Learning co-plane attention across MRI sequences for diagnosing twelve types of knee abnormalities.

Multi-sequence magnetic resonance imaging is crucial in accurately identifying knee abnormalities but requires substantial expertise from radiologists to interpret. Here, we introduce a deep learning model incorporating co-plane attention across image sequences to classify knee abnormalities. To assess the effectiveness of our model, we collected the largest multi-sequence knee magnetic resonance imaging dataset involving the most comprehensive range of abnormalities, comprising 1748 subjects and 12 types of abnormalities. Our model achieved an overall area under the receiver operating characteristic curve score of 0.812. It achieved an average accuracy of 0.78, outperforming junior radiologists (accuracy 0.65) and remains competitive with senior radiologists (accuracy 0.80). Notably, with the assistance of model output, the diagnosis accuracy of all radiologists was improved significantly (p < 0.001), elevating from 0.73 to 0.79 on average. The interpretability analysis demonstrated that the model decision-making process is consistent with the clinical knowledge, enhancing its credibility and reliability in clinical practice.

Ionic Hyperbranched Poly(amido-amine)-Incorporated Nanofiltration Membranes for High-Efficiency Dye Desalination.

High-efficiency dye desalination is crucial in the textile industry, considering its importance for human health, safe aquatic ecological systems, and resource recovery. In order to solve the problem of effective separation of univalent salt and ionic dye under the condition of high salt, ionic hyperbranched poly(amido-amine) (HBPs) were synthesized based on a simple and scalable one-step polycondensation method and then incorporated into the polyamide (PA) selective layers to construct charged nanochannels through interfacial polymerization (IP) on the surface of a polyvinyl chloride ultrafiltration (PVC-UF) hollow fiber membrane. Both the internal nanopores of HBPs (internal nanochannels) and the interfacial voids between HBPs and the PA matrix (external nanochannels) can be regarded as a fast water molecule transport pathway, while the terminal ionic groups of ionic HBPs endow the nanochannels with charge characteristics for improving ionic dye/salt selectivities. The permeate fluxes and dye/salt selectivities of HBP-TAC/PIP (57.3 L m-2 h-1 and rhodamine B (RB)/NaCl selectivity of 224.0) and HBP-PS/PIP (63.7 L m-2 h-1 and lemon yellow (LY)/NaCl selectivity of 664.0) membranes under 0.4 MPa operation pressure are much higher than PIP-only and HBP-NH2/PIP membranes. At the same time, this project also studied the membrane desalination process in a simulated high-salinity dye/salt mixture system to provide a theoretical basis and technical support for the actual dye desalination process.

Highly active nanoparticle enhanced rapid adsorption-killing mechanism to combat multidrug-resistant bacteria.

Contact-killing surfaces with the ability to rapidly adsorb and kill microorganisms are desperately needed since the rapid outbreak of multidrug-resistant (MDR) bacteria poses a serious threat to human health. Therefore, a series of amphiphilic nanoengineered polyquaterniums (ANPQs) were synthesized, and immobilizing ANPQs onto equipment surfaces provided a simple method for preventing microbial infections. The strong charge-positive property of ANPQ offered the possibility of rapid adsorption and efficient killing, such that all bacteria are adsorbed after 10 seconds of contact with ANPQ-treated fabrics, and more than 99.99% of pathogens are killed within 30 seconds. Surprisingly, the adsorption-killing mechanism made it difficult for bacteria to develop resistance to ANPQ coating, even after long-term repeated treatment. Importantly, in a Methicillin-resistant Staphylococcus aureus infection model, ANPQ-treated fabrics exhibited a potent anti-infectious performance while remaining nontoxic. It is envisaged that the strategy of using ANPQ coating undoubtedly provides a promising candidate for fighting MDR strains.

Zwitterionic Separator Featured with Superdesolvating Properties for High Performance Lithium-Sulfur Batteries.

