Enzyme-free and rapid colorimetric analysis of osteopontin via triple-helix aptamer probe coupled with catalytic hairpin assembly reaction.

BACKGROUND: Osteopontin (OPN) is closely associated with tumorigenesis, growth, invasion, and immune escape and it serves as a plasma biomarker for hepatocellular carcinoma (HCC). Nevertheless, the accurate and rapid detection of low-abundance OPN still poses significant challenges. Currently, the majority of protein detection methods rely heavily on large precision instruments or involve complex procedures. Therefore, developing a simple, enzyme-free, rapid colorimetric analysis method with high sensitivity is imperative. RESULTS: In this study, we have developed a portable colorimetric biosensor by integrating the triple-helix aptamer probe (THAP) and catalytic hairpin assembly (CHA) strategy, named as T-CHA. After binding to the OPN, the trigger probe can be released from THAP, then initiates the CHA reaction and outputs the signal through the formation of a G-quadruplex/Hemin DNAzyme with horseradish peroxidase-like activity. Consequently, this colorimetric sensor achieves visual free-labeled detection without additional fluorophore modification and allows for accurate quantification by measuring the optical density of the solution at 650 nm. Under optimal conditions, the logarithmic values of various OPN concentrations exhibit satisfactory linearity in the range of 5 pg mL-1 to 5 ng mL-1, with a detection limit of 2.04 pg mL-1. Compared with the widely used ELISA strategy, the proposed T-CHA strategy is rapid (∼105 min), highly sensitive, and cost-effective. SIGNIFICANCE: The T-CHA strategy, leveraging the low background leakage of THAP and the high catalytic efficiency of CHA, has been successfully applied to the detection of OPN in plasma, demonstrating significant promise for the early diagnosis of HCC in point-of-care testing. Given the programmability of DNA and the universality of T-CHA, it can be readily modified for analyzing other useful tumor biomarkers.

A new artificial intelligence system for both stomach and small bowel capsule endoscopy.

BACKGROUND AND AIMS: Despite the benefits of artificial intelligence (AI) in small bowel (SB) capsule endoscopy (CE) image reading, information on its application in the stomach and SB CE is lacking. METHODS: In this multicenter, retrospective diagnostic study, gastric imaging data were added to the deep learning (DL)-based SmartScan (SS), which has been described previously. A total of 1,069 magnetically controlled gastrointestinal (GI) CE examinations (comprising 2,672,542 gastric images) were used in the training phase for recognizing gastric pathologies, producing a new AI algorithm named SS Plus. 342 fully automated, magnetically controlled CE (FAMCE) examinations were included in the validation phase. The performance of both senior and junior endoscopists with both the SS Plus-Assisted Reading (SSP-AR) and conventional reading (CR) modes was assessed. RESULTS: SS Plus was designed to recognize 5 types of gastric lesions and 17 types of SB lesions. SS Plus reduced the number of CE images required for review to 873.90 (1000) (median, IQR 814.50-1,000) versus 44,322.73 (42,393) (median, IQR 31,722.75-54,971.25) for CR. Furthermore, with SSP-AR, endoscopists took 9.54 min (8.51) (median, IQR 6.05-13.13) to complete the CE video reading. In the 342 CE videos, SS Plus identified 411 gastric and 422 SB lesions, whereas 400 gastric and 368 intestinal lesions were detected with CR. Moreover, junior endoscopists remarkably improved their CE image reading ability with SSP-AR. CONCLUSIONS: Our study shows that the newly upgraded DL-based algorithm SS Plus can detect GI lesions and help improve the diagnostic performance of junior endoscopists in interpreting CE videos.

Efficacy of cardiopulmonary rehabilitation nursing in enhancing pulmonary function, sleep quality, and living ability in COVID-19 patients.

