CRISPR-AMRtracker: A novel toolkit to monitor the antimicrobial resistance gene transfer in fecal microbiota.

The spread of antibiotic resistance genes (ARGs), particularly those carried on plasmids, poses a major risk to global health. However, the extent and frequency of ARGs transfer in microbial communities among human, animal, and environmental sectors is not well understood due to a lack of effective tracking tools. We have developed a novel fluorescent tracing tool, CRISPR-AMRtracker, to study ARG transfer. It combines CRISPR/Cas9 fluorescence tagging, fluorescence-activated cell sorting, 16S rRNA gene sequencing, and microbial community analysis. CRISPR-AMRtracker integrates a fluorescent tag immediately downstream of ARGs, enabling the tracking of ARG transfer without compromising the host cell's antibiotic susceptibility, fitness, conjugation, and transposition. Notably, our experiments demonstrate that sfGFP-tagged plasmid-borne mcr-1 can transfer across diverse bacterial species within fecal samples. This innovative approach holds the potential to illuminate the dynamics of ARG dissemination and provide valuable insights to shape effective strategies in mitigating the escalating threat of antibiotic resistance.

Chemoenzymatic Installation of Site-Specific Chemical Groups on DNA Enhances the Catalytic Activity.

Functional DNAs are valuable molecular tools in chemical biology and analytical chemistry but suffer from low activities due to their limited chemical functionalities. Here, we present a chemoenzymatic method for site-specific installation of diverse functional groups on DNA, and showcase the application of this method to enhance the catalytic activity of a DNA catalyst. Through chemoenzymatic introduction of distinct chemical groups, such as hydroxyl, carboxyl, and benzyl, at specific positions, we achieve significant enhancements in the catalytic activity of the RNA-cleaving deoxyribozyme 10-23. A single carboxyl modification results in a 100-fold increase, while dual modifications (carboxyl and benzyl) yield an approximately 700-fold increase in activity when an RNA cleavage reaction is catalyzed on a DNA-RNA chimeric substrate. The resulting dually modified DNA catalyst, CaBn, exhibits a kobs of 3.76 min-1 in the presence of 1 mM Mg2+ and can be employed for fluorescent imaging of intracellular magnesium ions. Molecular dynamics simulations reveal the superior capability of CaBn to recruit magnesium ions to metal-ion-binding site 2 and adopt a catalytically competent conformation. Our work provides a broadly accessible strategy for DNA functionalization with diverse chemical modifications, and CaBn offers a highly active DNA catalyst with immense potential in chemistry and biotechnology.

Unlocking the Potential of CO2 Capture: A Synergistic Hybridization Strategy for Polymeric Hydrogels with Tunable Physicochemical Properties.

Unlocking CO2 capture potential remains a complex and challenging endeavor. Here, a blueprint is crafted for optimizing materials through CO2 capture and developing a synergistic hybridization strategy that involves synthesizing CO2-responsive hydrogels by integrating polymeric networks interpenetrated with polyethyleneimine (PEI) chains and inorganic CaCl2. Diverging from conventional CO2 absorbents, which typically serve a singular function in CO2 capture, these hybrid PEAC hydrogels additionally harness its presence to tune their optical and mechanical properties once interacting with CO2. Such synergistic functions entail two significant steps: (i) rapid CO2-fixing through PEI chains to generate abundant carbamic acid and carbamate species and (ii) mineralization via CaCl2 to induce the formation of CaCO3 micro-crystals within the hydrogel matrix. Due to the reversible bonding, the PEAC hydrogels enable the decoupling of CO2 through an acid fumigation treatment or a heating process, achieving dynamic CO2 capture-release cycles up to 8 times. Furthermore, the polyethyleneimine-acrylamide-calcium chloride (PEAC) hydrogel exhibits varying antibacterial attributes and high interfacial adhesive strength, which can be modulated by fine-tuning the compositions of PEI and CaCl2. This versatility underscores the promising potential of PEAC hydrogels, which not only unlocks CO2 capture capabilities but also offers opportunities in diverse biological and biomedical applications.