Lithium-sulfur chemistry has greatly expanded the boundaries of lithium batteries, but the persistent parasitic reaction of soluble sulfur intermediates with lithium anode remains a primary challenge. Understanding and regulating the solvation structures of lithium ions (Li+) and polysulfides (LiPSs) are critical to addressing the above issues. Herein, inspired by the natural superhydrophilic resistance to contamination, we developed a zwitterionic nanoparticles (ZWP) separator capable of modulating the solvated of Li+ and LiPSs. The dense solvated layer induced by ZWP effectively prevents the movement of LiPSs without compromising Li+ transport. Moreover, the high electrolyte affinity of the ZWP effectively results in minimizing the deposition of LiPSs on the separator. Furthermore, the structure of the solvated Li+ and LiPSs is also unveiled by molecular simulation and nuclear magnetic resonance (NMR). In addition, in situ UV setup proved the ZWP separator can effectively suppress the shuttle of LiPSs. The restricted space formed by the tightly packed ZWP stabilizes the lithium deposition and regulates dendrite growth. Consequently, the performance of lithium-sulfur batteries is significantly improved and good cycle stability is maintained even at high sulfur loadings (5 mg cm-2). This contribution provides a new insight into the rational design of lithium-sulfur battery separators.

Influence of cationic groups on the antibacterial behavior of cationic nano-sized hyperbranched polymers to enhance bacteria-infected wound healing.

With the continuous emergence of drug-resistant pathogens, new strategies with high antibacterial efficacy are urgently needed. Herein, five cationic nano-sized hyperbranched polymers (CNHBPs) with cationic functional groups have been constructed, and their antibacterial mechanism has been studied in detail. CNHBPs bearing secondary ammonium salt groups and long alkyl chains (S12-CNHBP) exhibited weak antibacterial and antibiofilm ability, while CNHBPs bearing quaternary ammonium salt groups and long alkyl chains (Q12-CNHBP) showed the highest antimicrobial and strongest antibiofilm activities. ζ potential and isothermal titration microcalorimetry (ITC) results suggest that the negatively charged surfaces of bacterial cells provided Q12-CNHBP with a higher intrinsic electrostatic driving force for bacterial killing than that with S12-CNHBP. Fluorescent tracing and morphological observations indicate that the bacterial genome might be another antibacterial target for S12-CNHBP in addition to the cell wall and membrane, which are mainly antibacterial targets for Q12-CNHBP, making it less likely to induce bacterial resistance. Surprisingly, Q12-CNHBP exhibited superior in vivo therapeutic efficacy in a mouse wound model of methicillin-resistant Staphylococcus aureus (MRSA) infection with low toxicity during treatment. These advantages and ease of preparation will undoubtedly distinguish Q12-CNHBP as a new class of suitable candidates to combat multidrug-resistant pathogen infections. This study opens up a new avenue for exploiting antibacterial biomaterials to treat infections caused by drug-resistant bacteria.

Secondary Ammonium-Based Hyperbranched Poly(amidoamine) with Excellent Membrane-Active Property for Multidrug-Resistant Bacterial Infection.

With the rapid emergence of microbial infections induced by "superbugs", public health and the global economy are threatened by the lack of effective and biocompatible antibacterial agents. Herein, we systematically design a series of secondary ammonium-based hyperbranched poly(amidoamine) (SAHBP) with different alkyl chain lengths for probing high-efficacy antibacterial agents. SAHBP modified with alkyl tails at the hyperbranched core could efficiently kill Escherichia coli and Staphylococcus aureus, two types of clinically important bacteria worldwide. The best SAHBP with 12-carbon-long alkyl tails (SAHBP-12) also showed high activity against problematic multidrug-resistant bacteria, including Pseudomonas aeruginosa and methicillin-resistant S. aureus (MRSA). Based on ζ potential, isothermal titration microcalorimetry (ITC), and membrane integrity assays, it is found that SAHBP-12 could attach to the cell membrane via electrostatic adsorption and hydrophobic interactions, following which the integrity of the bacterial cell wall and the cell membrane is disrupted, resulting in severe cell membrane damage and the leakage of cytoplasmic contents, finally causing bacterial cell death. Impressively, benefiting from excellent membrane-active property, SAHBP-12 exhibited robust therapeutic efficacy in MRSA-infected mice wounds. Moreover, SAHBP-12 also showed excellent biosafety in vitro and in vivo, which undoubtedly distinguished it as a potent weapon in combating the growing threat of problematic multidrug-resistant bacterial infections.

