Copper Loading-Controlled Selective Synthesis of 2,5-Bis(trifluoromethyl) and Monotrifluoromethyl-Substituted Oxazoles.

A general domino annulation reaction of sulfonylmethyl isocyanide with trifluoroacetic anhydride in the presence of copper chloride as an additive is developed. The reaction affords 2,5-bis(trifluoromethyl)oxazoles in modest to good yields under mild conditions. A wide variety of sulfonylmethyl isocyanide and perfluorocarboxylic anhydride substrates are amenable to this transformation. Under a higher copper salt loading conditions, the reaction led to the formation of monotrifluoromethyl-substituted oxazole product.

Zirconium-Catalyzed Synthesis of 6-(Trifluoromethyl)-2H-pyran-2-ones via C-C Bond Cleavage.

A strategy for the annulation reaction of alkynones with ethyl 4,4,4-trifluoro-3-oxobutanoate through C-C bond cleavage is described. The zirconium-catalyzed transformation provides access to a wide range of structurally diverse 6-(trifluoromethyl)-2H-pyran-2-ones in moderate to good yields, utilizing Na2CO3 as a base. Further transformations into trifluoromethylated arene derivatives have been demonstrated as well. Furthermore, plausible reaction pathways are proposed by conducting various control experiments and isolating a ß-diketone intermediate (X-ray) containing an intramolecular hydrogen bond.

Predictive ability of multi-population genomic prediction methods of phenotypes for reproduction traits in Chinese and Austrian pigs.

BACKGROUND: Multi-population genomic prediction can rapidly expand the size of the reference population and improve genomic prediction ability. Machine learning (ML) algorithms have shown advantages in single-population genomic prediction of phenotypes. However, few studies have explored the effectiveness of ML methods for multi-population genomic prediction. RESULTS: In this study, 3720 Yorkshire pigs from Austria and four breeding farms in China were used, and single-trait genomic best linear unbiased prediction (ST-GBLUP), multitrait GBLUP (MT-GBLUP), Bayesian Horseshoe (BayesHE), and three ML methods (support vector regression (SVR), kernel ridge regression (KRR) and AdaBoost.R2) were compared to explore the optimal method for joint genomic prediction of phenotypes of Chinese and Austrian pigs through 10 replicates of fivefold cross-validation. In this study, we tested the performance of different methods in two scenarios: (i) including only one Austrian population and one Chinese pig population that were genetically linked based on principal component analysis (PCA) (designated as the "two-population scenario") and (ii) adding reference populations that are unrelated based on PCA to the above two populations (designated as the "multi-population scenario"). Our results show that, the use of MT-GBLUP in the two-population scenario resulted in an improvement of 7.1% in predictive ability compared to ST-GBLUP, while the use of SVR and KKR yielded improvements in predictive ability of 4.5 and 5.3%, respectively, compared to MT-GBLUP. SVR and KRR also yielded lower mean square errors (MSE) in most population and trait combinations. In the multi-population scenario, improvements in predictive ability of 29.7, 24.4 and 11.1% were obtained compared to ST-GBLUP when using, respectively, SVR, KRR, and AdaBoost.R2. However, compared to MT-GBLUP, the potential of ML methods to improve predictive ability was not demonstrated. CONCLUSIONS: Our study demonstrates that ML algorithms can achieve better prediction performance than multitrait GBLUP models in multi-population genomic prediction of phenotypes when the populations have similar genetic backgrounds; however, when reference populations that are unrelated based on PCA are added, the ML methods did not show a benefit. When the number of populations increased, only MT-GBLUP improved predictive ability in both validation populations, while the other methods showed improvement in only one population.

Self-delivery photothermal-boosted-nanobike multi-overcoming immune escape by photothermal/chemical/immune synergistic therapy against HCC.