Tough and stretchable ionic polyurethane foam for use in wearable devices.

Developing tough and conductive materials is crucial for the fields of wearable devices. However, soft materials like polyurethane (PU) are usually non-conductive, whereas conductive materials like carbon nanotubes (CNTs) are usually brittle. Besides, their composites usually face poor interfacial interactions, leading to a decline in performance in practical use. Here, we develop a stretchable PU/CNTs composite foam for use as a strain sensor. A cationic chain extender is incorporated to afford PU cationic groups and to regulate its mechanical properties, whose tensile strength is up to 12.30 MPa and breaking strain exceeds 1000%, and which shows considerable adhesion capability. Furthermore, porous PU foam is prepared via a salt-templating method and carboxylic CNTs with negative groups are loaded to afford the foam conductivity. The obtained foam shows high sensitivity to small strain (GF = 5.2) and exhibits outstanding long-term cycling performance, which is then used for diverse motion detection. The strategy illustrated here should provide new insights into the design of highly efficient PU-based sensors.

Waste to Wealth: Discarded Cigarette Butt-Derived Metal-Free N-Rich Carbon Catalysts for the Selective Catalytic Oxidation of Hydrogen Sulfide to Sulfur.

The selective catalytic oxidation of toxic gas H2S to elemental sulfur (H2S-SCO) is a promising desulfurization process known for its dual benefits of recovering valuable sulfur resources and mitigating environmental pollution. Nevertheless, developing cost-effective and efficient catalysts for H2S-SCO remains a significant challenge. In this study, we synthesized a low-cost and metal-free nitrogen-rich carbon catalyst (NrCC) by copyrolyzing discarded cigarette butts (organic solid wastes that are difficult to degrade naturally) with urea for the continuous H2S-SCO process at a relatively low temperature. The NrCC exhibited exceptional catalytic performance, achieving complete H2S conversion to sulfur at 180 °C, and demonstrated excellent stability in humid (RH = 80%) and high CO2 concentration environments. The catalyst succeeded due to its developed pore structure (specific surface area as high as 2267.77 m2·g-1) and abundant pyridine-N sites. DFT calculations showed that the pyridine-N neighbor carbon sites were the active sites promoting H2S adsorption and dissociation. This study presents a novel "waste control by waste" strategy that integrates the utilization of organic solid waste resources with air pollution control measures, showcasing the potential for sustainable environmental solutions.

Cross-provincial inpatient mobility patterns and their determinants in China.

BACKGROUND: The incongruity between the regional supply and demand of healthcare services is a persistent challenge both globally and in China. Patient mobility plays a pivotal role in addressing this issue. This study aims to delineate the cross-provincial inpatient mobility network (CIMN) in China and identify the underlying factors influencing this CIMN. METHODS: We established China's CIMN by applying a spatial transfer matrix, utilizing the flow information from 5,994,624 cross-provincial inpatients in 2019, and identified the primary demand and supply provinces for healthcare services. Subsequently, we employed GeoDetector to analyze the impact of 10 influencing factors-including medical resources, medical quality, and medical expenses-on the spatial patterns of CIMN. FINDINGS: Beijing, Shanghai, Zhejiang, and Jiangsu provinces are the preferred medical destinations for cross-provincial inpatients, while Anhui, Henan, Hebei, and Jiangsu provinces are the main sources for cross-provincial inpatients. Patient flow between provinces decreases with distance. The spatial distribution of medical resources, medical quality, and medical expenses account for 87%, 73%, and 56% of the formation of CIMN, respectively. Additionally, interactions between these factors enhance explanatory power, suggesting that considering their interactions can more effectively optimize medical resources and services. CONCLUSIONS: The analysis of CIMN reveals the supply and demand patterns of healthcare services, providing insights into the inequality characteristics of healthcare access. Furthermore, understanding the driving factors and their interactions offers essential evidence for optimizing healthcare services.