OBJECTIVE: The purpose of this study was to elucidate the impact of cardiopulmonary rehabilitation nursing on the pulmonary function, sleep quality, and living ability of patients afflicted with Coronavirus Disease 2019 (COVID-19). METHODS: A total of 98 patients with COVID-19 treated at The People's Hospital of Guang'an between September 2021 and January 2023 were retrospectively collected as the research subjects. Among them, 48 patients who received standard nursing care from September 2021 to September 2022 were set as the control group, and 50 patients who underwent cardiopulmonary rehabilitation nursing from October 2022 to January 2023 were set as the research group. The pulmonary function indicators [including Forced Expiratory Volume in 1 second (FEV1) and Left Ventricular Ejection Fraction (LVEF)], sleep quality [evaluated using the Pittsburgh Sleep Quality Index (PSQI)], and living ability [assessed by the 36-Item Short Form Survey (SF-36) scale] pre- and post-intervention were compared between the two groups. RESULTS: Pre-intervention, FEV1, LVEF, PSQI scores, inflammatory factor levels [C-reactive protein (CRP), procalcitonin (PCT)], and SF-36 scores showed no significant differences between the two groups (P>0.05). Post-intervention, the research group exhibited notably enhanced FEV1 and LVEF, lower PSQI scores, lower CRP and PCT, and higher SF-36 scores compared with the control group, with statistical significance (P<0.05). Multifactorial logistic regression analysis showed that non-receipt of cardiopulmonary rehabilitation, age ≥60 years, concurrent respiratory failure, coexistent heart failure, and acid-base imbalance were independent risk factors of adverse outcomes in COVID-19 patients (P<0.05). CONCLUSION: Application of cardiopulmonary rehabilitation nursing in COVID-19 patients can significantly improve pulmonary function, sleep quality, and overall quality of life, and relieve the inflammatory state of the patients, thereby enhancing prognosis. This approach has certain value of popularization and application.

Association of Triglyceride Glucose-Derived Indexes with Recurrent Events Following Atherosclerotic Cardiovascular Disease.

Background: Triglyceride glucose (TyG) and TyG-body mass index (TyG-BMI) are reliable surrogate indexes of insulin resistance and used for risk stratification and outcome prediction in patients with atherosclerotic cardiovascular disease (ASCVD). Here, we inserted estimated average glucose (eAG) into the TyG (TyAG) and TyG-BMI (TyAG-BMI) as derived parameters and explored their clinical significance in cardiovascular risk prediction. Methods: This was a population-based cohort study of 9,944 Chinese patients with ASCVD. The baseline admission fasting glucose and A1C-derived eAG values were recorded. Cardiovascular events (CVEs) that occurred during an average of 38.5 months of follow-up were recorded. We stratified the patients into four groups by quartiles of the parameters. Baseline data and outcomes were analyzed. Results: Distribution of the TyAG and TyAG-BMI indexes shifted slightly toward higher values (the right side) compared with TyG and TyG-BMI, respectively. The baseline levels of cardiovascular risk factors and coronary severity increased with quartile of TyG, TyAG, TyG-BMI, and TyAG-BMI (all P<0.001). The multivariate-adjusted hazard ratios for CVEs when the highest and lowest quartiles were compared from low to high were 1.02 (95% confidence interval [CI], 0.77 to 1.36; TyG), 1.29 (95% CI, 0.97 to 1.73; TyAG), 1.59 (95% CI, 1.01 to 2.58; TyG-BMI), and 1.91 (95% CI, 1.16 to 3.15; TyAG-BMI). The latter two showed statistical significance. Conclusion: This study suggests that TyAG and TyAG-BMI exhibit more information than TyG and TyG-BMI in disease progression among patients with ASCVD. The TyAG-BMI index provided better predictive performance for CVEs than other parameters.

Exploring secondary aerosol formation associated with elemental carbon in the lower free troposphere.

The variability of element carbon (EC) mixed with secondary species significantly complicates the assessment of its environmental impact, reflecting the complexity and diversity of EC-containing particles' composition and morphology during their ascent and regional transport. While the catalytic role of EC in secondary aerosol formation is recognized, the effects of heterogeneous chemistry on secondary species formation within diverse EC particle types are not thoroughly understood, particularly in the troposphere. Alpine sites offer a prime environment to explore EC properties post-transport from the ground to the free troposphere. Consequently, we conducted a comprehensive study on the genesis of secondary aerosols in EC-containing particles at Mt. Hua (altitude: 2069 m) from 1 May to 10 July, using a single particle aerosol mass spectrometer (SPAMS). Our analysis identified six major EC particle types, with EC-K, EC-SN, and EC-NaK particles accounting for 27.6 %, 27.0 %, and 19.6 % of the EC particle population, respectively. The concentration-weighted trajectory (CWT) indicated that the lower free troposphere over Mt. Hua is significantly affected by anthropogenic emissions at ground-level, predominantly from northwestern and eastern China. Atmospheric interactions are crucial in generating high sulfate levels in EC-SN and EC-OC particles (> 70 %) and notable nitrate levels in EC-K, EC-BB, and EC-Fe particles (> 80 %). The observed high chloride content in EC-OC particles (56 ± 32 %) might enhance chlorine's reactivity with organic compounds via heterogeneous reactions within the troposphere. Distinct diurnal cycles for sulfate and nitrate are mainly driven by varying transport dynamics and formation processes, showing minimal dependency on EC particle types. Enhanced nocturnal oxalate conversion in EC-Fe particles is likely due to the aqueous oxidation of precursors, with Fe-catalyzed Fenton reactions enhancing OH radical production. This investigation provides critical insights into EC's role in secondary aerosol development during its transport in the lower free troposphere.

