Covered Stent Treatment for Direct Carotid-Cavernous Fistulas: A Meta-analysis of Efficacy and Safety Outcomes.

BACKGROUND: Direct carotid-cavernous fistulas (dCCFs) involve the abnormal shunting of blood between the internal carotid artery and the cavernous sinus. The use of covered stents (CSs) has been reported for the treatment of complex carotid artery lesions. However, the efficacy and safety of CS treatment for dCCFs remain controversial. Thus, we performed a systematic review and meta-analysis to evaluate these efficacy and safety endpoints. METHODS: A systematic literature review was performed by comprehensively searching the Medline, Embase, and Web of Science databases to identify studies that were related to CS treatment for dCCFs. Then, a meta-analysis was conducted to pool the efficacy and safety outcomes from these studies based on perioperative and follow-up data. RESULTS: Fourteen non-comparative studies enrolling 156 patients with 160 dCCFs met the inclusion criteria. When analyzing perioperative outcomes, the technical success rate was 98.5% [95% confidence interval (CI), 0.948, 1.000], and the immediate complete occlusion rate was 90.9% (95% CI, 0.862, 0.959). Vasospasm and dissection occurred in 32.2% (95% CI, 0.238, 0.463) and 0.1% (95% CI, 0.000, 0.012) of patients, respectively. The in-stent acute thrombus formation rate was 0.1% (95% CI, 0.000; 0.013). Postoperatively, the mortality rate was 0.1% (95% CI, 0.000, 0.013). Based on available follow-up data, the final complete occlusion and parent artery stenosis rates were 99.3% (95% CI, 0.959, 1.000) and 18.6% (95% CI, 0.125, 0.277), respectively. CONCLUSIONS: CS placement can be used to safely and effectively treat dCCFs. These results provide a reference for future clinical trials.

Nitric Oxide-Releasing Porous Coating with Antibacterial Activity and Blood Compatibility.

Nitric oxide (NO)-releasing coating is promising to enhance the biocompatibility of medical devices. In this study, polyurethane (PU) and S-nitrosated keratin (KSNO) were dissolved with dimethyl sulfoxide (DMSO) and tetrahydrofuran (THF) to prepare a coating solution. This solution is facile to form a porous coating on various substrates based on solvent-evaporation-induced phase separation (SEIPS). The coating could continuously release NO up to 200 h in the presence of ascorbic acid (Asc). In addition, the coating could accelerate endothelialization by promoting the viability of human umbilical vein endothelial cells (HUVECs) while inhibiting the proliferation of human umbilical artery smooth muscle cells (HUASMCs). Furthermore, the coating had good antibacterial activity and blood compatibility. Taken together, this universal coating provides wider potential applications in the field of cardiovascular implants.

LVONet: automatic classification model for large vessel occlusion based on the difference information between left and right hemispheres.

Objective.Stroke is a highly lethal condition, with intracranial vessel occlusion being one of its primary causes. Intracranial vessel occlusion can typically be categorized into four types, each requiring different intervention measures. Therefore, the automatic and accurate classification of intracranial vessel occlusions holds significant clinical importance for assessing vessel occlusion conditions. However, due to the visual similarities in shape and size among different vessels and variations in the degree of vessel occlusion, the automated classification of intracranial vessel occlusions remains a challenging task. Our study proposes an automatic classification model for large vessel occlusion (LVO) based on the difference information between the left and right hemispheres.Approach.Our approach is as follows. We first introduce a dual-branch attention module to learn long-range dependencies through spatial and channel attention, guiding the model to focus on vessel-specific features. Subsequently, based on the symmetry of vessel distribution, we design a differential information classification module to dynamically learn and fuse the differential information of vessel features between the two hemispheres, enhancing the sensitivity of the classification model to occluded vessels. To optimize the feature differential information among similar vessels, we further propose a novel cooperative learning loss function to minimize changes within classes and similarities between classes.Main results.We evaluate our proposed model on an intracranial LVO data set. Compared to state-of-the-art deep learning models, our model performs optimally, achieving a classification sensitivity of 93.73%, precision of 83.33%, accuracy of 89.91% and Macro-F1 score of 87.13%.Significance.This method can adaptively focus on occluded vessel regions and effectively train in scenarios with high inter-class similarity and intra-class variability, thereby improving the performance of LVO classification.