Metformin combined with glucose starvation synergistically suppress triple-negative breast cancer by enhanced unfolded protein response.

Metformin (MET) is a well-documented drug used in the treatment of type II diabetes. Recent studies have revealed its potential anti-tumor effects in various types of cancer. However, the dosage of MET required to exhibit anti-tumor activity is considerably higher than the clinically recommended dosage. In this study, we investigated the synergistical anti-tumor effect of glucose deprivation and MET in MDA-MB-231 cells, which represents a triple-negative breast cancer subtype (TNBC). Our findings demonstrate that glucose deprivation significantly enhances the anti-tumor activity of MET by reducing cell proliferation and increasing cell apoptosis. RNA-seq was performed to identify the key molecules involved in this process. Our results indicate that unfolded protein response of endoplasmic reticulum (UPRER) was significantly activated upon glucose starvation combining with MET compared to glucose starvation alone. Notably, the combined treatment significantly activated UPRER signaling pathway through ATF4/ATF3/CHOP axis, due to enhanced UPRER stress. In conclusion, our study suggests that the synergistic effects of MET and glucose deprivation suppress cell proliferation in TNBC by activating pro-apoptotic molecules through UPRER stress. These findings have potential implications for the anti-tumor application of MET in TNBC.

A spine segmentation method based on scene aware fusion network.

BACKGROUND: Intervertebral disc herniation, degenerative lumbar spinal stenosis, and other lumbar spine diseases can occur across most age groups. MRI examination is the most commonly used detection method for lumbar spine lesions with its good soft tissue image resolution. However, the diagnosis accuracy is highly dependent on the experience of the diagnostician, leading to subjective errors caused by diagnosticians or differences in diagnostic criteria for multi-center studies in different hospitals, and inefficient diagnosis. These factors necessitate the standardized interpretation and automated classification of lumbar spine MRI to achieve objective consistency. In this research, a deep learning network based on SAFNet is proposed to solve the above challenges. METHODS: In this research, low-level features, mid-level features, and high-level features of spine MRI are extracted. ASPP is used to process the high-level features. The multi-scale feature fusion method is used to increase the scene perception ability of the low-level features and mid-level features. The high-level features are further processed using global adaptive pooling and Sigmoid function to obtain new high-level features. The processed high-level features are then point-multiplied with the mid-level features and low-level features to obtain new high-level features. The new high-level features, low-level features, and mid-level features are all sampled to the same size and concatenated in the channel dimension to output the final result. RESULTS: The DSC of SAFNet for segmenting 17 vertebral structures among 5 folds are 79.46 ± 4.63%, 78.82 ± 7.97%, 81.32 ± 3.45%, 80.56 ± 5.47%, and 80.83 ± 3.48%, with an average DSC of 80.32 ± 5.00%. The average DSC was 80.32 ± 5.00%. Compared to existing methods, our SAFNet provides better segmentation results and has important implications for the diagnosis of spinal and lumbar diseases. CONCLUSIONS: This research proposes SAFNet, a highly accurate and robust spine segmentation deep learning network capable of providing effective anatomical segmentation for diagnostic purposes. The results demonstrate the effectiveness of the proposed method and its potential for improving radiological diagnosis accuracy.

Polysaccharide-Based Injectable Hydrogels with Fast Gelation and Self-Strengthening Mechanical Kinetics for Oral Tissue Regeneration.

Oral defects lead to a series of function disorders, severely threatening the patients' health. Although injectable hydrogels are widely studied in tissue regeneration, their mechanical performance is usually stationary after implant, without further self-adaption toward the microenvironment. Herein, an injectable hydrogel with programmed mechanical kinetics of instant gelation and gradual self-strengthening along with outstanding biodegradation ability is developed. The fast gelation is realized through rapid Schiff base reaction between biodegradable chitosan and aldehyde-modified sodium hyaluronate, while self-strengthening is achieved via slow reaction between redundant amino groups on chitosan and epoxy-modified hydroxyapatite. The resultant hydrogel also possesses multiple functions including (1) bio-adhesion, (2) self-healing, (3) bactericidal, (4) hemostasis, and (5) X-ray in situ imaging, which can be effectively used for oral jaw repair. We believe that the strategy illustrated here will provide new insights into dynamic mechanical regulation of injectable hydrogels and promote their application in tissue regeneration.