Immune checkpoint inhibitors (ICIs) combined with antiangiogenic therapy have shown encouraging clinical benefits for the treatment of unresectable or metastatic hepatocellular carcinoma (HCC). Nevertheless, therapeutic efficacy and wide clinical applicability remain a challenge due to "cold" tumors' immunological characteristics. Tumor immunosuppressive microenvironment (TIME) continuously natural force for immune escape by extracellular matrix (ECM) infiltration, tumor angiogenesis, and tumor cell proliferation. Herein, we proposed a novel concept by multi-overcoming immune escape to maximize the ICIs combined with antiangiogenic therapy efficacy against HCC. A self-delivery photothermal-boosted-NanoBike (BPSP) composed of black phosphorus (BP) tandem-augmented anti-PD-L1 mAb plus sorafenib (SF) is meticulously constructed as a triple combination therapy strategy. The simplicity of BPSP's composition, with no additional ingredients added, makes it easy to prepare and presents promising marketing opportunities. (1) NIR-II-activated BPSP performs photothermal therapy (PTT) and remodels ECM by depleting collagen I, promoting deep penetration of therapeutics and immune cells. (2) PTT promotes SF release and SF exerts anti-vascular effects and down-regulates PD-L1 via RAS/RAF/ERK pathway inhibition, enhancing the efficacy of anti-PD-L1 mAb in overcoming immune evasion. (3) Anti-PD-L1 mAb block PD1/PD-L1 recognition and PTT-induced ICD initiates effector T cells and increases response rates of PD-L1 mAb. Highly-encapsulated BPSP converted 'cold' tumors into 'hot' ones, improved CTL/Treg ratio, and cured orthotopic HCC tumors in mice. Thus, multi-overcoming immune escape offers new possibilities for advancing immunotherapies, and photothermal/chemical/immune synergistic therapy shows promise in the clinical development of HCC.

Pushing the Limit of Photo-Controlled Polymerization: Hyperchromic and Bathochromic Effects.

The photocatalyst (PC) zinc tetraphenylporphyrin (ZnTPP) is highly efficient for photoinduced electron/energy transfer reversible addition-fragmentation chain transfer (PET-RAFT) polymerization. However, ZnTPP suffers from poor absorbance of orange light by the so-called Q-band of the absorption spectrum (maximum absorption wavelength λmax = 600 nm, at which molar extinction coefficient εmax = 1.0×104 L/(mol·cm)), hindering photo-curing applications that entail long light penetration paths. Over the past decade, there has not been any competing candidate in terms of efficiency, despite a myriad of efforts in PC design. By theoretical evaluation, here we rationally introduce a peripheral benzo moiety on each of the pyrrole rings of ZnTPP, giving zinc tetraphenyl tetrabenzoporphyrin (ZnTPTBP). This modification not only enlarges the conjugation length of the system, but also alters the a1u occupied π molecular orbital energy level and breaks the accidental degeneracy between the a1u and a2u orbitals, which is responsible for the low absorption intensity of the Q-band. As a consequence, not only is there a pronounced hyperchromic and bathochromic effect (λmax = 655 nm and εmax = 5.2×104 L/(mol·cm)) of the Q-band, but the hyperchromic effect is achieved without increasing the intensity of the less useful, low wavelength absorption peaks of the PC. Remarkably, this strong 655 nm absorption takes advantage of deep-red (650-700 nm) light, a major component of solar light exhibiting good atmosphere penetration, exploited by the natural PC chlorophyll a as well. Compared with ZnTPP, ZnTPTBP displayed a 49% increase in PET-RAFT polymerization rate with good control, marking a significant leap in the area of photo-controlled polymerization.

Nomogram for predicting postoperative deep vein thrombosis in patients with spinal fractures caused by high-energy injuries.

