Dual-response of multi-functional microsphere system to ultrasound and microenvironment for enhanced bone defect treatment.

Using bone tissue engineering strategies to achieve bone defect repair is a promising modality. However, the repair process outcomes are often unsatisfactory. Here we properly designed a multi-functional microsphere system, which could deliver bioactive proteins under the dual response of ultrasound and microenvironment, release microenvironment-responsive products on demand, reverse bone injury microenvironment, regulate the immune microenvironment, and achieve excellent bone defect treatment outcomes. In particular, the MnO2 introduced into the poly(lactic-co-glycolic acid) (PLGA) microspheres during synthesis could consume the acid produced by the degradation of PLGA to protect bone morphogenetic protein-2 (BMP-2). More importantly, MnO2 could consume reactive oxygen species (ROS) and produce Mn2+ and oxygen (O2), further promoting the repair of bone defects while reversing the microenvironment. Moreover, the reversal of the bone injury microenvironment and the depletion of ROS promoted the polarization of M1 macrophages to M2 macrophages, and the immune microenvironment was regulated. Notably, the ultrasound (US) irradiation used during treatment also allowed the on-demand release of microenvironment-responsive products. The multi-functional microsphere system combines the effects of on-demand delivery, reversal of bone injury microenvironment, and regulation of the immune microenvironment, providing new horizons for the clinical application of protein delivery and bone defect repair.

Urban greenspaces shape soil protist communities in a location-specific manner.

The impacts of urbanization on aboveground biodiversity are well studied, and its impact on soil microorganisms are also receiving increased attention. However, the impact of urbanization on the soil protists are hardly investigated. Here, we studied how urbanization and distinct urban greenspaces affect protist communities. We used amplicon sequencing of the18 S rRNA gene of samples from five types of urban greenspaces (parks, greenbelts, industrial areas, residential areas and hospital lawns), neighboring natural forests and agricultural ecosystems in Ningbo, China. We found that urban greenspaces harbored higher protist α-diversity than forests, while protist ß-diversity increased from agricultural systems to urban greenspaces to forests. Among the studied driving factors, soil bacterial α- and ß-diversity best predicted phagotrophic protist α- and ß-diversity in urban greenspaces, while differences in α- and ß-diversity of phototrophic protists were best explained by soil carbon-to-nitrogen ratio and fungal ß-diversity, respectively. Abiotic factors i.e., total phosphorus and carbon-to-nitrogen ratio, best predicted the α- and ß-diversity of protist parasites in urban greenspaces, respectively. The results revealed that the composition and drivers of protist communities vary between functional groups and urban ecosystems. Overall, our findings contribute to a better understanding of drivers of soil protist communities and indicate that soil protist communities and associated soil functions could be managed in predictable ways in urban greenspaces.

Continuous cropping disorders of eggplants (Solanum melongena L.) and tomatoes (Solanum lycopersicum L.) in suburban agriculture: Microbial structure and assembly processes.

Deciphering the intricate relationships between microorganisms and plants remains a formidable challenge in plant microbial ecology, an area that holds promise for optimizing microbial interventions to enhance stress resilience and agricultural yields. In our investigation, we procured samples during 2019 and 2022 from a suburban agricultural greenhouse. Our study delineated the composition of bacterial and fungal communities across various ecological niches-namely, the rhizosphere soil, bulk soil, and phyllosphere of healthy, Ralstonia solanacearum-infected, and dead eggplants and tomatoes. The structure and composition of both fungal and bacterial communities change significantly under the influence of the host genotype across all samples. In the tomato or eggplant groups, bacterial wilt exerts a more pronounced impact on the bacterial community than on the fungal community. We speculate that the rhizosphere of healthy eggplants and tomatoes harbored more antibiotic-producing (e.g., Amycolatopsis and Penicillium) and biocontrol (e.g., Bacillus) strains, which can lead to have lower absolute abundance of R. solanacearum. In the context of R. solanacearum invasion, deterministic processes were responsible for shaping 70.67 % and 80.63 % of the bacterial community assembly in the rhizosphere of eggplants and tomatoes, respectively. Deterministic processes dominated the assembly of fungal communities in the rhizosphere of R. solanacearum-infected eggplants, whereas the opposite was true in the tomatoes. Homogeneous selection emerged as the predominant force governing the bacterial community assembly in the rhizospheres of R. solanacearum-infected eggplants and tomatoes. The bacterial co-occurrence networks in healthy rhizosphere soil were characterized by reduced vulnerability and enhanced stability (i.e., robustness index) and complexity (i.e., cohesion index), compared to their infected counterparts. In summary, complex microbial networks in rhizosphere soils are more resistant to invasion by soil-borne pathogens. The dynamics of bacterial interactions and community assembly processes are pivotal for effective microbiome management and offer predictive insights into the ecological ramifications of R. solanacearum invasions.