Parallel auxin transport via PINs and plasmodesmata during the Arabidopsis leaf hyponasty response.

KEY MESSAGE: The leaf hyponasty response depends on tip-to-petiole auxin transport. This transport can happen through two parallel pathways: active trans-membrane transport mediated by PIN proteins and passive diffusion through plasmodesmata. A plant's ability to counteract potential shading by neighboring plants depends on transport of the hormone auxin. Neighbor sensing at the leaf tip triggers auxin production. Once this auxin reaches the abaxial petiole epidermis, it causes cell elongation, which leads to leaf hyponasty. Two pathways are known to contribute to this intercellular tip-to-petiole auxin movement: (i) transport facilitated by plasma membrane-localized PIN auxin transporters and (ii) diffusion enabled by plasmodesmata. We tested if these two modes of transport are arranged sequentially or in parallel. Moreover, we investigated if they are functionally linked. Mutants in which one of the two pathways is disrupted indicated that both pathways are necessary for a full hyponasty response. Visualization of PIN3-GFP and PIN7-GFP localization indicated PIN-mediated transport in parallel to plasmodesmata-mediated transport along abaxial midrib epidermis cells. We found plasmodesmata-mediated cell coupling in the pin3pin4pin7 mutant to match wild-type levels, indicating no redundancy between pathways. Similarly, PIN3, PIN4 and PIN7 mRNA levels were unaffected in a mutant with disrupted plasmodesmata pathway. Our results provide mechanistic insight on leaf hyponasty, which might facilitate the manipulation of the shade avoidance response in crops.

Metagenomic analysis of antimicrobial resistance in ducks, workers, and the environment in duck farms, southern China.

Duck farms are one of the important reservoirs of antimicrobial resistance genes (ARGs) that spread to humans and the environment. However, few studies have focused on the characteristics of antimicrobial profiles in duck farms. Here we explored the distribution characteristics and potential transmission mechanisms of ARGs in ducks, farm workers, and the environment in duck farms by a metagenomic approach. The results showed that the highest abundance and diversity of ARGs were found in duck manure. The abundance and diversity of ARGs in workers and environmental samples were higher than those in the control group. tet(X) and its variants were prevalent in duck farms, with tet(X10) being the most abundant. The genetic structure "tet(X)-like + α/ß hydrolase" was found in ducks, workers, and the environment, implying that tet(X) and its variants have been widely spread in duck farms. Network analysis indicated that ISVsa3 and IS5075 might play an important role in the coexistence of ARGs and metal resistance genes (MRGs). The Mantel tests showed that mobile genetic elements (MGEs) were significantly correlated with ARG profiles. The results suggest that duck manure may be a potential hotspot source of ARGs, including tet(X) variants that spread to the surrounding environment and workers via MGEs. These results help us optimize the antimicrobials strategy and deepen our understanding of ARG spread in duck farms.

FAD: Fine-Grained Adversarial Detection by Perturbation Intensity Classification.

Adversarial examples present a severe threat to deep neural networks' application in safetycritical domains such as autonomous driving. Although there are numerous defensive solutions, they all have some flaws, such as the fact that they can only defend against adversarial attacks with a limited range of adversarial intensities. Therefore, there is a need for a detection method that can distinguish the adversarial intensity in a fine-grained manner so that subsequent tasks can perform different defense processing against perturbations of various intensities. Based on thefact that adversarial attack samples of different intensities are significantly different in the highfrequency region, this paper proposes a method to amplify the high-frequency component of the image and input it into the deep neural network based on the residual block structure. To our best knowledge, the proposed method is the first to classify adversarial intensities at a fine-grained level, thus providing an attack detection component for a general AI firewall. Experimental results show that our proposed method not only has advanced performance in AutoAttack detection by perturbation intensity classification, but also can effectively apply to detect examples of unseen adversarial attack methods.