OBJECTIVE: Deep venous thrombosis (DVT) is a common complication in patients with spinal fractures caused by high-energy injuries. Early identification of patients at high risk of postoperative DVT is essential for the prevention of thrombosis. This study aimed to develop and validate a prediction model based on a nomogram to predict DVT in patients with spinal fractures caused by high-energy injuries. METHODS: Clinical data were collected from 936 patients admitted to our hospital between January 2016 and December 2021 with spinal fractures caused by high-energy injuries. Multivariate logistic regression analysis was used to identify the risk factors for postoperative DVT and to develop a nomogram. The predictive performance of the nomogram was evaluated by the receiver operating characteristic (ROC) curve and calibration curve. RESULTS: The incidence of preoperative DVT was 15.38% (144/936). The postoperative incidence of DVT was 20.5% (192/936). The multivariate analysis revealed that age, operation time, blood transfusion, duration of bed rest, American Spinal Injury Association (ASIA) score and D-dimer were risk factors for postoperative DVT. The area under the ROC curve of the nomogram was 0.835 and the calibration curve showed good calibration. CONCLUSIONS: The nomogram showed a good ability to predict postoperative DVT in patients with spinal fractures caused by high-energy injuries, which may benefit pre- and postoperative DVT prophylaxis strategy development.

Remarkable Second Harmonic Generation Response in (C5H6NO)+(CH3SO3)-: Unraveling the Role of Hydrogen Bond in Thermal Driven Nonlinear Optical Switch.

Heat-activated second harmonic generation (SHG) switching materials are gaining interest for their ability to switch between SHG on and off states, offering potential in optoelectronic applications. The novel nonlinear optical (NLO) switch, (C5H6NO)+(CH3SO3)- (4-hydroxypyridinium methylsulfonate, 4HPMS), is a near-room-temperature thermal driven material with a strong SHG response (3.3 × KDP), making it one of the most potent heat-stimulated NLO switches. It offers excellent contrast of 13 and a high laser-induced damage threshold (2.5 × KDP), with reversibility > 5 cycles. At 73 °C, 4HPMS transitions from the noncentrosymmetric Pna21 room temperature phase (RTP) to the centrosymmetric P21/c phase, caused by the rotation of the (C5H6NO)+ and (CH3SO3)- due to partially thermal breaking of intermolecular hydrogen bonds. The reverse phase change exhibits a large 50 °C thermal hysteresis. Density functional theory (DFT) calculations show that (C5H6NO)+ primarily dictates both the SHG coefficient (dij) and birefringence (∆n(Zeiss) = 0.216 vs ∆n(cal.) = 0.202 at 546 nm; Δn(Immersion) = 0.210 vs ∆n(cal.) = 0.198 at 589.3 nm), while the band gap (Eg) is influenced synergistically by (C5H6NO)+ and (CH3SO3)-. Additionally, 4HPMS-RTP also exhibits mechanochromism upon grinding as well as an aggregation-enhanced emission in a mixture of acetone and water.

Patellar development after patella instability and early reduction in growing rabbits.

BACKGROUND: Patella-shaped disorder has been considered as a predisposing factor for patella instability. But the influence of early patella reduction for patellar development remains unclear. This study aimed to evaluate whether early operation in patella instability could improve patella morphology in growing rabbits. METHODS: Fifty rabbits (1-month-old) were included in the study. The control group underwent no surgical procedures. The two experimental groups (reduction group and non-reduced group), underwent medial soft tissue restraint release surgery. The reduction group, rabbits underwent the medial soft tissue sutura surgery in order to stabilize the patella 2 months after release surgery. The non-reduced group, rabbits did not undergo suture surgery. Computed Tomography (CT) scans analysis in two experimental endpoints (2, 5 months after release surgery) were selected to evaluate the transverse diameter, thickness, Wiberg index and Wiberg angle. Gross observation was conducted to assess morphological changes of the patella. RESULTS: CT scans showed significant difference in the mean transverse diameter, Wiberg angle between the two experimental groups and the control group 2 months after release surgery. 5 months after release surgery, the indices of patella were found no statistically difference in the reduction group versus the control group. However, the transverse diameter, Wiberg angle in the non-reduced group were significantly differences than that in the reduction group (P < 0.05). Gross observation showed a flattened articular surface of the patella in the non-reduced group. CONCLUSIONS: The results indicated that patella instability may lead to patella-shaped disorder, showing a flattened morphology. Early patella reduction can improve the patella morphology in growing rabbits.

