Cadmium exposure induces skeletal muscle insulin resistance through the reactive oxygen species-mediated PINK1/Parkin pathway.

Epidemiological studies have suggested a positive association between environmental cadmium (Cd) exposure and type 2 diabetes mellitus (T2DM). Skeletal muscle insulin resistance (IR) plays a critical role in the pathogenesis of T2DM. This study aimed to investigate the effects of chronic low-level Cd exposure on skeletal muscle IR and its potential mechanism. Rats were exposed to drinking water containing 2 or 10 mg/L Cd for 24 weeks. Differentiated L6 myotubes were treated with Cd for 72 h. Immunofluorescence, flow cytometry assay, RNA-sequencing, and Seahorse analysis were conducted to determine the effects of Cd and its underlying mechanism on relevant parameters, including insulin sensitivity, glucose uptake, oxidative stress, mitophagy, and mitochondrial function in skeletal muscle and L6 myotubes. N-acetyl-cysteine (NAC), a scavenger of reactive oxygen species (ROS), and mitophagy inhibitor Cyclosporin A (CsA) were used to confirm the role of oxidative stress in mitophagy and mitochondrial dysfunction caused by Cd. We found that rats exposed to 10 mg/L Cd exhibited hyperglycemia and skeletal muscle IR. Cd markedly increased IRS-1 phosphorylation at Ser612, while decreased levels of phosphorylated PI3K, Akt, AS160, inhibited GLUT4 translocation and glucose uptake. Mechanistically, Cd increased the intracellular ROS, hydrogen peroxide, and malondialdehyde levels and decreased antioxidase activity in L6 myotubes. Furthermore, Cd upregulated the mRNA and protein levels of LC3II/I, PINK1, and Parkin. In addition, Cd induced the formation of mitophagosomes, reduced the mitochondrial membrane potential, decreased the adenosine triphosphate content, and impaired the mitochondrial respiratory capacity. Strikingly, NAC ameliorated oxidative stress, excessive mitophagy, and the associated reduction in myotube insulin sensitivity, while inhibition of mitophagy by CsA alleviated skeletal muscle IR. In conclusion, this study reveals a previously unrecognized mechanism that chronic low-level Cd exposure may induce mitophagy by activating the PINK1/Parkin signal pathway by increasing ROS, thus causing skeletal muscle IR and elevated blood glucose.

Prediction of Geometric Dimensions of Deposited Layer Produced Using Laser-Arc Hybrid Additive Manufacturing.

Laser-arc hybrid additive manufacturing (LAHAM) holds substantial potential in industrial applications, yet ensuring dimensional accuracy remains a major challenge. Accurate prediction and effective control of the geometrical dimensions of the deposited layers are crucial for achieving this accuracy. The width and height of the deposited layers, key indicators of geometric dimensions, directly affect the forming precision. This study conducted experiments and in-depth analysis to investigate the influence of various process parameters on these dimensions and proposed a predictive model for accurate forecasting. It was found that the width of the deposited layers was positively correlated with laser power and arc current and negatively correlated with scanning speed, while the height was negatively correlated with laser power and scanning speed and positively with arc current. Quantitative analysis using the Taguchi method revealed that the arc current had the most significant impact on the dimensions of the deposited layers, followed by scanning speed, with laser power having the least effect. A predictive model based on extreme gradient boosting (XGBoost) was developed and optimized using particle swarm optimization (PSO) for tuning the number of leaf nodes, learning rate, and regularization coefficients, resulting in the PSO-XGBoost model. Compared to models enhanced with PSO-optimized support vector regression (SVR) and XGBoost, the PSO-XGBoost model exhibited higher accuracy, the smallest relative error, and performed better in terms of Mean Relative Error (MRE), Mean Square Error (MSE), and Coefficient of Determination R2 metrics. The high predictive accuracy and minimal error variability of the PSO-XGBoost model demonstrate its effectiveness in capturing the complex nonlinear relationships between process parameters and layer dimensions. This study provides valuable insights for controlling the geometric dimensions of the deposited layers in LAHAM.