Aligned electrospun fiber film loaded with multi-enzyme mimetic iridium nanozymes for wound healing.

A film with elaborate microstructures that offers biomimetic properties and multi functionalities is highly desired in wound healing. Here, we develop an aligned hydrogel fiber film integrated with multi-active constituents to promote wound healing. Such fiber films are designed and constructed by photo-crosslinking the methacrylate gelatin (GelMA) doped with silver nanoparticles (Ag NPs) and iridium nanoparticles coated with polyvinylpyrrolidone (PVP-Ir NPs) in the precursor solution using electrospinning. The nature of GelMA hydrogel and the aligned arrangement of nanofibers endow the film with high-water content, self-degradability, improved bionic characteristics, oriented cell growth, and improved cell proliferation and migration. Moreover, the encapsulated nanozymes and Ag NPs offer the fiber film with superior reactive oxygen species (ROS) scavenging and antibacterial capability. The infected wound model shows that the multi-active hydrogel fiber film can reduce inflammation by killing bacteria and decomposing ROS, which accelerates the growth of new blood vessels and granulation tissue. Benefitting from these features, the versatile aligned GelMA fiber film demonstrates the clinically translational potential for wound healing.

Risk of primary osteoporosis score (RPOPs): an algorithm model for primary osteoporosis risk assessment in grass-roots hospital.

BACKGROUND: This study aimed to develop and validate a lasso regression algorithm model which was established by correlation factors of bone mineral density (BMD) and could be accurately predicted a high-risk population of primary osteoporosis (POP). It provides a rapid, economical and acceptable early screening method for osteoporosis in grass-roots hospitals. METHODS: We collected 120 subjects from primary osteoporosis screening population in Zhejiang Quhua Hospital between May 2021 and November 2021 who were divided into three groups (normal, osteopenia and osteoporosis) according to the BMD T-score. The levels of three micro-RNAs in the plasma of these people were detected and assessed by qRT-PCR. At the same time, the levels of ß-CTX and t-P1NP in serum of the three groups were determined. Based on the cluster random sampling method, 84 subjects (84/120, 70%) were selected as the training set and the rest were the test set. Lasso regression was used to screen characteristic variables and establish an algorithm model to evaluate the population at high risk of POP which was evaluated and tested in an independent test cohort. The feature variable screening process was used 10-fold cross validation to find the optimal lambda. RESULTS: The osteoporosis risk score was established in the training set: Risk of primary osteoporosis score (RPOPs) = -0.1497785 + 2.52Age - 0.19miR21 + 0.35miR182 + 0.17ß-CTx. The sensitivity, precision and accuracy of RPOPs in an independent test cohort were 79.17%, 82.61% and 75%, respectively. The AUC in the test set was 0.80. Some risk factors have a significant impact on the abnormal bone mass of the subjects. These risk factors were female (p = 0.00013), older than 55 (p < 2.2e-16) and BMI < 24 (p = 0.0091) who should pay more attention to their bone health. CONCLUSION: In this study, we successfully constructed and validated an early screening model of osteoporosis that is able to recognize people at high risk for developing osteoporosis and remind them to take preventive measures. But it is necessary to conduct further external and prospective validation research in large sample size for RPOPs prediction models.

Bearing Fault Diagnosis Method Based on RCMFDE-SPLR and Ocean Predator Algorithm Optimizing Support Vector Machine.

