cancer diagnosis, characterized by high specificity and sensitivity as well as a clear cutoff value, thereby holding potential as a reliable tool for cancer diagnosis at early stage.

Serum amyloid beta 42 levels correlated with metabolic syndrome and its components.

Introduction: Beta-amyloid accumulation in the brain appears to be a key initiating event in Alzheimer's disease (AD), and factors associated with increased deposition of beta-amyloid are of great interest. Enhanced deposition of amyloid-ß peptides is due to an imbalance between their production and elimination. Previous studies show that diminished levels of CSF amyloid beta 42 (Aß42) is a biomarker in AD; however, the role of serum Aß42 in AD is contradictory. BMI and obesity have been reported to be related to increased serum Aß42 levels. Therefore, we aimed to investigate the relation between metabolic syndrome (MetS), its clinical measures (abdominal obesity, high glucose, high triglyceride, low high-density lipoprotein cholesterol level, and hypertension), and serum Aß42 levels. Methods: A total of 1261 subjects, aged 18-89 years in Chengdu, China, were enrolled from January 2020 to January 2021 to explore the correlation of serum Aß42 levels with body mass index (BMI), blood lipids, and blood pressure. Furthermore, as the risk of MetS is closely related to age, 1,212 participants (N = 49 with age ≥ 80 years old were excluded) were analyzed for the correlation of serum Aß42 level and MetS clinical measures. Results: The results showed that log-transformed serum Aß42 level was positively correlated with BMI (R = 0.29; p < 0.001), log-transformed triglyceride (R = 0.14; p < 0.001), and diastolic blood pressure (DBP) (R = 0.12; p < 0.001) and negatively correlated with high-density lipoprotein (HDL-c) (R = -0.18; p < 0.001). After adjusting for age, sex, and other covariates, elevated serum Aß42 level was correlated with higher values of BMI (ßmodel1 = 2.694, ßmodel2 = 2.703) and DBP (ßmodel1 = 0.541, ßmodel2 = 0.546) but a lower level of HDL-c (ßmodel2 = -1.741). Furthermore, serum Aß42 level was positively correlated with MetS and its clinical measures, including BMI and DBP, and negatively correlated with HDL-c level in the Han Chinese population. However, the level of serum Aß42 did not show a significant correlation with high glucose or high triglyceride. Discussion: These observations indicate that MetS and its components are associated with higher levels of serum Aß42 and hence limit the potential of serum Aß42 as a suitable diagnostic biomarker for AD. As such, we recommend serum Aß42 serve as a direct risk biomarker for MetS rather than for AD.

Pan-cancer characterization of cell-free immune-related miRNA identified as a robust biomarker for cancer diagnosis.

Minimally invasive testing is essential for early cancer detection, impacting patient survival rates significantly. Our study aimed to establish a pioneering cell-free immune-related miRNAs (cf-IRmiRNAs) signature for early cancer detection. We analyzed circulating miRNA profiles from 15,832 participants, including individuals with 13 types of cancer and control. The data was randomly divided into training, validation, and test sets (7:2:1), with an additional external test set of 684 participants. In the discovery phase, we identified 100 differentially expressed cf-IRmiRNAs between the malignant and non-malignant, retaining 39 using the least absolute shrinkage and selection operator (LASSO) method. Five machine learning algorithms were adopted to construct cf-IRmiRNAs signature, and the diagnostic classifies based on XGBoost algorithm showed the excellent performance for cancer detection in the validation set (AUC: 0.984, CI: 0.980-0.989), determined through 5-fold cross-validation and grid search. Further evaluation in the test and external test sets confirmed the reliability and efficacy of the classifier (AUC: 0.980 to 1.000). The classifier successfully detected early-stage cancers, particularly lung, prostate, and gastric cancers. It also distinguished between benign and malignant tumors. This study represents the largest and most comprehensive pan-cancer analysis on cf-IRmiRNAs, offering a promising non-invasive diagnostic biomarker for early cancer detection and potential impact on clinical practice.

Transcranial photobiomodulation for brain diseases: review of animal and human studies including mechanisms and emerging trends.

The brain diseases account for 30% of all known diseases. Pharmacological treatment is hampered by the blood-brain barrier, limiting drug delivery to the central nervous system (CNS). Transcranial photobiomodulation (tPBM) is a promising technology for treating brain diseases, due to its effectiveness, non-invasiveness, and affordability. tPBM has been widely used in pre-clinical experiments and clinical trials for treating brain diseases, such as stroke and Alzheimer's disease. This review provides a comprehensive overview of tPBM. We summarize emerging trends and new discoveries in tPBM based on over one hundred references published in the past 20 years. We discuss the advantages and disadvantages of tPBM and highlight successful experimental and clinical protocols for treating various brain diseases. A better understanding of tPBM mechanisms, the development of guidelines for clinical practice, and the study of dose-dependent and personal effects hold great promise for progress in treating brain diseases.

Fragmented QRS complex could predict all-cause mortality in patients with connective tissue disease-associated pulmonary arterial hypertension.