A Novel Approach for Apple Freshness Prediction Based on Gas Sensor Array and Optimized Neural Network.

Apple is an important cash crop in China, and the prediction of its freshness can effectively reduce its storage risk and avoid economic loss. The change in the concentration of odor information such as ethylene, carbon dioxide, and ethanol emitted during apple storage is an important feature to characterize the freshness of apples. In order to accurately predict the freshness level of apples, an electronic nose system based on a gas sensor array and wireless transmission module is designed, and a neural network prediction model using an improved Sparrow Search Algorithm (SSA) based on chaotic sequence (Tent) to optimize Back Propagation (BP) is proposed. The odor information emitted by apples is studied to complete an apple freshness prediction. Furthermore, by fitting the relationship between the prediction coefficient and the input vector, the accuracy benchmark of the prediction model is set, which further improves the prediction accuracy of apple odor information. Compared with the traditional prediction method, the system has the characteristics of simple operation, low cost, reliable results, mobile portability, and it avoids the damage to apples in the process of freshness prediction to realize non-destructive testing.

Synthesis of 2,3-Bis(trifluoromethylseleno) Indoles through an Oxidative Copper-Mediated Domino Reaction.

An oxidative copper-mediated double trifluoromethylselenolation of terminal 2-alkynylanilines using [(bpy)CuSeCF3]2 is reported, providing a moderately efficient and convenient approach to 2,3-bis(trifluoromethylseleno)indoles. Mechanistic studies show that a cascade sequence of oxidation, trifluoromethylselenolation, 5-endo-dig cyclization, and elimination is involved in this transformation.

Estimation of Soil Organic Matter in Arid Zones with Coupled Environmental Variables and Spectral Features.

The soil organic matter (SOM) content is a key factor affecting the function and health of soil ecosystems. For measurements of land reclamation and soil fertility, SOM monitoring using visible and near-infrared spectroscopy (Vis-NIR) is one approach to quantifying soil quality, and Vis-NIR is important for monitoring the SOM content in a broad and nondestructive manner. To investigate the influence of environmental factors and Vis-NIR spectroscopy in estimating SOM, 249 soil samples were collected from the Werigan-Kuqa oasis in Xinjiang, China, and their spectral reflectance, SOM content and soil salinity were measured. To classify and improve the prediction accuracy, we also take into account the soil salinity content as a variable indicator. Relevant environmental variables were extracted using remote sensing datasets (land-use/land-cover (LULC), digital elevation model (DEM), World Reference Base for Soil Resources (WRB), and soil texture). On the basis of Savitzky-Golay (S-G) smoothing and first derivative (FD) preprocessing of the original spectrum, three clusters were obtained by K-means clustering through the use of Vis-NIR and used as spectral classification variables. Using Vis-NIR as Model 1, Vis-NIR combined with spectral classification as Model 2, environmental variables as Model 3, and the combination of all the above variables (Vis-NIR, spectral classification, environmental variables, and soil salinity) as Model 4, a SOM content estimation model was constructed using partial least squares regression (PLSR). Using the 249 soil samples, the modeling set contained 166 samples and the validation set contained 83 samples. The results showed that Model 2 (validation r2 = 0.78) was better than Model 1 (validation r2 = 0.76). The prediction accuracy for Model 4 (validation r2 = 0.85) was better than Model 2 (validation r2 = 0.78). Among these, Model 3 was the worst (validation r2 = 0.39). Therefore, the combination of environmental variables with Vis-NIR spectroscopy to estimate SOM content is an important method and has important implications for improving the accuracy of SOM predictions in arid regions.

Regioselective Synthesis of 5-Trifluoromethyl 1,2,4-Triazoles via [3 + 2]-Cycloaddition of Nitrile Imines with CF3CN.