Combining physical-based model and machine learning to forecast chlorophyll-a concentration in freshwater lakes.

Increasing algal blooms in freshwater lakes have become a serious challenge facing the world. Short-term forecast of chlorophyll-a concentration (Chla) is essential for providing early warnings and taking action to mitigate the risks of algal blooms in freshwater lakes. At present, a variety of data-driven models and physical-based models have been developed for Chla forecast, yet how to effectively combine multiple models for improving the forecast accuracy remains largely unknown. Here we developed an effective model by combining a physical-based model and machine learning algorithms (long short-term memory, LSTM; random forest, RF; support vector machine, SVM) to forecast the Chla in a freshwater lake, and a Bayesian model averaging (BMA) ensemble forecasting method was further proposed to improve the accuracy and reliability of the forecast results. We found that, with the increase of time steps of advance forecast from 1-day to 7-day, the forecast accuracy as measured by R2 of the machine learning algorithms is decreased from 0.95 to 0.68. The combination of physical-based modeling with LSTM had great capability in short-term forecast of Chla, owing to the fact that the physical-based model can provide high-frequency Chla data and LSTM is skilled at forecasting in the sequence. This is also evidenced by the weights in the BMA method. The proposed BMA short-term ensemble forecasting results had the robust performance when compared to each individual machine learning forecast model for the 7-day advance forecast, with the largest R2 (0.834) and the smallest RMSE (0.267 µg/L). In particular, the uncertainty of a single machine learning model can be effectively reduced by the BMA method.

Bayesian model averaging by combining deep learning models to improve lake water level prediction.

Water level (WL) is an essential indicator of lakes and sensitive to climate change. Fluctuations of lake WL may significantly affect water supply security and ecosystem stability. Accurate prediction of lake WL is, therefore, crucial for water resource management and eco-environmental protection. In this study, three deep learning (DL) models, including long short-term memory (LSTM), the gated recurrent unit (GRU), and the temporal convolutional network (TCN), were used to predict WLs at five stations of Poyang Lake for different forecast periods (1-day ahead, 3-day ahead, and 7-day ahead). The forecast results of the three DL models were synthesized through Bayesian model averaging (BMA) to improve prediction accuracy, and Monte Carlo sampling method was used to calculated the 90 % confidence intervals to analyze the model uncertainty. All the three DL models achieved satisfactory prediction accuracy. GRU performed best in most forecast scenarios, followed by TCN and LSTM. None of the models, however, consistently provided the optimal results in all forecast scenarios. Lake WL prediction accuracy of BMA had a further improvement in metrics of NSE and R2 in 80 % of the forecast scenarios and ranked at least top two in all forecast scenarios. The uncertainty analysis showed that the containing ration (CR) values were above 84 % while the relative bandwidth (RB) maintained reliable performance over the 7-day ahead prediction. The proposed framework in the present study can realize satisfactory WL forecast accuracy while avoiding complex comparison and selection of DL models, and it can also be easily applied to the prediction of other hydrological variables.

A CRISPR-Cas12a-based platform facilitates the detection and serotyping of Streptococcus suis serotype 2.