Dimension Prediction and Microstructure Study of Wire Arc Additive Manufactured 316L Stainless Steel Based on Artificial Neural Network and Finite Element Simulation.

The dimensional accuracy and microstructure affect the service performance of parts fabricated by wire arc additive manufacturing (WAAM). Regulating the geometry and microstructure of such parts presents a challenge. The coupling method of an artificial neural network and finite element (FE) is proposed in this research for this purpose. Back-propagating neural networks (BPNN) based on optimization algorithms were established to predict the bead width (BW) and height (BH) of the deposited layers. Then, the bead geometry was modeled based on the predicted dimension, and 3D FE heat transfer simulation was performed to investigate the evolution of temperature and microstructure. The results showed that the errors in BW and BH were less than 6%, and the beetle antenna search BPNN model had the highest prediction accuracy compared to the other models. The simulated melt pool error was less than 5% with the experimental results. The decrease in the ratio of the temperature gradient and solidification rate induced the transition of solidified grains from cellular crystals to columnar dendrites and then to equiaxed dendrites. Accelerating the cooling rate increased the primary dendrite arm spacing and δ-ferrite content. These results indicate that the coupling model provides a pathway for regulating the dimensions and microstructures of manufactured parts.

Multilevel Proteomic Profiling of Colorectal Adenocarcinoma Caco-2 Cell Differentiation to Characterize an Intestinal Epithelial Model.

Emergent advancements on the role of the intestinal microbiome for human health and disease necessitate well-defined intestinal cellular models to study and rapidly assess host, microbiome, and drug interactions. Differentiated Caco-2 cell line is commonly utilized as an epithelial model for drug permeability studies and has more recently been utilized for investigating host-microbiome interactions. However, its suitability to study such interactions remains to be characterized. Here, we employed multilevel proteomics to demonstrate that both spontaneous and butyrate-induced Caco-2 differentiations displayed similar protein and pathway changes, including the downregulation of proteins related to translation and proliferation and upregulation of functions implicated in host-microbiome interactions, such as cell adhesion, tight junction, extracellular vesicles, and responses to stimuli. Lysine acetylomics revealed that histone protein acetylation levels were decreased along with cell differentiation, while the acetylation in proteins associated with mitochondrial functions was increased. This study also demonstrates that, compared to spontaneous differentiation methods, butyrate-containing medium accelerates Caco-2 differentiation, with earlier upregulation of proteins related to host-microbiome interactions, suggesting its superiority for assay development using this intestinal model. Altogether, this multiomics study emphasizes the controlled progression of Caco-2 differentiation toward a specialized intestinal epithelial-like cell and establishes its suitability for investigating the host-microbiome interactions.

Sustainable All-Day Thermoelectric Power Generation From the Hot Sun and Cold Universe.

Energy conversion from the environment into electricity is the most direct and effective electricity source to sustainably power off-grid electronics, once the electricity requirement exceeds the capability of traditional centralized power supply systems. Normally photovoltaic cells have enabled distributed power generation during the day, but do not work at night. Thus, efficient electricity generation technologies for a sustainable all-day power supply with no necessity for energy storage remain a challenge. Herein, an innovative all-day power generation strategy is reported, which self-adaptively integrates the diurnal photothermal and nocturnal radiative cooling processes into the thermoelectric generator (TEG) via the spectrally dynamic modulated coating, to continuously harvest the energy from the hot sun and the cold universe for power generation. Synergistic with the optimized latent heat phase change material, the electricity generation performance of the TEG is dramatically enhanced, with a maximum power density exceeding 1000 mW m-2 during the daytime and up to 25 mW m-2 during the nighttime, corresponding to an improvement of 123.1% and 249.1%, compared with the conventional strategy. This work maximizes the utilization of ambient energy resources to provide an environmentally friendly and uninterrupted power generation strategy. This opens up new possibilities for sustained power generation both daytime and nighttime.