We herein describe a general approach to 5-trifluoromethyl 1,2,4-triazoles via the [3 + 2]-cycloaddition of nitrile imines generated in situ from hydrazonyl chloride with CF3CN, utilizing 2,2,2-trifluoroacetaldehyde O-(aryl)oxime as the precursor of trifluoroacetonitrile. Various functional groups, including alkyl-substituted hydrazonyl chloride, were tolerated during cycloaddition. Furthermore, the gram-scale synthesis and common downstream transformations proved the potential synthetic relevance of this developed methodology.

Assessing Soil Organic Matter Content in a Coal Mining Area through Spectral Variables of Different Numbers of Dimensions.

Soil organic matter (SOM) is a crucial indicator for evaluating soil quality and an important component of soil carbon pools, which play a vital role in terrestrial ecosystems. Rapid, non-destructive and accurate monitoring of SOM content is of great significance for the environmental management and ecological restoration of mining areas. Visible-near-infrared (Vis-NIR) spectroscopy has proven its applicability in estimating SOM over the years. In this study, 168 soil samples were collected from the Zhundong coal field of Xinjiang Province, Northwest China. The SOM content (g kg-1) was determined by the potassium dichromate external heating method and the soil reflectance spectra were measured by the spectrometer. Two spectral feature extraction strategies, namely, principal component analysis (PCA) and the optimal band combination algorithm, were introduced to choose spectral variables. Linear models and random forests (RF) were used for predictive models. The coefficient of determination (R2), root mean square error (RMSE), and the ratio of the performance to the interquartile distance (RPIQ) were used to evaluate the predictive performance of the model. The results indicated that the variables (2DI and 3DI) derived from the optimal band combination algorithm outperformed the PCA variables (1DV) regardless of whether linear or RF models were used. An inherent gap exists between 2DI and 3DI, and the performance of 2DI is significantly poorer than that of 3DI. The accuracy of the prediction model increases with the increasing number of spectral variable dimensions (in the following order: 1DV < 2DI < 3DI). This study proves that the 3DI is the first choice for the optimal band combination algorithm to derive sensitive parameters related to SOM in the coal mining area. Furthermore, the optimal band combination algorithm can be applied to hyperspectral or multispectral images and to convert the spectral response into image pixels, which may be helpful for a soil property spatial distribution map.

ALDH1A1 Inhibits Chicken Preadipocytes' Proliferation and Differentiation via the PPARγ Pathway In Vitro and In Vivo.

ALDH1A1 (aldehyde dehydrogenase 1A1) is a crucial protein in retinoids' metabolism, and the lack of ALDH1A1 inhibits the fat deposition in mice. However, whether ALDH1A1 has a similar effect on chickens' fat-depot is still unknown. In this study, we investigate the role of ALDH1A1 in chickens' adipogenesis. The immortalized chicken preadipocyte 1 (ICP1) cell line and chicken primary preadipocytes isolated from abdominal fat were used to perform a series of experiments in vitro to elucidate the effects of ALDH1A1. In addition, lentivirus was used to verify the results of cell experiments in vivo. The data showed that overexpression of ALDH1A1 significantly weakened the proliferation of preadipocytes and suppressed the differentiation of preadipocytes through the PPARγ pathway, and the knockdown experiments had the opposite results. Moreover, chickens injected with overexpression lentivirus had higher abdominal fat percentage, a bigger size of lipid droplets, and higher triglyceride content in abdominal fat, and chickens injected with interfering lentivirus had the opposite situation. We proved that ALDH1A1 not only inhibited the proliferation and differentiation of chickens' preadipocytes in vitro, but also inhibited the fat-depot of chickens in vivo, which was completely opposite the function of ALDH1A1 in mice, indicating that ALDH1A1 may have a different mechanism that is still unknown.

Evaluating the effectiveness of a disaster preparedness nursing education program in Chengdu, China.