Pilocarpine HCl 1.25% for treatment of presbyopia after laser vision correction: pooled analysis of two phase 3 randomized trials (GEMINI 1 and 2).

PURPOSE: To evaluate the efficacy of topical pilocarpine HCl 1.25% (Pilo) in treating presbyopia in individuals with or without a history of laser vision correction (laser-assisted in situ keratomileusis [LASIK] or photorefractive keratectomy [PRK]). SETTING: Multiple clinical sites. DESIGN: Pooled analysis of 2 identically designed prospective, randomized, vehicle-controlled studies (GEMINI 1 and 2). METHODS: Adults aged 40 to 55 years with presbyopia received once-daily Pilo or vehicle bilaterally for 30 days. Responder rates for ≥3-line improvement in mesopic, high-contrast, binocular distance-corrected near visual acuity (DCNVA) were determined on day 30. RESULTS: Among participants with a history of LASIK/PRK (n = 39 in the Pilo group, n = 41 in the vehicle group), responder rates for ≥3-line improvement in DCNVA on day 30 at hours 0.25, 0.5, 1, 3, 6, 8, and 10, respectively, were 16.7%, 38.9%, 41.7%, 37.8%, 16.2%, 13.9%, and 8.3% with Pilo and 0.0%, 2.6%, 10.5%, 5.1%, 7.7%, 2.6%, and 0.0% with vehicle. Responder rates in the LASIK/PRK subgroup were significantly higher with Pilo than vehicle at hours 0.25 ( P = .0087), 0.5 ( P = .0001), 1 ( P = .0022), and 3 ( P = .0005). In contrast, there were no significant differences in responder rates between Pilo-treated participants with and without LASIK/PRK. Among non-LASIK/PRK participants in the Pilo group (n = 336), responder rates for ≥3-line improvement in DCNVA on day 30 at hours 0.25, 0.5, 1, 3, 6, 8, and 10, respectively, were 16.8%, 32.7%, 39.0%, 28.0%, 17.4%, 12.6%, and 10.5%. CONCLUSIONS: Pilo treatment effectively and similarly improved DCNVA in presbyopes with or without a history of laser vision correction.

Endothelium-Mimicking Bilayer Vascular Grafts with Dual-Releasing of NO/H2S for Anti-Inflammation and Anticalcification.

Vascular complications caused by diabetes impair the activities of endothelial nitric oxide synthase (eNOS) and cystathionine γ-lyase (CSE), resulting in decreased physiological levels of nitric oxide (NO) and hydrogen sulfide (H2S). The low bioavailability of NO and H2S hinders the endothelialization of vascular grafts. In this study, endothelium-mimicking bilayer vascular grafts were designed with spatiotemporally controlled dual releases of NO and H2S for in situ endothelialization and angiogenesis. Keratin-based H2S donor was synthesized and electrospun with poly(l-lactide-co-ε-caprolactone) (PLCL) as the outer layer of the graft to release H2S. Hyaluronic acid, one of the major glycosaminoglycans in endothelial glycocalyx, was complexed with Cu ions as the inner layer to mimic glutathione peroxidase (GPx) and maintain long-term physiological NO flux. The synergistic effects of NO and H2S of bilayer grafts selectively promoted the regeneration and migration of human umbilical vascular endothelial cells (HUVECs), while inhibiting the overproliferation of human umbilical artery smooth muscle cells (HUASMCs). Bilayer grafts could effectively prevent vascular calcification, reduce inflammation, and alleviate endothelial dysfunction. The in vivo study in a rat abdominal aorta replacement model for 1 month showed that the graft had a good patency rate and had potential for vascular remodeling in situ.

Field Measurement and Analysis on the Mechanical Response of Asphalt Pavement Using Large-Particle-Size Crushed Stone Base Treated with Fly Ash and Slag Powder.

