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The importance of singlet oxygen ( 1 O 2 ) in the environmental and biomedical fields has motivated research for effective 1 O 2 production. Electrocatalytic processes hold great potential for highly-automated and scalable 1 O 2 synthesis, but they are energy- and chemical-intensive. Herein, we present a Janus electrocatalytic membrane realizing ultra-efficient 1 O 2 production (6.9 mmol per m 3 of permeate) and very low energy consumption (13.3 Wh per m 3 of permeate) via a fast, flow-through electro-filtration process without the addition of chemical precursors. We confirm that a superoxide-mediated chain reaction, initiated by electrocatalytic oxygen reduction on the cathodic membrane side and subsequently terminated by H 2 O 2 oxidation on the anodic membrane side, is crucial for 1 O 2 generation. We further demonstrate that the high 1 O 2 production efficiency is mainly attributable to the enhanced mass and charge transfer imparted by nano- and micro-confinement effects within the porous membrane structure. Our findings highlight a new electro-filtration strategy and an innovative reactive membrane design for synthesizing 1 O 2 for a broad range of potential applications including environmental remediation. Electrocatalytic processes are promising for automated and scalable synthesis of singlet oxygen, but they are energy- and chemical-intensive. Here the authors present a Janus electrocatalytic membrane that selectively produces singlet oxygen with low energy consumption and free of chemical precursors.

This study develops water treatment membranes using an innovative surface modifier comprising threaded supramolecular assemblies formed by hydrophilic cyclodextrin (CD) and low-surface-energy polydimethylsiloxane (PDMS). These supramolecular constructs establish dynamic hydrophilic and low-surface-energy heterogeneous microdomains that enhance synergistic resistance-release antifouling mechanisms. The modified membranes demonstrate better antifouling performance compared to conventional systems, particularly addressing the critical limitation of traditional membranes under low tangential flow conditions. The Brownian motion of the CDs sustains microdomain activity to prevent foulant accumulation in static environments, while tangential flow amplifies dynamic interactions to accelerate foulant detachment. The threading configuration of CDs along PDMS chains prevents water channel blockage caused by PDMS aggregation and facilitates water transport through the dynamic mobility of CDs. When separating bovine serum albumin solutions under an initial flux of 550 L·m −2 ·h −1 with 60 rpm stirring, the membrane exhibits merely 14.2% flux decline, highlighting its exceptional antifouling performance and permeability. Water treatment membranes are prone to fouling, degrading performance. Here the authors integrate cyclodextrin supramolecular systems which harness the dynamic behavior of surface molecules to prevent foulant accumulation, thereby preserving membrane performance.

Pore size uniformity is one of the most critical parameters in determining membrane separation performance. Recently, a novel type of conjugated microporous polymers (CMPs) has shown uniform pore size and high porosity. However, their brittle nature has prevented them from preparing robust membranes. Inspired by the skin-core architecture of spider silk that offers both high strength and high ductility, herein we report an electropolymerization process to prepare a CMP membrane from a rigid carbazole monomer, 2,2’,7,7’-tetra(carbazol-9-yl)-9,9’-spirobifluorene, inside a robust carbon nanotube scaffold. The obtained membranes showed superior mechanical strength and ductility, high surface area, and uniform pore size of approximately 1 nm. The superfast solvent transport and excellent molecular sieving well surpass the performance of most reported polymer membranes. Our method makes it possible to use rigid CMPs membranes in pressure-driven membrane processes, providing potential applications for this important category of polymer materials. Conjugated microporous polymers (CMPs) have great potential in membrane applications but are often brittle. Here, the authors develop an electropolymerization process to form a skin-core architecture which allows them to overcome mechanical limitations while keeping the excellent separation performance of CMP membranes.

In the field of target tracking, monopulse radar is widely used to obtain the positions of radar targets. The achieved angle measurement performance is greatly weakened when barrage interference is contained in the main lobe of the receiving antenna. Interference signals can be easily filtered by the conventional polarization filtering (PF) method. However, the conventional PF method is unable to address situations in which two barrage interferences with different polarization states are contained in the main lobe, because the polarizations of both interferences become complex. To filter dual‐interference sources in the main lobe, a novel polarimetric filtering method is proposed in this letter. This novel method is based on polarization selection, which is implemented to suppress one of the dual‐interference sources. The appropriate polarimetric parameters are first selected by a monopulse ratio constraint condition. Then, the spatial location of the other interference source can be measured. After searching the whole polarimetric domain, the spatial parameters of the two interference sources can be acquired by the polarimetric monopulse system. Finally, the waveforms of the interference signals can also be estimated during the filtering process. The results of a microwave chamber experiment demonstrate that this novel filtering method is effective.