For the problem that rolling bearing fault characteristics are difficult to extract accurately and the fault diagnosis accuracy is not high, an unsupervised characteristic selection method of refined composite multiscale fluctuation-based dispersion entropy (RCMFDE) combined with self-paced learning and low-redundant regularization (SPLR) is proposed, for which the fault diagnosis is carried out by support vector machine (SVM) optimized by the marine predator algorithm (MPA). First, we extract the entropy characteristics of the bearings under different fault states by RCMFDE and the introduction of the fine composite multiscale coarse-grained method and fluctuation strategy improves the stability and estimation accuracy of the bearing characteristics; then, a novel dimensionality-reduction method, SPLR, is used to select better entropy characteristics, and the local flow structure of the fault characteristics is preserved and the redundancy is constrained by two regularization terms; finally, using the MPA-optimized SVM classifier by combining Levy motion and Eddy motion strategies, the preferred RCMFDE is fed into the MPA-SVM model for fault diagnosis, for which the obtained bearing fault diagnosis accuracy is 97.67%. The results show that the RCMFDE can effectively improve the stability and accuracy of the bearing characteristics, the SPLR-based low-dimensional characteristics can suppress the redundancy characteristics and improve the effectiveness of the characteristics, and the MPA-based adaptive SVM model solves the parameter randomness problem and, therefore, the proposed method has outstanding superiority.

Protective effects of Astragaloside IV against oxidative injury and apoptosis in cultured astrocytes by regulating Nrf2/JNK signaling.

Ischemic stroke is a worldwide complex brain disease that results in numerous disabilities and deaths. It leads to the deprivation of oxygen and glucose, which causes energy failure and neuronal death. The activation of astrocytes contributes to neuronal damage or repair after brain ischemia/reperfusion, although astrocytes get little attention as potential drug targets. This study investigated the protective effects of Astragaloside IV (AS-IV) on oxygen glucose deprivation/reoxygenation (OGD/R)-induced damage in rat primary cultured astrocytes and the underlying molecular mechanism. The results showed that compared with the control group, astrocytes under OGD/R exposure significantly decreased cell viability and increased the number of apoptotic cells, whereas AS-IV evidently protected the astrocytes against OGD/R-induced cell damage. In addition, low and medium concentrations of AS-IV can promote the increase of intracellular superoxide dismutase (SOD) level, as well as restored the morphological changes caused by OGD/R exposure. Supplementation with AS-IV after OGD/R exposure promoted the expression of oxidation and apoptosis indexes and further study demonstrated that AS-IV inhibited CXCR4 receptor and downregulated the activation of p-JNK/JNK pathway, which suppressed the expression of Bax/Bcl-2, and finally uprising Nrf2/Keap1 signaling. In conclusion, these findings revealed that AS-IV protected against OGD/R-induced astrocytes through inhibiting oxidative stress and apoptotic pathways.

Synthesis of ß-Methylsulfonylated N-Heterocycles from Saturated Cyclic Amines with the Insertion of Sulfur Dioxide.

An efficient synthesis of ß-methylsulfonylated N-heterocycles via FeCl3-catalyzed C(sp3)-H dehydrogenation and C(sp2)-H methylsulfonylation of inactivated cyclic amines with the promotion and participation of inorganic sodium metabisulfite and dicumyl peroxide (DCP) has been developed. Notably, bifunctional DCP acted not only as an oxidant to promote the dehydrogenation but also as a methyl radical to participate in the sulfone formation. With this protocol, a number of ß-methylsulfonylated tetrahydropyridines, tetrahydroazepines, and pyrroles were obtained in a facile one-pot manner.

Future Flood Risk Assessment under the Effects of Land Use and Climate Change in the Tiaoxi Basin.

Global warming and land-use change affects runoff in the regional basin. Affected by different factors, such as abundant rainfall and increased impervious surface, the Taihu basin becomes more vulnerable to floods. As a result, a future flood risk analysis is of great significance. This paper simulated the land-use expansion and analyzed the surface change from 2020 to 2050 using the neural network Cellular Automata Markov (CA-Markov) model. Moreover, the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) dataset was corrected for deviation and used to analyze the climate trend. Second, the verified SWAT model was applied to simulate future runoff and to analyze the future flood risk. The results show that (1) land use is dominated by cultivated land and forests. In the future, the area of cultivated land will decrease and construction land will expand to 1.5 times its present size. (2) The average annual precipitation and temperature will increase by 1.2% and 1.5 degrees from 2020 to 2050, respectively. During the verified period, the NSE and r-square values of the SWAT model are greater than 0.7. (3) Compared with the historical extreme runoff, the extreme runoff in the return period will increase 10%~25% under the eight climate models in 2050. In general, the flood risk will increase further under the climate scenarios.