The mechanical response of asphalt pavement under vehicular loading is an essential reference for crack-resistant pavement design. However, limited research focuses on the mechanical response measurement of asphalt pavement using a large-particle-size crushed stone base treated with fly ash and slag powder. Therefore, two types of asphalt pavements were constructed. The first type of asphalt pavement uses a large-particle-size crushed stone base treated with fly ash and slag powder, where the slag powder uses granulated blast furnace slag powder. The second type uses a conventional cement-stabilized crushed stone base and serves as a reference structure. Firstly, the strain gauges and temperature sensors were installed during the construction of asphalt pavements. Secondly, the mechanical response of the pavement was tested at different speeds and service time conditions. Then, sensitivity analysis and three-factor analysis of variance (ANOVA) were carried out. Finally, the prediction equations were developed. The results show that the longitudinal strain pulse of the asphalt layer exhibited a "compression-tension-compression" characteristic. For the transverse strain pulse of the asphalt layer, the base layer's transverse and longitudinal strain pulses were only shown as "tensile" characteristics. The vehicular speed significantly affected the strain values for the base and asphalt layers, showing a decreasing trend with increasing speed. For the asphalt layer, the strain values showed an increasing trend with increasing temperature; for the base layer, the strain values showed a decreasing trend with increasing service time. The type of base layer had a significant effect on the strain value. Compared with the conventional base layer, the large-particle-size crushed stone base treated with fly ash and slag powder had lower strain at the base layer and a lower position of the asphalt layer, which could better prevent bottom-up fatigue cracking. Finally, the strain prediction model of the pavement under the speed and temperature (service time) was fitted to obtain a model that can predict the mechanical response of the pavement under different operating conditions. The findings of this research can provide a reference for the design of asphalt pavement using a large-particle-size crushed stone base treated with fly ash and slag powder.

Feasibility and effectiveness of automatic deep learning network and radiomics models for differentiating tumor stroma ratio in pancreatic ductal adenocarcinoma.

OBJECTIVE: This study aims to compare the feasibility and effectiveness of automatic deep learning network and radiomics models in differentiating low tumor stroma ratio (TSR) from high TSR in pancreatic ductal adenocarcinoma (PDAC). METHODS: A retrospective analysis was conducted on a total of 207 PDAC patients from three centers (training cohort: n = 160; test cohort: n = 47). TSR was assessed on hematoxylin and eosin-stained specimens by experienced pathologists and divided as low TSR and high TSR. Deep learning and radiomics models were developed including ShuffulNetV2, Xception, MobileNetV3, ResNet18, support vector machine (SVM), k-nearest neighbor (KNN), random forest (RF), and logistic regression (LR). Additionally, the clinical models were constructed through univariate and multivariate logistic regression. Kaplan-Meier survival analysis and log-rank tests were conducted to compare the overall survival time between different TSR groups. RESULTS: To differentiate low TSR from high TSR, the deep learning models based on ShuffulNetV2, Xception, MobileNetV3, and ResNet18 achieved AUCs of 0.846, 0.924, 0.930, and 0.941, respectively, outperforming the radiomics models based on SVM, KNN, RF, and LR with AUCs of 0.739, 0.717, 0.763, and 0.756, respectively. Resnet 18 achieved the best predictive performance. The clinical model based on T stage alone performed worse than deep learning models and radiomics models. The survival analysis based on 142 of the 207 patients demonstrated that patients with low TSR had longer overall survival. CONCLUSIONS: Deep learning models demonstrate feasibility and superiority over radiomics in differentiating TSR in PDAC. The tumor stroma ratio in the PDAC microenvironment plays a significant role in determining prognosis. CRITICAL RELEVANCE STATEMENT: The objective was to compare the feasibility and effectiveness of automatic deep learning networks and radiomics models in identifying the tumor-stroma ratio in pancreatic ductal adenocarcinoma. Our findings demonstrate deep learning models exhibited superior performance compared to traditional radiomics models. KEY POINTS: • Deep learning demonstrates better performance than radiomics in differentiating tumor-stroma ratio in pancreatic ductal adenocarcinoma. • The tumor-stroma ratio in the pancreatic ductal adenocarcinoma microenvironment plays a protective role in prognosis. • Preoperative prediction of tumor-stroma ratio contributes to clinical decision-making and guiding precise medicine.

Recent advances in keratin for biomedical applications.