OBJECTIVE: To develop and evaluate a disaster nursing preparedness training program to improve nursing students' ability in disaster fundamentals, triage, and family preparedness when facing a disaster. DESIGN AND SAMPLE: An experimental study was applied using a pretest and post-test control group design. Participants were randomly assigned to the experimental (n = 31) and control (n = 32) groups. MEASURES: The program lasted 7 hr. All participants completed structured questionnaires at three time points. Results were compared between the two groups using Mann-Whitney U tests. Outcome measures were knowledge, skill, and attitude. RESULTS: Students receiving the program displayed greater increases in knowledge and skills related to disaster preparedness than those in the control group. One month after the intervention, the experimental group still had significantly higher levels of disaster knowledge and skill than the control group. There were no statistically significant differences over time in attitude measures. CONCLUSIONS: This program enhanced students' ability and the findings can serve as a basis for further developing public health education for all nurses. Chinese leaders of public health institutions and nursing administrators can create guidelines for PHN competencies and prepare the public health nursing workforce to be effective in disaster, preparedness, response, and recovery.

Distribution characteristics of perioperative deep vein thrombosis (DVT) and risk factors of postoperative DVT exacerbation in patients with thoracolumbar fractures caused by high-energy injuries.

OBJECTIVE: To investigate the distribution characteristics of perioperative deep venous thrombosis (DVT) in patients with thoracolumbar fractures caused by high-energy injuries and analyze the risk factors of postoperative DVT exacerbation. METHODS: From October 2016 to July 2021, a total of 550 patients with thoracolumbar fractures due to high-energy injuries in our hospital were retrospectively analyzed. Both lower limbs were examined by ultrasound before and after operation. Depending on whether the postoperative DVT was exacerbating, the group was divided into a DVT exacerbation group and a non-DVT exacerbation group. Clinical data were used to study the characteristics of perioperative DVT. Logistic regression analysis and receiver operating characteristic (ROC) curve were used to explore the risk factors of postoperative DVT exacerbation. RESULTS: DVT was found in 97 patients before operation, including 78 cases of distal thrombus, 6 cases of proximal thrombus, and 13 cases of mixed thrombus. Postoperative DVT increased to 116, including 87 distal thrombus, 10 proximal thrombus, and 19 mixed thrombus. The intermuscular vein was the most easily involved vein. Compared with lumbar fractures, thoracic fractures were more likely to have postoperative proximal thrombus (P=0.014). There were 48 cases of thrombus exacerbation after operation. Logistic regression analysis revealed that age, lower extremity muscle strength, time from injury to operation, and blood loss were risk factors for postoperative DVT exacerbation. CONCLUSIONS: The intermuscular vein is the most easily involved vein. The anatomical distribution of DVT at different fracture sites is different, and patients with thoracic fractures are more likely to have proximal DVT after operation. Age, lower extremity muscle strength, time from injury to operation, and blood loss were risk factors for postoperative DVT exacerbation.

Influence of surface water and groundwater on functional traits and trade-off strategies of oasis communities at the end of the Keriya River, China.

Plant functional traits reflect the capacity of plants to adapt to their environment and the underlying optimization mechanisms. However, few studies have investigated trade-off strategies for functional traits in desert-wetland ecosystems, the mechanisms by which surface water disturbance and groundwater depth drive functional trait variation at the community scale, and the roles of intraspecific and interspecific variation. Therefore, this study analyzed specific differences in community-weighted mean traits among habitat types and obtained the relative contribution of intraspecific and interspecific variation by decomposing community-weighted mean traits, focusing on the Daliyabuyi Oasis in the hinterland of the Taklamakan Desert. We also explored the mechanisms by which surface water and groundwater influence different sources of variability specifically. The results showed that plant height, relative chlorophyll content, leaf thickness, leaf nitrogen content, and nitrogen-phosphorus ratio were the key traits reflecting habitat differences. As the groundwater depth becomes shallower and surface water disturbance intensifies, plant communities tend to have higher leaf nitrogen content, nitrogen-phosphorus ratio, and relative chlorophyll content and lower height. Surface water, groundwater, soil water content, and total soil nitrogen can influence interspecific and intraspecific variation in these traits through direct and indirect effects. As arid to wet habitats change, plant trade-off strategies for resources will shift from conservative to acquisitive. The study concluded that community functional traits are mainly contributed by interspecific variation, but consideration of intraspecific variation and the covariation effects that exist between it and interspecific variation can help to further enhance the understanding of the response of community traits in desert-wetland ecosystems to environmental change. Surface water disturbance has a non-negligible contribution to this adaptation process and plays a higher role than groundwater depth.