Streptococcus suis serotype 2 is an economically important zoonotic pathogen that causes septicemia, arthritis, and meningitis in pigs and humans. S. suis serotype 2 is responsible for substantial economic losses to the swine industry and poses a serious threat to public health, and accurate and rapid detection is important for the prevention and control of epidemic disease. In this study, we developed a high-fidelity detection and serotyping platform for S. suis serotype 2 based on recombinase polymerase amplification (RPA) and a clustered regularly interspaced short palindromic repeat (CRISPR)-Cas12a system called Cards-SSJ/K. Cards-SSJ had a detection limit of 10 CFU, takes <60 min, and no cross-reaction was found with other S. suis serotypes, closely related Streptococcus spp., or common pig pathogens, and Cards-SSK could differentiate serotype 2 from serotype 1/2. Results from Cards-SSJ and qPCR were equivalent in detecting S. suis serotype 2 in tissue samples. Analysis indicated that despite a relatively high reagent cost compared to PCR and qPCR, Cards-SSJ was less time-consuming and had low requirements for equipment and personnel. Thus, it is an excellent method for point-of-care detection for S. suis serotype 2.

Effects of NO2 and SO2 on the secondary organic aerosol formation from ß-pinene photooxidation.

Elucidating the effects of anthropogenic pollutants on the photooxidation of biogenic volatile organic compounds is crucial to understanding the fundamental mechanisms of secondary organic aerosol (SOA) formation. Here, the impacts of NO2 and SO2 on SOA formation from the photooxidation of a representative monoterpene, ß-pinene, were investigated by a number of laboratory studies. The results indicated NO2 enhanced the SOA mass concentrations and particle number concentrations under both low and high ß-pinene conditions. This could be rationalized that the increased O3 concentrations upon the NOx photolysis was helpful for the generation of more amounts of O3-oxidized products, which accelerated the SOA nucleation and growth. Combing with NO2, the promotion of the SOA yield by SO2 was mainly reflected in the increase of mass concentration, which might be due to the elimination of the newly formed particles by the initially formed particles. The observed low oxidation degree of SOA might be attributed to the fast growth of SOA, resulting in the uptake of less oxygenated gas-phase species onto the particle phase. The present findings have important implications for SOA formation affected by anthropogenic-biogenic interactions in the ambient atmosphere.

Fouling-resistant electrode for electrochemical sensing based on covalent-organic frameworks TpPA-1 dispersed cabon nanotubes.

The key problem that limits the practical applications of nonenzymatic electrochemical sensors in biological media, is the biofouling and chemical fouling of electrodes due to the adsorption of biological molecules and oxidation (reduction) products. Electrode fouling will cause low accuracy, poor stability, and low sensitivity. Here, a simple and efficient antifouling electrode was demonstrated for electrochemical sensing based on covalent-organic framework (COF) TpPA-1 and carboxylic multi-walled carbon nanotubes (CNT) composites. COF TpPA-1 possesses abundant hydrophilic groups, which assisted the dispersion of CNT in water and formed uniform composites by π-π interaction. In addition, the introduction of CNT into the composites improved the electron transfer rate of COF TpPA-1. The antifouling interface was characterized by electrochemistry, contact angle measurement, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS). The electrode showed good chemical and bio-fouling resistant performance for the electrochemical detection of ß-nicotinamide adenine dinucleotide (NADH) and uric acid (UA) in real serum samples.

Classification of regulatory T cells and their role in myocardial ischemia-reperfusion injury.

Myocardial ischemia-reperfusion injury (MIRI) is closely related to the final infarct size in acute myocardial infarction (AMI). Therefore, reducing MIRI can effectively improve the prognosis of AMI patients. At the same time, the healing process after AMI is closely related to the local inflammatory microenvironment. Regulatory T cells (Tregs) can regulate various physiological and pathological immune inflammatory responses and play an important role in regulating the immune inflammatory response after AMI. However, different subtypes of Tregs have different effects on MIRI, and the same subtype of Tregs may also have different effects at different stages of MIRI. This article systematically reviews the classification and function of Tregs, as well as the role of various subtypes of Tregs in MIRI. A comprehensive understanding of the role of each subtype of Tregs can help design effective methods to control immune reactions, reduce MIRI, and provide new potential therapeutic options for AMI.