The development of keratin-based biomaterials provides an approach to addressing related environmental pollutants and turns waste into wealth. Keratin possesses various merits, such as biocompatibility, biodegradability, hemostasis, non-immunogenicity, antibacterial activity, antioxidation, multi-responsiveness, and abundance in nature. Additionally, keratin biomaterials have been extensively employed in various biomedical applications such as drug delivery, wound healing, and tissue engineering. This review focuses on the properties and biomedical applications of keratin biomaterials. It is anticipated to provide valuable insights for the research and development of keratin biomaterials.

Comparison of ecosystem health in different geomorphic regions of Chishui River Basin, Southwest China.

Ecosystem health of the Chishui River Basin (CRB, a crucial ecological barrier in the upper reaches of the Yangtze River) is vital for the ecological security and sustainability of the Yangtze River Basin. We used RUSLE model, SWAT model, Fragstats and geographic detectors to construct a theoretical framework of ecosystem health assessment for CRB, and examined the spatiotemporal variations and driving factors of ecosystem health in CRB under ecological restoration from 2010 to 2020. The results showed that ecosystem service in the CRB decreased and then increased during 2010-2020 and the overall trend was downward. The overall ecosystem service function was higher in the Danxia (non-karst) area than that in the karst area. The ecosystem health was generally subhealthy, with the Danxia area being mostly extremely healthy and healthy, whereas the karst area mostly subhealthy and unhealthy. There were differences in the dominant drivers of ecosystem health between karst and Danxia areas. Vegetation, precipitation, and bedrock bareness rate were the dominant drivers in the karst area, while vegetation, land use, and precipitation were the dominant factors in Danxia area. After interaction detection, the explanatory power of impact factors increased, and the dominant interaction factor combinations in different geomorphological type regions had shown great differences. Among them, precipitation∩normalized difference vegetation index (NDVI), precipitation∩digital elevation model (DEM) and precipitation ∩ bedrock bareness rate were the dominant interaction factor combinations in the karst area, and NDVI∩precipitation, NDVI∩land use and NDVI∩DEM were the dominant interaction factor combinations in Danxia area. These results would provide scientific support for health maintenance and conservation of CRB ecosystem.

Hydrogen sulfide releasing poly(γ-glutamic acid) biocomposite hydrogel with monitoring, antioxidant, and antibacterial properties for diabetic wound healing.

Adverse factors such as high levels of glucose, oxidative stress, inflammation, and bacterial infection impede diabetic wound healing and even worsen wounds. Owing to its outstanding anti-inflammatory and antioxidant properties as well as the potential to promote cell migration and proliferation, hydrogen sulfide(H2S) gas therapy is promising for chronic diabetic wound recovery. In this work, a multifunctional poly(γ-glutamic acid)(PGA) hydrogel encapsulated with keratin-based H2S donor(KTC), ciprofloxacin(Cip), and anthocyanins(Ant) was developed. The resultant hydrogel was capable of releasing H2S, thereby promoting cell proliferation and enhancing anti-inflammation and antioxidant activity. The release of antibiotic Cip was accelerated under a diabetic wound microenvironment, thereby enhancing the antibacterial activity of the hydrogel. The encapsulated Ant could serve as a pH monitor, sensitively indicating wound pH conditions in situ and indirectly reflecting wound infection. In vivo results in diabetic wound healing suggested that PGA/Ant/KTC/Cip hydrogel reduced inflammation and promoted angiogenesis and collagen deposition, thereby accelerating wound healing.

Yolk-Shell and Hollow Zr/Ce-UiO-66 for Manipulating Selectivity in Tandem Reactions and Photoreactions.

One of the hallmarks of multicomponent metal-organic frameworks (MOFs) is to finely tune their active centers to achieve product selectivity. In particular, obtaining bimetallic MOF hollow structures with precisely tailored redox centers under the same topology is still challenging despite a recent surge of such efforts. Herein, we present an engineering strategy named "cluster labilization" to generate hierarchically porous MOF composites with hollow structures and tunable active centers. By partially replacing zirconium with cerium in the hexanuclear clusters of UiO-66, unevenly distributed yolk-shell structures (YSS) were formed. Through acid treatment or annealing of the YSS precursor, single-shell hollow structures (SSHS) or double-shell hollow structures (DSHS) can be obtained, respectively. The active centers in SSHS and DSHS differ in their species, valence, and spatial locations. More importantly, YSS, SSHS, and DSHS with distinct active centers and microenvironments exhibit tunable catalytic activity, reversed selectivity, and high stability in the tandem reaction and the photoreaction.