OBJECTIVES: To investigate the prognostic impact and pathophysiological characteristics of fragmented QRS complex (fQRS) on patients with connective tissue disease-associated pulmonary arterial hypertension (CTD-PAH). METHODS: This was a multicentre retrospective study recruiting 141 patients with CTD-PAH diagnosed by right heart catheterization (114 cases in the discovery cohort and 27 cases in the validation cohort). fQRS and ST-T change were detected on conventional 12-lead electrocardiogram (ECG). Patients were followed up every 3 months to update their status and the primary end point was all-cause death. Clinical information and ECG characteristics were compared between survival and death groups and Kaplan-Meier curve was used for survival analysis. RESULTS: There were significant differences in age, gender, 6-min walk distance, NT-proBNP, WHO class, presence of fQRS and presence of ST-T change in inferior leads between survival group and death group. Inferior fQRS and ST-T change were significantly associated with right ventricular (RV) dilatation and reduced RV ejection fraction (RVEF). Kaplan-Meier curve showed that all-cause mortality was higher in CTD-PAH with fQRS (p= 0.003) and inferior ST-T change (p= 0.012). Low- and intermediate-risk CTD-PAH with inferior ST-T change had higher all-cause mortality (p= 0.005). The prognostic value of fQRS and inferior ST-T change was validated in external validation cohort. CONCLUSION: The presence of inferior fQRS and ST-T change could predict poor prognosis in CTD-PAH. CLINICAL TRIAL REGISTRATION NUMBER: NCT05980728, https://clinicaltrials.gov.

Risk and Incidence of Cardiovascular Disease Associated with Polycystic Ovary Syndrome.

AIMS: We aimed to evaluate the risk of cardiovascular disease (CVD) in women with polycystic ovary syndrome (PCOS) and estimate the global incidence of PCOS-associated CVD. METHODS: We conducted a meta-analysis across five databases to evaluate the risk of CVD among women with PCOS. Global incidence of PCOS-associated CVD was calculated by a population attributable fraction (PAF) modelling using the pooled RR, PCOS prevalence, CVD incidence number and age-standardized rate (ASIR), from the Global Burden of Diseases 2019. An estimated annual percentage change (EAPC) was used to assess the temporal trend of PCOS-associated CVD. RESULTS: The risk of CVD was significantly increased in the women with PCOS for all-age group (pooled RR 1.51, 95% CI 1.36-1.69), and 10- to 54-year-old (1.37, 1.17-1.59). Globally, from 1990 to 2019, the PCOS associated CVD cases in women across all-age group has rised from 102 530 to 235 560. The most affected regions were East Asia & Pacific (108 430, 66 090-166 150) in 2019. The South Asia has the highest increase trend of PCOS-associated CVD ASIRs (EAPC 2.61%, 2.49-2.73). The annual increase ASIR in PCOS-CVD incidence for the 10-54 age group (EAPC 0.49%; 0.41-0.56) is faster than that of the all-age group (0.34; 0.27-0.42). The middle- or low-middle sociodemographic index countries, experienced higher increase trend of CVD due to PCOS in the past thirty years. CONCLUSIONS: Women with PCOS have a significantly increased risk of CVD. Efficient measures to enhance its prevention and treatment are important for regions with high PCOS-associated CVD burden, especially premature CVD in women under 55 years.

Studies have reported cardiovascular disease (CVD) is the leading cause of mortality for women. Meanwhile, women with polycystic ovary syndrome (PCOS) substantially elevate the risk of CVD. However, no studies have quantified the impact of PCOS on the overall CVD burden. This study performed a meta-analysis to assess the risk of CVD in all-age group and 10 to 54 years old women, living with PCOS with 17 articles, and estimated the burdens of PCOS-associated CVD burden, by global, 7 World-bank defined regions, and 204 countries, from 1990 to 2019, using a PAF modelling. Our study implicated women in all-age group, and 10 to 54 years old with PCOS face a 1.51-fold, and 1.37-fold increased risk of CVD compared those without, respectively. Globally, approximately 0.85% of CVD new cases in 2019 were associated with PCOS, corresponded a more than 2-fold increase of PCOS-associated CVD cases from 1990. However, the burden of PCOS-associated CVD varies widely by region; for instance, nearly 1.49% of CVD new cases were attributed to PCOS in North America. Meanwhile, the East Asia & Pacific region had the highest PCOS-associated new CVD case, and the South Asia experienced the highest increase in age-standardised incidence rates of CVD due to PCOS. Notably, we found higher worldwide PAFs, and annual increase ASIR than that in all-age group women. This result suggests that premature CVD in women with PCOS under 55 years deserve more attention.

Multiple cytokine analysis based on QuantiFERON-TB gold plus in different tuberculosis infection status: an exploratory study.