Prediction of Geometric Characteristics of Laser Cladding Layer Based on Least Squares Support Vector Regression and Crested Porcupine Optimization.

The morphology size of laser cladding is a crucial parameter that significantly impacts the quality and performance of the cladding layer. This study proposes a predictive model for the cladding morphology size based on the Least Squares Support Vector Regression (LSSVR) and the Crowned Porcupine Optimization (CPO) algorithm. Specifically, the proposed model takes three key parameters as inputs: laser power, scanning speed, and powder feeding rate, with the width and height of the cladding layer as outputs. To further enhance the predictive accuracy of the LSSVR model, a CPO-based optimization strategy is applied to adjust the penalty factor and kernel parameters. Consequently, the CPO-LSSVR model is established and evaluated against the LSSVR model and the Genetic Algorithm-optimized Backpropagation Neural Network (GA-BP) model in terms of relative error metrics. The experimental results demonstrate that the CPO-LSSVR model can achieve a significantly improved relative error of no more than 2.5%, indicating a substantial enhancement in predictive accuracy compared to other methods and showcasing its superior predictive performance. The high accuracy of the CPO-LSSVR model can effectively guide the selection of laser cladding process parameters and thereby enhance the quality and efficiency of the cladding process.

Correlation between Lactate Dehydrogenase to Albumin Ratio and the Prognosis of Patients with Cardiac Arrest.

Background: Cardiac arrest (CA) is a common event in the intensive care unit (ICU), which seriously threatens the prognosis of patients. Therefore, it is crucial to determine a simple and effective clinical indicator to judge the prognosis of patients after a CA for later treatments. The purpose of this study was to investigate the relationship between the lactate dehydrogenase to albumin ratio (LAR) and the prognosis of patients after a CA. Methods: The clinical data of participants was obtained from the Medical Information Mart for Intensive Care IV (MIMIC-IV, v2.0; 2008 to 2019). According to the 30-day prognosis, patients were divided into a survivors group (n = 216) and a non-survivors group (n = 304). The optimal LAR threshold was determined using restricted cubic spline (RCS), which divided patients into a high LAR group ( ≥ 15.50, n = 257) and a low LAR group ( < 15.50, n = 263). The ICU hospitalization and 30-day accumulative survival curves of the two groups were plotted following the Kaplan-Meier survival analysis. Multivariate Cox regression was used to analyze the relationship between the LAR and the prognosis of CA patients. Receiver operating characteristic (ROC) curves were drawn to evaluate the predictive efficacy of the LAR on 30-day all-cause mortality, and sensitivity analysis was used to check the reliability of the findings. Results: A total of 520 patients with CA were enrolled and the 30-day mortality was 58.46%. The LAR in the non-survivors group was higher than in the survivors group. The RCS showed a linear trend relationship between the LAR and the mortality risk in patients during their ICU stay and 30 days; moreover, as the LAR increased, so did the risk of mortality. The Kaplan-Meier survival curve showed that compared with the low LAR group, the cumulative survival rates of ICU hospitalization and 30 days were lower in the high LAR group among CA patients (p < 0.001). Multivariate Cox regression analysis showed that an elevated LAR ( ≥ 15.50) was an independent risk factor for mortality during ICU stay and 30 days (p < 0.005). ROC analysis suggested that the LAR was superior to the sequential organ failure assessment (SOFA) score in predicting the 30-day all-cause mortality in CA patients (area under the curve (AUC) = 0.676, 95% confidence interval [CI]: 0.629-0.723). To verify the reliability of our findings, we performed sensitivity analyses and found that the findings were reliable. Conclusions: An elevated LAR might be a predictor of mortality in patients following a CA during ICU hospitalization and 30 days, thereby it can be used to provide a reference for the clinical management of these patients.

A universal solvent-replacement strategy to convert alginate hydrogels into mechanically strong and transparent alginate eutectogels for sensitive strain sensors.