Electric Assisted Salt-Responsive Bacterial Killing and Release of Polyzwitterionic Brushes in Low-Concentration Salt Solution.

Polyzwitterionic brushes with strong antipolyelectrolyte effects have shown great potential as versatile platforms for the development of switchable friction/lubrication and bacterial absorption/desorption surfaces. However, the surface property switches of these brushes are usually triggered by high salt concentrations (>0.53 M), thereby greatly limiting their applications in biological fields where the salt concentration for mammals is ?0.15 M. To solve this problem, an electric field was used to assist the salt-responsive process of the polyzwitterionic brushes to achieve bacterial release at low concentrations of the salt solution. Briefly, poly(3-(dimethyl (4-vinylbenzyl) ammonium) propyl sulfonate) (polyDVBAPS) brushes grafted on ITO surfaces were prepared by surface initiated atom transfer radical polymerization. The bacterial release of this surface was conducted under an electric field, where anions were migrated and enriched around the brush-grafted ITO surface as anode. The local high concentration ion led to the conformation change of the brush and release of the attached bacteria. The effect of salt type, salt concentration, electric field strength, and conducting time on the bacterial release properties were investigated. The results indicated that under an electrical field of 3 V/mm, polyDVBAPS showed release capacities of ?93% for E. coli and ?81% for S. aureus in 0.12 M NaCl electrolyte solution. Furthermore, by the introduction of a bactericidal agent, i.e., Triclosan (TCS), an antibacterial surface with dual functions of killing and release was fabricated. This surface could kill ?90% and release 95% of attached E. coli in a 0.12 M NaCl solution by the application of a 3 V/mm electric field. This work demonstrated the feasibility of triggering a salt-responsive behavior of polyzwitterionic at low salt concentration by assistance of electric field, which would greatly extend the applications of polyzwitterionic, in particular in biological applications.

Structural Dependence of Salt-Responsive Polyzwitterionic Brushes with an Anti-Polyelectrolyte Effect.

Some polyzwitterionic brushes exhibit a strong "anti-polyelectrolyte effect" and ionic specificity that make them versatile platforms to build smart surfaces for many applications. However, the structure-property relationship of zwitterionic polymer brushes still remains to be elucidated. Herein, we aim to study the structure-dependent relationship between different zwitterionic polymers and the anti-polyelectrolyte effect. To this end, a series of polyzwitterionic brushes with different cationic moieties (e.g., imidazolium, ammonium, and pyridinium) in their monomeric units and with different carbon spacer lengths (e.g., CSL = 1, 3, and 4) between the cation and anion were designed and synthesized to form polymer brushes via the surface-initiated atom transfer radical polymerization. All zwitterionic brushes were carefully characterized for their surface morphologies, compositions, wettability, and film thicknesses by atomic force microscopy, contact angle measurement, and ellipsometry, respectively. The salt-responsiveness of all zwitterionic brushes to surface hydration and friction was further examined and compared both in water and in salt solutions with different salt concentrations and counterion types. The collective data showed that zwitterionic brushes with different cationic moieties and shorter CSLs in salt solution induced higher surface friction and lower surface hydration than those in water, exhibiting strong anti-polyelectrolyte effect salt-responsive behaviors. By tuning the CSLs, cationic moieties, and salt concentrations and types, the surface wettability can be changed from a highly hydrophobic surface (∼60°) to a highly hydrophilic surface (∼9°), while interfacial friction can be changed from ultrahigh friction (µ ≈ 4.5) to superior lubrication (µ ≈ 10-3). This work provides important structural insights into how subtle structural changes in zwitterionic polymers can yield great changes in the salt-responsive properties at the interface, which could be used for the development of smart surfaces for different applications.