BACKGROUND: More efficient and convenient diagnostic method is a desperate need to reduce the burden of tuberculosis (TB). This study explores the multiple cytokines secretion based on QuantiFERON-TB Gold Plus (QFT-Plus), and screens for optimal cytokines with diagnostic potential to differentiate TB infection status. METHODS: Twenty active tuberculosis (ATB) patients, fifteen patients with latent TB infection (LTBI), ten patients with previous TB and ten healthy controls (HC) were enrolled. Whole blood samples were collected and stimulated by QFT-Plus TB1 and TB2 antigens. The levels of IFN-γ, TNF-α, IL-2, IL-6, IL-5, IL-10, IP-10, IL-1Ra, CXCL-1 and MCP-1 in supernatant were measured by Luminex bead-based multiplex assays. The receiver operating characteristic curve was used to evaluate the diagnostic accuracy of cytokine for distinguishing different TB infection status. RESULTS: After stimulation with QFT-Plus TB1 and TB2 antigens, the levels of all cytokines, except IL-5 in TB2 tube, in ATB group were significantly higher than that in HC group. The levels of IL-1Ra concurrently showed the equally highest AUC for distinguishing TB infection from HC, followed by the levels of IP-10 in both TB1 tube and TB2 tube. Moreover, IP-10 levels displayed the largest AUC for distinguishing ATB patients from non-ATB patients. Meanwhile, the levels of IP-10 also demonstrated the largest AUC in both TB1 tube and TB2 tube for distinguishing ATB patients from LTBI. CONCLUSIONS: In addition to conventional detection of IFN-γ, measuring IP-10 and IL-1Ra based on QFT-Plus may have the more tremendous potential to discriminate different TB infection status.

Saturation-Tolerant Prescribed Control for Nonlinear Systems With Unknown Control Directions and External Disturbances.

In this article, saturation-tolerant prescribed control (SPC) is investigated for a class of multiinput-multioutput (MIMO) nonlinear systems. The key challenge lies in how to guarantee both input and performance constraints simultaneously for nonlinear systems especially under external disturbance and unknown control directions. We propose concise finite-time tunnel prescribed performance (FTPP) for better tracking performance, which features tight allowable set and user-specified settling time. To comprehensively tackle the conflict between the above two constraints, an auxiliary system is designed to explore their interconnections instead of neglecting their contradictions. By introducing its generated signals into FTPP, the obtained saturation-tolerant prescribed performance (SPP) has the ability to degrade or recover the performance boundaries in the light of different saturation conditions. Consequently, the developed SPC, together with nonlinear disturbance observer (NDO), can effectively improve the robustness and reduce the conservatism against external disturbances, input, and performance constraints. Finally, comparative simulations are presented to showcase these theoretical findings.

miR-1304 targets KLK11 to regulate gastric cancer cell proliferation through the mTOR signaling pathway.

OBJECTIVE: Gastric cancer (GC) is prevalent worldwide but has a dismal prognosis, and its molecular and pathogenic pathways remain unknown. Kallikrein 11 (KLK11) has a reduced expression in GC and may be a promising biomarker. METHOD: Herein, the function of KLK11 in GC and its regulatory mechanism was studied. Gene sequencing and quantitative reverse transcription-polymerase chain reaction were used to determine the expression of KLK11 in GC and precancerous lesions. Cell function tests and flow cytometry were conducted to determine the proliferative capacity and cell cycle of GC cells, respectively. A luciferase reporter test confirmed the interaction between RNA molecules. The mTOR/4E-BP1 signaling pathway was analyzed using western blotting. RESULT: KLK11 has a suppressed expression in GC samples. KLK11 decreased the proliferative capacity of GC cells, by inhibiting the degree of mTOR/4E-BP1 phosphorylation. In contrast, miR-1304 increased GC cell proliferation by inhibiting KLK11. Moreover, KLK11 was able to limit in vivo GC cell proliferation. CONCLUSION: These findings reveal a promising strategy to prevent and treat GC by targeting the KLK11-mediated mTOR/4E-BP1 cascade.

Adaptive Safe Reinforcement Learning With Full-State Constraints and Constrained Adaptation for Autonomous Vehicles.

High-performance learning-based control for the typical safety-critical autonomous vehicles invariably requires that the full-state variables are constrained within the safety region even during the learning process. To solve this technically critical and challenging problem, this work proposes an adaptive safe reinforcement learning (RL) algorithm that invokes innovative safety-related RL methods with the consideration of constraining the full-state variables within the safety region with adaptation. These are developed toward assuring the attainment of the specified requirements on the full-state variables with two notable aspects. First, thus, an appropriately optimized backstepping technique and the asymmetric barrier Lyapunov function (BLF) methodology are used to establish the safe learning framework to ensure system full-state constraints requirements. More specifically, each subsystem's control and partial derivative of the value function are decomposed with asymmetric BLF-related items and an independent learning part. Then, the independent learning part is updated to solve the Hamilton-Jacobi-Bellman equation through an adaptive learning implementation to attain the desired performance in system control. Second, with further Lyapunov-based analysis, it is demonstrated that safety performance is effectively doubly assured via a methodology of a constrained adaptation algorithm during optimization (which incorporates the projection operator and can deal with the conflict between safety and optimization). Therefore, this algorithm optimizes system control and ensures that the full set of state variables involved is always constrained within the safety region during the whole learning process. Comparison simulations and ablation studies are carried out on motion control problems for autonomous vehicles, which have verified superior performance with smaller variance and better convergence performance under uncertain circumstances. The effectiveness of the safe performance of overall system control with the proposed method accordingly has been verified.