Step-by-Step Modulation of Crystalline Features and Exciton Kinetics for 19.2% Efficiency Ortho-Xylene Processed Organic Solar Cells.

With plenty of popular and effective ternary organic solar cells (OSCs) construction strategies proposed and applied, its power conversion efficiencies (PCEs) have come to a new level of over 19% in single-junction devices. However, previous studies are heavily based in chloroform (CF) leaving behind substantial knowledge deficiencies in understanding the influence of solvent choice when introducing a third component. Herein, we present a case where a newly designed asymmetric small molecular acceptor using fluoro-methoxylated end-group modification strategy, named BTP-BO-3FO with enlarged bandgap, brings different morphological evolution and performance improvement effect on host system PM6:BTP-eC9, processed by CF and ortho-xylene (o-XY). With detailed analyses supported by a series of experiments, the best PCE of 19.24% for green solvent-processed OSCs is found to be a fruit of finely tuned crystalline ordering and general aggregation motif, which furthermore nourishes a favorable charge generation and recombination behavior. Likewise, over 19% PCE can be achieved by replacing spin-coating with blade coating for active layer deposition. This work focuses on understanding the commonly met yet frequently ignored issues when building ternary blends to demonstrate cutting-edge device performance, hence, will be instructive to other ternary OSC works in the future.

Association of energy delivery with short-term survival in mechanically ventilated critically ill adult patients: a secondary analysis of the NEED trial.

BACKGROUND AND AIMS: The optimal energy delivery for mechanically ventilated patients is controversial, particularly during the first week of ICU admission. This study aimed to investigate the association between different caloric adequacy and 28-day mortality in a cohort of critically ill adults on mechanical ventilation. METHODS: This is a secondary analysis of a multicenter, cluster-randomized controlled trial. Eligible patients were divided into four quartiles (Q1-Q4) according to caloric adequacy calculated by the actual average daily energy delivery during the first seven days of ICU stay divided by energy requirement as a percentage. Cox proportional hazards models were used to examine the impact of different quartiles of caloric adequacy on 28-day mortality in the whole cohort and subgroups with different nutritional risk status at enrollment. RESULTS: A total of 1587 patients were included in this study, with an overall 28-day mortality of 15.8%. The average caloric adequacy was 26.3 ± 11.9% (Q1), 52.5 ± 5.5% (Q2), 71.7 ± 6.4% (Q3), 107.0 ± 22.2% (Q4), respectively (p < 0.001 among quartiles). Compared with Q1, Q3 was associated with lower mortality in the unadjusted model (hazard ratio [HR] = 0.536; 95% confidence interval [CI], 0.375-0.767; P = 0.001) and adjusted model (adjusted HR = 0.508; 95% CI, 0.339-0.761; P = 0.001). This association remained valid in the subgroup of high nutritional risk patients (unadjusted HR = 0.387; 95% CI, 0.238-0.627; P < 0.001 and adjusted HR = 0.369; 95% CI, 0.216-0.630; P < 0.001, respectively), but not in those with low risk. CONCLUSIONS: Energy delivery near the 70% energy requirements in the first week of ICU stay was associated with reduced 28-day mortality among mechanically ventilated critically ill patients, especially in patients with high nutrition risk at admission.

Spectroscopic Signature of the Carbon-Carbon Coupling Reaction between Carbon Monoxide and Nickel Carbide.

Spectroscopic characterization of ketenylidene complexes is of essential importance for understanding the structure-reactivity relationships of the catalytic sites. Here, we report a size-specific photoelectron velocity map imaging spectroscopic study of the reactions of carbon monoxide with nickel carbide. Quantum chemical calculations have been conducted to search for the energetically favorable isomers and to recognize the experimental spectra. The target products with the chemical formula of NiC(CO)n- (n = 3-5) are characterized to have an intriguing ketenylidene CCO unit. The evolution from NiC(CO)3- to NiC(CO)4- involves the breaking and formation of the Ni-C bond and the coordination conversion between the terminal and bridging carbonyls. Experimental and theoretical analyses reveal an efficient C-C bond formation process within the reactions of carbon monoxide and laser-vaporized nickel carbide. This work highlights the pivotal roles played by metal carbides in the C-C bond formation and also proposes new ideas for the design and chemical control of a broad class of complexes with unique physical and chemical properties.