Rapamycin reverses ferroptosis by increasing autophagy in MPTP/MPP+-induced models of Parkinson's disease.

Parkinson's disease is a neurodegenerative disorder, and ferroptosis plays a significant role in the pathological mechanism underlying Parkinson's disease. Rapamycin, an autophagy inducer, has been shown to have neuroprotective effects in Parkinson's disease. However, the link between rapamycin and ferroptosis in Parkinson's disease is not entirely clear. In this study, rapamycin was administered to a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced Parkinson's disease mouse model and a 1-methyl-4-phenylpyridinium-induced Parkinson's disease PC12 cell model. The results showed that rapamycin improved the behavioral symptoms of Parkinson's disease model mice, reduced the loss of dopamine neurons in the substantia nigra pars compacta, and reduced the expression of ferroptosis-related indicators (glutathione peroxidase 4, recombinant solute carrier family 7, member 11, glutathione, malondialdehyde, and reactive oxygen species). In the Parkinson's disease cell model, rapamycin improved cell viability and reduced ferroptosis. The neuroprotective effect of rapamycin was attenuated by a ferroptosis inducer (methyl (1S,3R)-2-(2-chloroacetyl)-1-(4-methoxycarbonylphenyl)-1,3,4,9-tetrahyyridoindole-3-carboxylate) and an autophagy inhibitor (3-methyladenine). Inhibiting ferroptosis by activating autophagy may be an important mechanism by which rapamycin exerts its neuroprotective effects. Therefore, the regulation of ferroptosis and autophagy may provide a therapeutic target for drug treatments in Parkinson's disease.

SFF-Siam: A New Oracle Bone Rejoining Method Based on Siamese Network.

The rejoining of oracle bone rubbings is a fundamental topic in oracle bone inscriptions (OBIs) research. However, the traditional oracle bone (OB) rejoining methods are not only time-consuming and laborious but difficult to apply to large-scale OB rejoining. We proposed a simple OB rejoining model (SFF-Siam) to handle this challenge. First, the similarity feature fusion (SFF) module is designed to combine two inputs and make them relate to each other, then a backbone feature extraction network is used to evaluate the similarity between inputs, and the forward feedback network outputs the probability that two OB fragments can be rejoined. Extensive experiments demonstrate that the SFF-Siam achieved a good effect in OB rejoining. The average accuracy of the SFF-Siam network reached 96.4% and 90.1% in our benchmark datasets, respectively. It provides valuable data for promoting the use of OBIs in conjunction with AI technology.

Modeling the Enzyme Specificity by Molecular Cages through Regulating Reactive Oxygen Species Evolution.

Mimicking the active site and the substrate binding cavity of the enzyme to achieve specificity in catalytic reactions is an essential challenge. Herein, porous coordination cages (PCCs) with intrinsic cavities and tunable metal centers have proved the regulation of reactive oxygen species (ROS) generating pathways as evidenced by multiple photo-induced oxidations. Remarkably, in the presence of the Zn4 -µ4 -O center, PCC converted dioxygen molecules from triplet to singlet excitons, whereas the Ni4 -µ4 -O center promoted the efficient dissociation of electrons and holes to conduct electron transfer towards substrates. Accordingly, the distinct ROS generation behavior of PCC-6-Zn and PCC-6-Ni enables the conversion of O2 to 1 O2 and O2 ⋅- , respectively. In contrast, the Co4 -µ4 -O center combined the 1 O2 and O2 ⋅- together to generate carbonyl radicals, which in turn reacted with the oxygen molecules. Harnessing the three oxygen activation pathways, PCC-6-M (M=Zn/Ni/Co) display specific catalytic activities in thioanisole oxidation (PCC-6-Zn), benzylamine coupling (PCC-6-Ni), and aldehyde autoxidation (PCC-6-Co). This work not only provides fundamental insights into the regulation of ROS generation by a supramolecular catalyst but also demonstrates a rare example of achieving reaction specificity through mimicking natural enzymes by PCCs.