Reliable detection of malachite green by self-assembled SERS substrates based on gold-silicon heterogeneous nano pineapple structures.

Morphology regulation of heterodimer nanoparticles and the use of their asymmetric features for further practical applications are crucial because of the rich optical properties and various combinations of heterodimers. This work used silicon to asymmetrically wrap half of a gold sphere and grew gold branches on the bare gold surface to form heterogeneous nano pineapples (NPPs) which can effectively improve Surface-enhanced Raman scattering (SERS) properties through chemical enhancement and lightning-rod effect respectively. The asymmetric structures of NPPs enabled them to self-assemble into the monolayer membrane with consistent branch orientation. The prepared substrate had high homogeneity and better SERS ability than disorganized substrates, and achieved reliable detection of malachite green (MG) in clams with a detection limit of 7.8 × 10-11 M. This work provided a guide to further revise the morphology of heterodimers and a new idea for the use of asymmetric dimers for practically photochemical and biomedical sensing.

The hepatocellular carcinoma risk in patients with HBV-related cirrhosis: a competing risk nomogram based on a 4-year retrospective cohort study.

Objective: The study aimed to build and validate a competitive risk nomogram to predict the cumulative incidence of hepatocellular carcinoma (HCC) for patients with hepatitis B virus (HBV)-related cirrhosis. Methods: A total of 1401 HBV-related cirrhosis patients were retrospectively enrolled from January 1, 2011 to December 31, 2014. Application of 20 times imputation dealt with missing data using multiple imputation by chained equations (MICE). The patients were randomly divided into a training set (n = 1017) and a validation set (n = 384) at a ratio of 3:1. A prediction study was carried out using a competing risk model, where the event of interest was HCC and the competing events were death and liver transplantation, and subdistribution hazard ratios (sHRs) with 95% CIs were reported. The multivariate competing risk model was constructed and validated. Results: There was a negligible difference between the original database and the 20 imputed datasets. At the end of follow-up, the median follow-up time was 69.9 months (interquartile range: 43.8-86.6). There were 31.5% (442/1401) of the patients who developed HCC, with a 5-year cumulative incidence of 22.9 (95%CI, 20.8%-25.2%). The univariate and multivariate competing risk regression and construction of the nomogram were performed in 20 imputed training datasets. Age, sex, antiviral therapy history, hepatitis B e antigen, alcohol drinking history, and alpha-fetoprotein levels were included in the nomogram. The area under receiver operating characteristic curve values at 12, 24, 36, 60, and 96 months were 0.68, 0.69, 0.70, 0.68, and 0.80, and the Brier scores were 0.30, 0.25, 0.23, 0.21, and 0.20 in the validation set. According to the cumulative incidence function, the nomogram effectively screened out high-risk HCC patients from low-risk patients in the presence of competing events (Fine-Gray test p < 0.001). Conclusion: The competitive risk nomogram was allowed to be used for predicting HCC risk in individual patients with liver cirrhosis, taking into account both the association between risk factors and HCC and the modifying effect of competition events on this association.

Automated chemoenzymatic modular synthesis of human milk oligosaccharides on a digital microfluidic platform.

Glycans, along with proteins, nucleic acids, and lipids, constitute the four fundamental classes of biomacromolecules found in living organisms. Generally, glycans are attached to proteins or lipids to form glycoconjugates that perform critical roles in various biological processes. Automatic synthesis of glycans is essential for investigation into structure-function relationships of glycans. In this study, we presented a method that integrated magnetic bead-based manipulation and modular chemoenzymatic synthesis of human milk oligosaccharides (HMOs), on a DMF (Digital Microfluidics) platform. On the DMF platform, enzymatic modular reactions were conducted in solution, and purification of products or intermediates was achieved by using DEAE magnetic beads, circumventing the intricate steps required for traditional solid-phase synthesis. With this approach, we have successfully synthesized eleven HMOs with highest yields of up to >90% on the DMF platform. This study would not only lay the foundation for OPME synthesis of glycans on the DMF platform, but also set the stage for developing automated enzymatic glycan synthesizers based on the DMF platform.

The effect of lipid-lowering therapy on lipid-related residual risk factors: a prospective study.