In Vivo Effect of Single Intra-Articular Injection of Tranexamic Acid on Articular Cartilage and Meniscus: Study in a Rat Model.

BACKGROUND: Tranexamic acid (TXA) has been increasingly used in arthroscopic surgery to prevent hemarthrosis. Despite its effectiveness, safety concerns have been raised regarding its potential cytotoxicity to articular cartilage and meniscus following intra-articular injection. METHODS: To evaluate the impact of TXA on cartilage and meniscus, a rat model of knee instability was utilized wherein anterior cruciate ligament (ACL) transection surgery was followed by a single intra-articular injection of TXA at varying concentrations (0, 20, 50, 100, and 150 mg/mL) in saline solution. Cell viability assessment of the cartilage and meniscus (n = 6 per group) was conducted at 24 hours, and gross observation and histological analysis of the medial tibial plateau and medial meniscus were conducted at 2, 4, and 8 weeks (n = 6 per group and time point). RESULTS: The chondrocyte viability was significantly decreased in the 50, 100, and 150 mg/mL TXA groups compared with the specimens injected with saline solution only (saline group) (p = 0.001, p < 0.001, p < 0.001, respectively), as was meniscal cell viability (p = 0.042, p < 0.001, p < 0.001, respectively). At week 8, the saline and 20 and 50 mg/mL groups showed relatively normal appearances, whereas the 100 and 150 mg/mL groups exhibited increased and varying severity of cartilage and meniscal degeneration. In the 150 mg/mL group, the mean Osteoarthritis Research Society International score was significantly higher than that in the saline and 20 mg/mL groups (p = 0.010 and p = 0.007). Additionally, the mean meniscus score in the 150 mg/mL group was significantly higher than that in the saline, 20 mg/mL, and 50 mg/mL groups (p = 0.020, p = 0.021, p = 0.031, respectively). CONCLUSIONS: Our findings indicate that concentrations of TXA at or above 100 mg/mL can lead to decreased cell viability in both cartilage and meniscus, resulting in significant cartilage degeneration in rats with ACL transection. Furthermore, the use of 150 mg/mL of TXA led to significant meniscal degeneration. CLINICAL RELEVANCE: It is prudent to avoid using concentrations of TXA at or above 100 mg/mL for intra-articular injection, as such concentrations may result in adverse effects on the cartilage and meniscus.

Cis-trans isomerization of peptoid residues in the collagen triple-helix.

Cis-peptide bonds are rare in proteins, and building blocks less favorable to the trans-conformer have been considered destabilizing. Although proline tolerates the cis-conformer modestly among all amino acids, for collagen, the most prevalent proline-abundant protein, all peptide bonds must be trans to form its hallmark triple-helix structure. Here, using host-guest collagen mimetic peptides (CMPs), we discover that surprisingly, even the cis-enforcing peptoid residues (N-substituted glycines) form stable triple-helices. Our interrogations establish that these peptoid residues entropically stabilize the triple-helix by pre-organizing individual peptides into a polyproline-II helix. Moreover, noting that the cis-demanding peptoid residues drastically reduce the folding rate, we design a CMP whose triple-helix formation can be controlled by peptoid cis-trans isomerization, enabling direct targeting of fibrotic remodeling in myocardial infarction in vivo. These findings elucidate the principles of peptoid cis-trans isomerization in protein folding and showcase the exploitation of cis-amide-favoring residues in building programmable and functional peptidomimetics.

Synergistic toxicity of some food additives used in non-alcoholic beverages on renal tubular epithelial cells.