Chlorhexidine-loaded polysulfobetaine/keratin hydrogels with antioxidant and antibacterial activity for infected wound healing.

Multifunctional hydrogel dressings are promising for wound healing. In the study, chlorhexidine(CHX) loaded double network hydrogels were prepared by free radical polymerization of sulfobetaine and oxidative self-crosslinking of reduced keratin. The introduced keratin and CHX endowed hydrogels with cytocompatibility, antioxidant capability as well as enhanced antibacterial activity due to the antifouling property of polysulfobetaine. These hydrogels exhibited acidity, glutathione(GSH), and trypsin triple-responsive release behaviors, resulting in the accelerated release of CHX under wound microenvironments. Intriguingly, the freeze-drying hydrogels could be ground to powders and sprinkled on the irregular wound bed, followed by absorbing wound fluid to reform hydrogel in situ. These xerogel powders were more convenient for sterilization, formulation, and storage. Further, these xerogel powders could be rejected after being mixed with an appropriate amount of water. In vivo infected wound healing confirmed that the xerogel powder dressing significantly promoted collagen deposition and reduced inflammation, thereby accelerating the closure and regeneration of skin wounds. Taken together, these degradable xerogel powders have great potential applications for wound healing.

Multiresponsive Keratin-Polysulfobetaine Conjugate-Based Micelles as Drug Carriers with a Prolonged Circulation Time.

A protein-polymer conjugate combines the chemical properties of a synthetic polymer chain with the biological properties of a protein. In this study, the initiator terminated with furan-protected maleimide was first synthesized through three steps. Then, a series of zwitterionic poly[3-dimethyl(methacryloyloxyethyl)ammonium propanesulfonate] (PDMAPS) was synthesized via atom transfer radical polymerization (ATRP) and optimized. Subsequently, well-controlled PDMAPS was conjugated with keratin via thiol-maleimide Michael addition. The keratin-PDMAPS conjugate (KP) could self-assemble in an aqueous solution to form micelles with low critical micelle concentration (CMC) values and good blood compatibility. The drug-loaded micelles exhibited triple responsiveness to pH, glutathione (GSH), and trypsin under tumor microenvironments. In addition, these micelles showed high toxicity against A549 cells while low toxicity on normal cells. Furthermore, these micelles performed prolonged blood circulation.

Rainstorm sediment events in heterogeneous karst small watersheds: Process characteristics, prediction modeling and management enlightenment.

Frequent rainstorms caused by climate change are causing significant stresses and impacts on karst zones and even global hydrological systems. However, few reports have focused on rainstorm sediment events (RSE) based on long series, high-frequency signals in karst small watersheds. Present study assessed the process characteristics of RSE and analyzed the response of specific sediment yield (SSY) to environmental variables using random forest and correlation coefficients. Management strategies are then provided based on revised index of sediment connectivity (RIC) visualizations, sediment dynamics and landscape patterns, and modeling solutions for SSY are explored through the innovative use of multiple models. The results showed that the sediment process showed high variability (CV > 0.36), and the same index had obvious watershed differences. Landscape pattern and RIC show highly significant correlation with mean or maximum suspended sediment concentration (p<0.01, |r|>0.235). Early rainfall depth was the dominant factor affecting SSY (Contribution = 48.15 %). The hysteresis loop and RIC infer that the sediment of Mahuangtian and Maolike mainly comes from downstream farmland and riverbeds, while Yangjichong comes from remote hillsides. The watershed landscape is centralized and simplified. In the future, patches of shrubs or herbaceous plants should be added around the cultivated land and at the bottom of the sparse forest to increase the sediment collection capacity. The backpropagation neural network (BPNN) is optimal for modeling SSY, particularly for running the variables preferred by the generalized additive model (GAM). This study provides insight into understanding RSE in karst small watersheds. It will help the region to cope with future extreme climate change and develop sediment management models that are consistent with regional realities.

A Stable Fe-Zn Modified Sludge-Derived Biochar for Diuron Removal: Kinetics, Isotherms, Mechanism, and Practical Research.