A Polymer Nanocomposite with Strong Full-Spectrum Solar Absorption and Infrared Emission for All-Day Thermal Energy Management and Conversion.

Realizing efficient energy utilization from the heat source of the sun and the cold source of outer space is of great significance for addressing the global energy and environmental crisis. Materials with ideal full-spectrum solar absorption and infrared emission are highly desirable for adapting to the continuous weather dynamic throughout the day, nonetheless, their development remains challenging. Here, a polymer nanocomposite with full-spectrum strong solar (280-2500 nm) absorption ranging from 88.8% to 94.8% with an average value of 93.2% and full-spectrum high infrared (8-13 µm) emission ranging from 81.3% to 90.0% with an average value of 84.2%, is reported by melt-processing polypropylene and uniformly dispersed low-loading MXene nanosheets (1.9 vol%). The nanocomposite can achieve daytime photothermal enhancement of ≈50 °C and nighttime radiative cooling of 8 °C. The temperature difference throughout the day ensures all-day uninterrupted thermoelectric generation, yielding a power density output of 1.5 W m-2 (daytime) and 7.9 mW m-2 (nighttime) in real outdoor environment without any additional energy consumption. This work provides an impressive polymer nanocomposite with ideal full-spectrum solar absorption and infrared emission for all-day uninterrupted thermal energy management and conversion.

A comprehensive study of the colloidal properties, biocompatibility, and synergistic antioxidant actions of Antarctic krill phospholipids.

Excipient selection is crucial to address the oxidation and solubility challenges of bioactive substances, impacting their safety and efficacy. AKPL, a novel ω-3 polyunsaturated fatty acids (PUFAs) esterified phospholipid derived from Antarctic krill, demonstrates unique antioxidant capabilities and synergistic effects. It exhibits pronounced surface activity and electronegativity at physiological pH, as evidenced by a critical micelle concentration (CMC) of 0.15 g/L and ζ-potential of -49.9 mV. In aqueous environments, AKPL self-assembles into liposomal structures, offering high biocompatibility and promoting cell proliferation. Its polyunsaturated bond-rich structure provides additional oxidation sites, imparting antioxidant properties superior to other phospholipids like DSPC and DOPC. Additionally, AKPL augments the efficacy of lipophilic antioxidants, such as alpha-tocopherol and curcumin, in aqueous media through both intermolecular and intramolecular interactions. In sum, AKPL emerges as an innovative unsaturated phospholipid, offering new strategies for encapsulating and delivering oxygen-sensitive agents.

Biomimetic Superhydrophobic Materials through 3D Printing: Progress and Challenges.

Superhydrophobicity, a unique natural phenomenon observed in organisms such as lotus leaves and desert beetles, has inspired extensive research on biomimetic materials. Two main superhydrophobic effects have been identified: the "lotus leaf effect" and the "rose petal effect", both showing water contact angles larger than 150°, but with differing contact angle hysteresis values. In recent years, numerous strategies have been developed to fabricate superhydrophobic materials, among which 3D printing has garnered significant attention due to its rapid, low-cost, and precise construction of complex materials in a facile way. In this minireview, we provide a comprehensive overview of biomimetic superhydrophobic materials fabricated through 3D printing, focusing on wetting regimes, fabrication techniques, including printing of diverse micro/nanostructures, post-modification, and bulk material printing, and applications ranging from liquid manipulation and oil/water separation to drag reduction. Additionally, we discuss the challenges and future research directions in this burgeoning field.