Evidences supported many food additives (FAs) possess toxicity to human health due to chronic excessive exposure. Global hygienic standards strictly limit the dosage of each FA and mixture of the same functional FAs. However, the synergetic effects caused by the combination of FAs with different functions require careful evaluation. In the present study, the content of each FA in beverages was determined by HPLC-UV-Vis detection. The cytotoxic effects of selected typical FAs alone or their combination were evaluated in human renal tubular epithelial cells. Mathematical Modeling and bioinformatics methods were employed to evaluate the toxicity of FAs and to predict the key target proteins of FAs on renal tubular cell toxicity, which were verified by western blot. The results indicated above 5 FAs were used in each surveyed beverage. The content of each FA and the respective ratios of the same functional FAs in each beverage did not exceed the maximum permitted level. But it was intensively shown that the significant synergistic cytotoxicity for the combination of FAs with lower concentration. The intercellular signaling transduction pathways including JNK/STAT, PI3P/AKT, and MAPK pathways, which could also be activated by PDGF signaling, were predicted to be involved in Fas-induced cytotoxicity. The increased expression of p-STAT3, p-JNK and p-AKT was associated with renal tubular injury. The current study implied the synergistic cytotoxic effect caused by multiple FAs at no toxic dosages via activated cellular transduction pathways regulating cell survival and apoptosis function, which warning of the synergistic toxic effects of different types of FAs.

Machine learning model for predicting physical activity related bleeding risk in Chinese boys with haemophilia A.

BACKGROUND: Physical activity is a crucial part of an active lifestyle for haemophiliac children. However, the fear of bleeds has been identified as barriers to participating physical activity for haemophiliac children even with prophylaxis. Lack of evidence and metrics driven by data is key problem. OBJECTIVES: We aim to develop machine learning models based on clinical data with multiple potential factors considered to predict risk of physical activity bleeding for haemophilia children with prophylaxis. METHODS: From this cohort study, we collected information on 98 haemophiliac children with adequate prophylaxis (trough FVIII:C level > 1 %). The involved potential predictor variables include demographic information, treatment information, physical activity, joint evaluation, and pharmacokinetic parameters, etc. We applied CoxPH, Random Survival Forests (RSF) and DeepSurv to construct prediction models for the risk of bleeding during physical activities. All three survival analysis models were internally and externally validated. RESULTS: A total of 98 patients were enrolled in this study. Their median age was 7.9 (5.5, 10.2) years. The CoxPH, RSF and DeepSurv models' discriminative and calibration abilities were all high, and the RSF model had the best performance (Internal validation: C-index, 0.7648 ± 0.0139; Brier Score, 0.1098 ± 0.0015; External validation: C-index, 0.7260 ± 0.0154; Brier Score, 0.0930 ± 0.0018). The prediction curves demonstrated that the developed RSF model can distinguish the risks well between bleeding and non-bleeding patients, as well as patients with different levels of physical activity. Meanwhile, the feature importance analysis confirmed that physical activity bleeding was deduced by comprehensive effects of various factors, and the importance of different factors on bleeding outcome is discrepant. CONCLUSIONS: This study revealed from the mechanism that it is necessary to incorporate multiple factors to accurately predict physical activity related bleeding risk. In clinical practice, the designed machine learning models can provide guidance for children with haemophilia A to positively participate in physical activity.

Design of Power Amplifiers for BDS-3 Terminal Based on InGaP/GaAs HBT MMIC and LGA Technology.