Eutectogels based on natural polymers have attracted significant attention as an alternative to easily dehydrated hydrogels and expensive ionogels in the development of flexible strain sensors. The feasibility of employing eutectogels derived from pure natural polymers could be greatly enhanced if their mechanical properties satisfy the requirements of applications. Herein, alginate eutectogels (AEs) with high mechanical properties (tensile strain 217 % and strength 2.26 MPa at fracture), and excellent transparency (over 90 %) are acquired via CaCl2 inducing ionic crosslinking and subsequent deep eutectic solvents (DESs, composed of glycerol and choline chloride) initiating physical crosslinking with a universal solvent- replacement strategy. Among them, sodium alginate, a natural polysaccharide polymer, is selected as representative supporting scaffolds and forms water-insoluble alginate hydrogels (AHs) in CaCl2 coagulation bath. The exchange of DESs with water of AHs not only restrengthens the polymer network by physical crosslinking, but also endows the obtained AEs with long-term solvent retention and high temperature resistance. In addition, the AEs not only have high reliability but also exhibit better linear sensitivity in a wide strain range (0-200 %). In particular, the AEs display multiple sensitivity to stretching, bending, and human motions, demonstrating feasibility as sensitive strain sensors.

Z-Increments Online Supervisory System Based on Machine Vision for Laser Solid Forming.

An improper Z-increment in laser solid forming can result in fluctuations in the off-focus amount during the manufacturing procedure, thereby exerting an influence on the precision and quality of the fabricated component. To solve this problem, this study proposes a closed-loop control system for a Z-increment based on machine vision monitoring. Real-time monitoring of the precise cladding height is accomplished by constructing a paraxial monitoring system, utilizing edge detection technology and an inverse perspective transformation model. This system enables the continuous assessment of the cladding height, which serves as a control signal for the regulation of the Z-increments in real-time. This ensures the maintenance of a constant off-focus amount throughout the manufacturing process. The experimental findings indicate that the proposed approach yields a maximum relative error of 1.664% in determining the cladding layer height, thereby enabling accurate detection of this parameter. Moreover, the real-time adjustment of the Z-increment quantities results in reduced standard deviations of individual cladding layer heights, and the height of the cladding layer increases. This proactive adjustment significantly enhances the stability of the manufacturing process and improves the utilization of powder material. This study can, therefore, provide effective guidance for process control and product optimization in laser solid forming.

Stretchable and transparent alginate ionic gel film for multifunctional sensors and devices.

Flexible and stretchable substrates based on pure natural polymers have attracted widespread attention for next-generation "green" electronics. However, fabrication of stretchable and "green" electronic sensors with integrated high stretchability, optical transmittance and good conductivity still remains tremendous challenges. Herein, alginate ionic gel films (AIGFs) with integrated high stretchability (tensile strength of 4.13 MPa and 191.1 % fracture strain) and excellent transparent properties (transparency of ∼92 %) are achieved by the glycerol inducing physical crosslinking and CaCl2 initiating ionic crosslinking, a simple soaking and drying strategy. The obtained gel films not only exhibit good ionic conductivity, but also high reliability, wide-range sensing, and multiple sensitivity to external stimulus. More importantly, these ionic conductive gel films as green substrates are successfully utilized for construction of flexible and patterned optoelectronic devices. This promising strategy will open up new powerful routes to construct highly stretchable, transparent, and ionic conductive substrates for multifunctional sensors and devices.

Stretchable and sensitive sodium alginate ionic hydrogel fibers for flexible strain sensors.