To remove typical herbicide diuron effectively, a novel sludge-derived modified biochar (SDMBC600) was prepared using sludge-derived biochar (SDBC600) as raw material and Fe-Zn as an activator and modifier in this study. The physico-chemical properties of SDMBC600 and the adsorption behavior of diuron on the SDMBC600 were studied systematically. The adsorption mechanisms as well as practical applications of SDMBC600 were also investigated and examined. The results showed that the SDMBC600 was chemically loaded with Fe-Zn and SDMBC600 had a larger specific surface area (204 m2/g) and pore volume (0.0985 cm3/g). The adsorption of diuron on SDMBC600 followed pseudo-second-order kinetics and the Langmuir isotherm model, with a maximum diuron adsorption capacity of 17.7 mg/g. The biochar could maintain a good adsorption performance (8.88-12.9 mg/g) under wide water quality conditions, in the pH of 2-10 and with the presence of humic acid and six typical metallic ions of 0-20 mg/L. The adsorption mechanisms of SDMBC600 for diuron were found to include surface complexation, π-π binding, hydrogen bonding, as well as pore filling. Additionally, the SDMBC600 was tested to be very stable with very low Fe and Zn leaching concentration ≤0.203 mg/L in the wide pH range. In addition, the SDMBC600 could maintain a high adsorption capacity (99.6%) after four times of regeneration and therefore, SDMBC600 could have a promising application for diuron removal in water treatment.

Multi-stimuli responsive Cu-MOFs@Keratin drug delivery system for chemodynamic therapy.

Although the potential of metal-organic framework (MOF) nanoparticles as drug delivery systems (DDS) for cancer treatment has been established by numerous studies, their clinical applications are still limited due to relatively poor biocompatibility. We fabricated a multifunctional Cu-MOFs@Keratin DDS for loaded drug and chemodynamic therapy (CDT) against tumor cells. The Cu-MOFs core was prepared using a hydrothermal method, and then loaded with the anticancer drug DOX and wrapped in human hair keratin. The Cu-MOFs@Keratin was well characterized by transmission electron microscopy (TEM), fourier transform infrared spectroscopy (FTIR), dynamic light scattering (DLS), and X-ray photoelectron spectroscopy (XPS). Characterization and pharmacokinetic studies of Cu-MOFs@Keratin were performed in vitro and in vivo. The keratin shell reduced the cytotoxicity and potential leakage of Cu-MOFs to normal cells, and allowed the drug-loaded nanoparticles to accumulate in the tumor tissues through enhanced permeability and retention effect (EPR). The particles entered the tumor cells via endocytosis and disintegrated under the stimulation of intracellular environment, thereby releasing DOX in a controlled manner. In addition, the Cu-MOFs produced hydroxyl radicals (·OH) by consuming presence of high intracellular levels of glutathione (GSH) and H2O2, which decreased the viability of the tumor cells.

Bilayer dressing based on aerogel/electrospun mats with self-catalytic hydrogen sulfide generation and enhanced antioxidant ability.

Hydrogen sulfide (H2S) releasing wound dressings have attracted much attention for their ability to promote cell proliferation, stimulate angiogenesis, and resist inflammation. Mimicking the skin structure, a bilayer wound dressing based on aerogel/mats with H2S release capability was designed and fabricated. A bio-macromolecular H2S donor based on a keratin-TA conjugate (KTC) was first synthesized through a thiol-disulfide exchange reaction. As an inner layer, KTC was then loaded into a gelatin hydrogel with large pores to absorb the wound exudates and generate H2S self-catalytically. Subsequently, polyurethane was electrospun with glutathione (GSH) to be used as an outer layer with small pores, which provided mechanical support, supplied GSH, and prevented bacterial invasion. The bilayer dressing was capable of generating H2S self-catalytically, achieving a controlled and sustained release. The dressing could also promote cell proliferation and migration. In addition, the dress possessed enhanced antioxidant ability and reactive oxygen species (ROS) scavenging capability. The bilayer dressing on promoting wound healing was investigated in a full-thickness excisional cutaneous wound model in rats. The results demonstrated that it could reduce inflammation, promote vascularization, and facilitate hair follicle regeneration, thereby accelerating wound healing. Overall, the bilayer dressing has great potential applications in the field of the wound dressing.