BACKGROUND: Remnant cholesterol (RC) and nonhigh-density lipoprotein cholesterol (nonHDL-C) are key risk factors for atherosclerotic cardiovascular disease (ASCVD), with apolipoprotein B (apoB) and lipoprotein(a) [Lp(a)] also contributing to its residual risk. However, real-world population-based evidence regarding the impact of current clinical LDL-C-centric lipid-lowering therapy (LLT) on achieving RC and nonHDL-C goals, as well as on modifying residual CVD risk factors is limited. METHODS: This prospective observational study enrolled 897 CVD patients from September, 2020 to July, 2021. All participants had previously received low-/moderate-intensity LLT and were discharged with either low-/moderate-intensity LLT or high-intensity LLT. After a median follow-up of 3 months, changes in RC, nonHDL-C, and other biomarkers were assessed. Multivariate logistic regression was performed to analyze the impact of the LLT on goal attainment. RESULTS: Among all patients, 83.50% transitioned to high-intensity LLT from low or moderate. After follow-up, the high-intensity group saw significantly greater reductions in RC (-20.51% vs. -3.90%, P = 0.025), nonHDL-C (-25.12% vs. 0.00%, P < 0.001), apoB (-19.35% vs. -3.17%, P < 0.001), triglycerides (-17.82% vs. -6.62%, P < 0.001), and LDL-C and total cholesterol. Spearman correlation analysis revealed that LDL-C reduction from current LLT was strongly correlated with nonHDL-C reduction (r = 0.87, P < 0.001). Patients who received high-intensity LLT had significant improvements in attainment of RC (from 44.2% to 60.7%, χ² = 39.23, P < 0.001) and nonHDL-C (from 19.4% to 56.9%, χ² = 226.06, P < 0.001) goals. Furthermore, multivariate logistic regression showed that high-intensity LLT was a protective factor for RC [odds ratio (OR) = 0.66; 95% confidence intervals (CI), 0.45-0.97; P = 0.033] and nonHDL-C goal attainment (OR = 0.51; 95% CI, 0.34-0.75; P < 0.001), without a significant increase of adverse reactions. CONCLUSION: Current levels of clinically prescribed LDL-C-centric treatment can reduce RC and other lipid-related residual risk factors, but high-intensity LLT is better at achieving nonHDL-C and RC goals than low-/moderate-intensity LLT, with a good safety profile. More targeted RC treatments are still needed to reduce residual lipid risk further.

Fabrication of SERS composite substrates using Ag nanotriangles-modified SiO2 photonic crystal and the application of malachite green detection.

A novel surface-enhanced Raman scattering (SERS) composite substrates on the basis of Ag triangular nanoplates(Ag TNPs)-modified SiO2 photonic crystals (PC) is fabricated and applied to the SERS detection of malachite green (MG). It consists of uniformly arranged Ag TNP@SiO2, a new PC. Notably, Ag TNP are uniformly aligned on the SiO2 surface, forming a three-dimensional high-density hotspot nanostructure. With the tip "hot spots" of Ag TNPs, Bragg diffraction of SiO2 and coupling enhancement between Ag TNPs and SiO2, the SERS enhancement of this composite substrates was multiplied. The effect on the SERS of Ag TNP@SiO2 composite substrate was systematically optimized by tuning Ag TNP size, size of SiO2 microspheres, coverage of Ag TNPs on SiO2 and fabrication method of Ag TNPs and PC. Moreover, the uniform of SERS composite substrates and Raman signal was dramatically increased by the method of vertical deposition. Eventually, the SERS composite substrates were employed in MG detection. Its broad detection range of 1 pM-1 µM and low limit of detection (LOD) of 0.49 pM indicated acceptable sensitivity and repeatability. This work illustrates the promising applicability in food safety analysis based on SERS composite substrates composed by Ag TNP@SiO2 with numerous SERS enhancements and excellent stability.

Study on the Phase Behavior Simulation Method of High-Salinity Reservoirs.

The presence of salinity affects the accuracy of existing correlations used in the equation of state. Moreover, the variation of salinity is often ignored in the systematic analysis of the phase diagram, resulting in a large error in the final calculation result. It is obvious that the conventional phase equilibrium calculation is not applicable in a high-salinity reservoir. By introducing the hydrocarbon-brine binary interaction coefficient and α-function, combined with the definition of salinity, and considering the variation of salinity under different pressure and temperature conditions, a more perfect phase equilibrium calculation model was established. The complete phase diagram was drawn, and the calculation results of salinity distribution are obtained. The effect of the mole percentage of water and salt content on the phase behavior was simulated. Finally, the phase distribution simulation is carried out based on the measured data. The phase state and salinity variation law of a high-salinity reservoir are obtained. According to the fluid composition of different periods, the real phase state of the high-salinity reservoir can be monitored in real time. It can provide a theoretical basis for the gas reservoir development and the dynamic evaluation of gas storage injection and production with a hydrocarbon-brine two-phase system.