Ionic conductive hydrogel fibers based on natural polymers provide an immense focus for a new generation of electronics due to their flexibility and knittability. The feasibility of utilizing pure natural polymer-based hydrogel fibers could be drastically improved if their mechanical and transparent performances satisfy the requirements of actual practice. Herein, we report a facile fabrication strategy for significantly stretchable and sensitive sodium alginate ionic hydrogel fibers (SAIFs), by glycerol initiating physical crosslinking and by CaCl2 inducing ionic crosslinking. The obtained ionic hydrogel fibers not only show significant stretchability (tensile strength of 1.55 MPa and fracture strain of ∼161 %), but also exhibit wide-range sensing, satisfactorily stable, rapidly responsive, and multiply sensitive abilities to external stimulus. In addition, the ionic hydrogel fibers have excellent transparency (over 90 % in a wide wavelength range), and good anti-evaporation and anti-freezing properties. Furthermore, the SAIFs have been easily knitted into a textile, and successfully applied as wearable sensors to recognize human motions, by observing the output electrical signals. Our methodology for fabrication intelligent SAIFs will shed light on artificial flexible electronics and other textile-based strain sensors.

Preparation of oral nanoparticles of Perillae Fructus oil and prevention application of cold stress in mice.

Perillae Fructus oil has an important function in relieving cold stress. However, its application in this aspect has still been restricted because of instability and low bioavailability. In this study, Perillae Fructus oil was extracted through Soxhlet extraction, analyzed through gas chromatography-mass spectrometry (GC-MS), and nanopackaged into a yeast shell for the preparation of nanoparticles for oral administration. The characteristics of the nanoparticles were investigated using a Malvern zeta-size nanoinstrument, scanning electron microscopy (SEM), and high-performance liquid chromatography (HPLC). Then, the roles of orally administered nanoparticles in relieving cold stress were evaluated by investigating blood physiological and biochemical indexes in mice. The results showed that the oil yield from Perillae Fructus and shell yield from yeast cells were ~48.37% and ~16.87%, respectively. Approximately 89.21% of the added oil was packaged into the yeast shell to form nanoparticles with an average diameter of 316.74 nm and a surface charge of +2.9 mV. The nanoparticles were stable in simulated gastric acid and could be effectively released in simulated intestinal fluid with an efficiency of ~91.34%. After oral administration of nanoparticles, the mouse blood indexes of white blood cells (WBCs), superoxide dismutase (SOD) activity, and malonaldehyde (MDA) content were recovered compared to those in model mice, with a more remarkable effect than oral administration of free Perillae Fructus oil. Overall, the stability and bioavailability were improved by packaging Perillae Fructus oil into a yeast shell. These nanoparticles are a new agent for the prevention of cold stress.

Trophoblast-specific knockdown of CSPG4 expression causes pregnancy complications with poor placentation in mice.

The multifunctional molecule chondroitin sulfate proteoglycan 4 (CSPG4/NG2) plays key roles in organogenesis and tumorigenesis. However, its roles in placentation remain unclear. In this study, CSPG4 expression in human and mouse placentas was investigated through immunohistochemistry (IHC), qPCR and western blotting. The theoretical structure and function of CSPG4 were assessed using bioinformatic tools, and the functions of CSPG4 in fetal and placental development were investigated using a mouse model established by trophoblast-specific CSPG4 knockdown and a trophoblast cell line with CSPG4 knockout by lentivirus infection. The results showed that CSPG4 was mainly located in trophoblasts in both human placentas and mouse placentas, with a higher level in preeclampsia (PE) placentas than in healthy control placentas. Furthermore, there was a trend of increasing expression in mouse placentas during pregnancy. The 3D structure of CSPG4 was visualized using an M model composed of two chains, and the structure implied that CSPG4 was a multifunctional molecule containing multiple pockets with multiligand binding sites and enzyme active sites. Trophoblast-specific CSPG4 knockdown caused frequent fetal loss, and viable fetal development was restricted by poor placentation, with mice placentas having reduced weight and width. The proliferation and invasion of CSPG4-knockout trophoblasts were significantly inhibited, and as such, the molecular signaling of AKT and ERK phosphorylation was inhibited, and the expression of MMP2 and MMP9 was reduced. In summary, CSPG4 deficiency inhibited trophoblast proliferation and invasion, which was associated with AKT, ERK and MMP signaling. CSPG4 deficiency also caused pregnancy complications with poor placentation in mice.