Hybrid Dilated Convolution with Multi-Scale Residual Fusion Network for Hyperspectral Image Classification.

The convolutional neural network (CNN) has been proven to have better performance in hyperspectral image (HSI) classification than traditional methods. Traditional CNN on hyperspectral image classification is used to pay more attention to spectral features and ignore spatial information. In this paper, a new HSI model called local and hybrid dilated convolution fusion network (LDFN) was proposed, which fuses the local information of details and rich spatial features by expanding the perception field. The details of our local and hybrid dilated convolution fusion network methods are as follows. First, many operations are selected, such as standard convolution, average pooling, dropout and batch normalization. Then, fusion operations of local and hybrid dilated convolution are included to extract rich spatial-spectral information. Last, different convolution layers are gathered into residual fusion networks and finally input into the softmax layer to classify. Three widely hyperspectral datasets (i.e., Salinas, Pavia University and Indian Pines) have been used in the experiments, which show that LDFN outperforms state-of-art classifiers.

Ionic Dendrimer Based Polyamide Membranes for Ion Separation.

Separating low/high-valent ions with sub-nanometer sizes is a crucial yet challenging task in various areas (e.g., within environmental, healthcare, chemical, and energy engineering). Satisfying high separation precision requires membranes with exceptionally high selectivity. One way to realize this is constructing well-designed ion-selective nanochannels in pressure-driven membranes where the separation mechanism relies on combined steric, dielectric exclusion, and Donnan effects. To this aim, charged nanochannels in polyamide (PA) membranes are created by incorporating ionic polyamidoamine (PAMAM) dendrimers via interfacial polymerization. Both sub-10 nm sizes of the ionic PAMAM dendrimer molecules and their gradient distributions in the PA nanofilms contribute to the successful formation of defect-free PA nanofilms, containing both internal (intramolecular voids) and external (interfacial voids between the ionic PAMAM dendrimers and the PA matrix) nanochannels for fast transport of water molecules. The external nanochannels with tunable ionizable groups endow the PA membranes with both high low/high-valent co-ion selectivity and chemical cleaning tolerance, while the ion sieving/transport mechanism was analyzed by employing the Donnan steric pore model with dielectric exclusion.

Negatively-charged nanofiltration membrane and its hexavalent chromium removal performance.

To enhance hexavalent chromium (Cr(VI)) removal performance under acidic conditions, the nanofiltration (NF) membrane with enhanced negative charge was fabricated via introducing 2, 5-diaminobenzenesulfonic acid (DABSA) into polyamide layer. The control membrane (NF-P) was directly prepared from piperazine and 1, 3, 5-benzenetricarbonyltrichloride. Surface chemical compositions, morphology, surface charge, pore size, permeability and pH-dependent separation performance of the fabricated membranes were characterized. The membranes showed the similar water permeance (∼11.5 L m-2 h-1 bar-1) and Na2SO4 rejections (∼98%) under neutral environments. The DABSA introduced NF membrane (NF-PD) was negatively charged in the pH range of 2.5-11, while the isoelectric point for NF-P was ∼pH 4.0. Cr(VI) removal ability was then evaluated under various concentrations and pH environments. The results indicated that NF-PD showed the better Cr(VI) rejection performance in all tested conditions than NF-P, especially under acidic environments (e.g., pH 4 and pH 5). Moreover, there was a fluctuation of the rejection with the increase of Cr(VI) concentration under acidic environments, which was mainly caused by the formation of Cr2O72- species. The harmful Cr(VI) was efficiently removed by the NF membrane with enhanced negative charge under acidic environments, which indicated the wider application range of the NF membrane.