Inhibition of phospholipase D promotes neurological function recovery and reduces neuroinflammation after spinal cord injury in mice.

Introduction: Spinal cord injury (SCI) is a severely disabling disease. Hyperactivation of neuroinflammation is one of the main pathophysiological features of secondary SCI, with phospholipid metabolism playing an important role in regulating inflammation. Phospholipase D (PLD), a critical lipid-signaling molecule, is known to be involved in various physiological processes, including the regulation of inflammation. Despite this knowledge, the specific role of PLD in SCI remains unclear. Methods: In this study, we constructed mouse models of SCI and administered PLD inhibitor (FIPI) treatment to investigate the efficacy of PLD. Additionally, transcriptome sequencing and protein microarray analysis of spinal cord tissues were conducted to further elucidate its mechanism of action. Results: The results showed that PLD expression increased after SCI, and inhibition of PLD significantly improved the locomotor ability, reduced glial scarring, and decreased the damage of spinal cord tissues in mice with SCI. Transcriptome sequencing analysis showed that inhibition of PLD altered gene expression in inflammation regulation. Subsequently, the protein microarray analysis of spinal cord tissues revealed variations in numerous inflammatory factors. Biosignature analysis pointed to an association with immunity, thus confirming the results obtained from transcriptome sequencing. Discussion: Collectively, these observations furnish compelling evidence supporting the anti-inflammatory effect of FIPI in the context of SCI, while also offering important insights into the PLD function which may be a potential therapeutic target for SCI.

Association of acute glycemic parameters at admission with cardiovascular mortality in the oldest old with acute myocardial infarction.

OBJECTIVES: Stress-related glycemic indicators, including admission blood glucose (ABG), stress-hyperglycemia ratio (SHR), and glycemic gap (GG), have been associated with worse outcomes after acute myocardial infarction (AMI). However, data regarding their prognostic value in the oldest old with AMI are unavailable. Therefore, this study aimed to investigate the association of stress-related glycemic indicators with short- and long-term cardiovascular mortality (CVM) in the oldest old (≥ 80 years) with AMI. METHODS: In this prospective study, a total of 933 consecutive old patients with AMI admitted to FuWai hospital (Beijing, China) were enrolled. On admission, ABG, SHR, and GG were assessed and all participants were classified according to their quartiles. Kaplan-Meier, restricted cubic splines (RCS), and multivariate Cox regression analyses were performed to evaluate the association between these glycemic indicators and CVM within 30 days and long-term follow-up. RESULTS: During an average of 1954 patient-years of follow-up, a total of 250 cardiovascular deaths were recorded. Kaplan-Meier analyses showed the lowest CVM in quartile 1 of ABG and in quartile 2 of SHR and GG. After adjusting for potential covariates, patients in quartile 4 of ABG, SHR, and GG had a respective 1.67-fold (95% CI: 1.03-2.69; P = 0.036), 1.80-fold (95% CI: 1.16-2.79; P = 0.009), and 1.78-fold (95% CI: 1.14-2.79; P = 0.011) higher risk of long-term CVM risk compared to those in the reference groups (quartile 1 of ABG and quartile 2 of SHR and GG). Furthermore, RCS suggested a J-shaped relationship of ABG and a U-shaped association of SHR and GG with long-term CVM. Additionally, we observed similar associations of these acute glycemic parameters with 30-day CVM. CONCLUSIONS: Our data first indicated that SHR and GG consistently had a U-shaped association with both 30-day and long-term CVM among the oldest old with AMI, suggesting that they may be useful for risk stratification in this special population.

Atorvastatin causes developmental and behavioral toxicity in yellowstripe goby (Mugilogobius chulae) embryos/larvae via disrupting lipid metabolism and autophagy processes.