With the development and popularization of the Beidou-3 navigation satellite system (BDS-3), to ensure its unique short message function, it is necessary to integrate a radio frequency (RF) transmitting circuit with high performance in the BDS-3 terminal. As the key device in an RF transmitting circuit, the RF power amplifier (PA) largely determines the comprehensive performance of the circuit with its transmission power, efficiency, linearity, and integration. Therefore, in this paper, an L-band highly integrated PA chip compatible with 3 W and 5 W output power is designed in InGaP/GaAs heterojunction bipolar transistor (HBT) technology combined with temperature-insensitive adaptive bias technology, class-F harmonic suppression technology, analog pre-distortion technology, temperature-insensitive adaptive power detection technology, and land grid array (LGA) packaging technology. Additionally, three auxiliary platforms are proposed, dedicated to the simulation and optimization of the same type of PA designs. The simulation results show that at the supply voltage of 5 V and 3.5 V, the linear gain of the PA chip reaches 39.4 dB and 38.7 dB, respectively; the output power at 1 dB compression point (P1dB) reaches 37.5 dBm and 35.1 dBm, respectively; the saturated output power (Psat) reaches 38.2 dBm and 36.2 dBm, respectively; the power added efficiency (PAE) reaches 51.7% and 48.2%, respectively; and the higher harmonic suppression ratios are less than -62 dBc and -65 dBc, respectively. The size of the PA chip is only 6 × 4 × 1 mm3. The results also show that the PA chip has high gain, high efficiency, and high linearity under both output power conditions, which has obvious advantages over similar PA chip designs and can meet the short message function of the BDS-3 terminal in various application scenarios.

Effects of Block Copolymer Terminal Groups on Toughening Epoxy-Based Composites: Microstructures and Toughening Mechanisms.

Despite the considerable research attention paid to block copolymer (BCP)-toughened epoxy resins, the effects of their terminal groups on their phase structure are not thoroughly understood. This study fills this gap by closely examining the effects of amino and carboxyl groups on the fracture toughness of epoxy resins at different temperatures. Through the combination of scanning electron microscopy and digital image correlation (DIC), it was found that the amino-terminated BCP was capable of forming a stress-distributing network in pure epoxy resin, resulting in better toughening effects at room temperature. In a 60 wt.% silica-filled epoxy composite system, the addition of a carboxyl-terminated BCP showed little toughening effect due to the weaker filler/matrix interface caused by the random dispersion of the microphase of BCPs and distributed silica. The fracture toughness of the epoxy system at high temperatures was not affected by the terminal groups, regardless of the addition of silica. Their dynamic mechanical properties and thermal expansion coefficients are also reported in this article.

Epigenomics in aortic dissection: From mechanism to therapeutics.

Aortic dissection (AD) has an unfavorable prognosis. It requires early diagnosis, appropriate treatment strategies, and suspicion to recognize symptoms; thus, it is commonly described as an acute aortic emergency. The clinical manifestations of painless AD are complex and variable. However, there is no effective treatment to prevent the progression of AD. Therefore, study of the molecular targets and mechanisms of AD to enable prevention or early intervention is particularly important. Although multiple gene mutations have been proposed as linked to AD development, evidence that multiple epigenetic elements are strongly associated is steadily increasing. These epigenetic processes include DNA methylation, N6-methyladenosine, histone modification, non-histone posttranslational modification, and non-coding RNAs (ncRNAs). Among these processes, resveratrol targeting Sirtuin 1 (SIRT1), 5-azacytidine (5azaC) targeting DNA methyltransferase (DNMT), and vitamin C targeting ten-eleven translocation 2 (Tet2) showed unique advantages in improving AD and vascular dysfunction. Finally, we explored potential epigenetic drugs and diagnostic methods for AD, which might provide options for the future.

Advances in volumetric bioprinting.

The three-dimensional (3D) bioprinting technologies are suitable for biomedical applications owing to their ability to manufacture complex and high-precision tissue constructs. However, the slow printing speed of current layer-by-layer (bio)printing modality is the major limitation in biofabrication field. To overcome this issue, volumetric bioprinting (VBP) is developed. VBP changes the layer-wise operation of conventional devices, permitting the creation of geometrically complex, centimeter-scale constructs in tens of seconds. VBP is the next step onward from sequential biofabrication methods, opening new avenues for fast additive manufacturing in the fields of tissue engineering, regenerative medicine, personalized drug testing, and soft robotics, etc. Therefore, this review introduces the printing principles and hardware designs of VBP-based techniques; then focuses on the recent advances in VBP-based (bio)inks and their biomedical applications. Lastly, the current limitations of VBP are discussed together with future direction of research.