Atorvastatin (ATV) is one of the most commonly prescribed lipid-lowering drugs detected frequently in the environment due to its high use and low degradation rate. However, the toxic effects of residual ATV in the aquatic environment on non-target organisms and its toxic mechanisms are still largely unknown. In the present study, embryos of a native estuarine benthic fish, Mugilogobius chulae, were employed to investigate the developmental and behavioral toxic effects of ATV including environmentally relevant concentrations. The aim of this study was to provide a scientific basis for ecological risk assessment of ATV in the aquatic environment by investigating the changes of biological endpoints at multiple levels in M. chulae embryos/larvae. The results showed that ATV had significantly lethal and teratogenic effects on M. chulae embryos/larvae and caused abnormal changes in developmental parameters including hatch rate, body length, heart rate, and spontaneous movement. ATV exposure caused oxidative stress in M. chulae embryos/larvae subsequently inhibited autophagy and activated apoptosis, leading to abnormal developmental processes and behavioral changes in M. chulae embryos/larvae. The disruptions of lipid metabolism, autophagy, and apoptosis in M. chulae embryos/larvae caused by ATV exposure may pose a potential ecological risk at the population level.

Itaconate alleviates anesthesia/surgery-induced cognitive impairment by activating a Nrf2-dependent anti-neuroinflammation and neurogenesis via gut-brain axis.

BACKGROUND: Postoperative cognitive dysfunction (POCD) is a common neurological complication of anesthesia and surgery in aging individuals. Neuroinflammation has been identified as a hallmark of POCD. However, safe and effective treatments of POCD are still lacking. Itaconate is an immunoregulatory metabolite derived from the tricarboxylic acid cycle that exerts anti-inflammatory effects by activating the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway. In this study, we investigated the effects and underlying mechanism of 4-octyl itaconate (OI), a cell-permeable itaconate derivative, on POCD in aged mice. METHODS: A POCD animal model was established by performing aseptic laparotomy in 18-month-old male C57BL/6 mice under isoflurane anesthesia while maintaining spontaneous ventilation. OI was intraperitoneally injected into the mice after surgery. Primary microglia and neurons were isolated and treated to lipopolysaccharide (LPS), isoflurane, and OI. Cognitive function, neuroinflammatory responses, as well as levels of gut microbiota and their metabolites were evaluated. To determine the mechanisms underlying the therapeutic effects of OI in POCD, ML385, an antagonist of Nrf2, was administered intraperitoneally. Cognitive function, neuroinflammatory responses, endogenous neurogenesis, neuronal apoptosis, and Nrf2/extracellular signal-related kinases (ERK) signaling pathway were evaluated. RESULTS: Our findings revealed that OI treatment significantly alleviated anesthesia/surgery-induced cognitive impairment, concomitant with reduced levels of the neuroinflammatory cytokines IL-1ß and IL-6, as well as suppressed activation of microglia and astrocytes in the hippocampus. Similarly, OI treatment inhibited the expression of IL-1ß and IL-6 in LPS and isoflurane-induced primary microglia in vitro. Intraperitoneal administration of OI led to alterations in the gut microbiota and promoted the production of microbiota-derived metabolites associated with neurogenesis. We further confirmed that OI promoted endogenous neurogenesis and inhibited neuronal apoptosis in the hippocampal dentate gyrus of aged mice. Mechanistically, we observed a decrease in Nrf2 expression in hippocampal neurons both in vitro and in vivo, which was reversed by OI treatment. We found that Nrf2 was required for OI treatment to inhibit neuroinflammation in POCD. The enhanced POCD recovery and promotion of neurogenesis triggered by OI exposure were, at least partially, mediated by the activation of the Nrf2/ERK signaling pathway. CONCLUSIONS: Our findings demonstrate that OI can attenuate anesthesia/surgery-induced cognitive impairment by stabilizing the gut microbiota and activating Nrf2 signaling to restrict neuroinflammation and promote neurogenesis. Boosting endogenous itaconate or supplementation with exogenous itaconate derivatives may represent novel strategies for the treatment of POCD.

Regioselective synthesis of isoquinolinonediones through remote unactivated C(sp3)-H bonds.

Herein, a general strategy for the remote-site-selective cascade addition/cyclization of unactivated C(sp3)-H bonds in free alcohols and sulfonamides to build isoquinolinonedione skeletons is developed. The site selectivity occurs predominantly via a 1,5-hydrogen atom transfer (HAT) process, triggered by heteroatom-centred radicals generated directly under silver catalysis. A broad substrate scope and excellent regio-/chemo-selective control are demonstrated in this method.