•This study proposed a robust and accurate segmentation method for WMH of vascular origin, outperforming the widely used methods to which it was compared.•The method has been validated on two external datasets, demonstrating good generalization ability across different MRI systems and protocols.•This approach is practical and requires no post-processing, offering an accessible and reliable solution for WMH segmentation in various large cohorts. White matter hyperintensity (WMH) is a primary manifestation of small vessel disease (SVD), leading to vascular cognitive impairment and other disorders. Accurate WMH quantification is vital for diagnosis and prognosis, but current automatic segmentation methods often fall short, especially across different datasets. The aims of this study are to develop and validate a robust deep learning segmentation method for WMH of vascular-origin. In this study, we developed a transformer-based method for the automatic segmentation of vascular-origin WMH using both 3D T1 and 3D T2-FLAIR images. Our initial dataset comprised 126 participants with varying WMH burdens due to SVD, each with manually segmented WMH masks used for training and testing. External validation was performed on two independent datasets: the WMH Segmentation Challenge 2017 dataset (170 subjects) and an in-house vascular risk factor dataset (70 subjects), which included scans acquired on eight different MRI systems at field strengths of 1.5T, 3T, and 5T This approach enabled a comprehensive assessment of the method’s generalizability across diverse imaging conditions. We further compared our method against LGA, LPA, BIANCA, UBO-detector and TrUE-Net in optimized settings. Our method consistently outperformed others, achieving a median Dice coefficient of 0.78 ± 0.09 in our primary dataset, 0.72 ± 0.15 in the external dataset 1, and 0.72 ± 0.14 in the external dataset 2. The relative volume errors were 0.15 ± 0.14, 0.50 ± 0.86, and 0.47 ± 1.02, respectively. The true positive rates were 0.81 ± 0.13, 0.92 ± 0.09, and 0.92 ± 0.12, while the false positive rates were 0.20 ± 0.09, 0.40 ± 0.18, and 0.40 ± 0.19. None of the external validation datasets were used for model training; instead, they comprise previously unseen MRI scans acquired from different scanners and protocols. This setup closely reflects real-world clinical scenarios and further demonstrates the robustness and generalizability of our model across diverse MRI systems and acquisition settings. As such, the proposed method provides a reliable solution for WMH segmentation in large-scale cohort studies.

Highlights A dry transfer method for the mass production of transparent conductive carbon nanotube (CNT) films inspired by typography has been proposed. The strain sensors based on the CNT films have high stretchability and repeatability (gauge factor up to 9960 at 85% strain). These ultrathin strain sensors can detect human motion, sound, and pulse, suggesting promising application prospects in wearable devices. Flexible and wearable sensing devices have broad application prospects in bio-monitoring such as pulse measurement, motion detection and voice recognition. In recent years, many significant improvements had been made to enhance the sensor’s performance including sensitivity, flexibility and repeatability. However, it is still extremely complicated and difficult to prepare a patterned sensor directly on a flexible substrate. Herein, inspired by typography, a low-cost, environmentally friendly stamping method for the mass production of transparent conductive carbon nanotube (CNT) film is proposed. In this dry transfer strategy, a porous CNT block was used as both the seal and the ink; and Ecoflex film was served as an object substrate. Well-designed CNT patterns can be easily fabricated on the polymer substrate by engraving the target pattern on the CNT seal before the stamping process. Moreover, the CNT film can be directly used to fabricate ultrathin (300 μm) strain sensor. This strain sensor possesses high sensitivity with a gauge factor (GF) up to 9960 at 85% strain, high stretchability (> 200%) and repeatability (> 5000 cycles). It has been used to measure pulse signals and detect joint motion, suggesting promising application prospects in flexible and wearable electronic devices.

Introduction High glucose levels are associated with cognitive impairment and total hippocampal volume reductions. However, the effects of the blood glucose level on hippocampal subfield volumes remain unclear, especially in the prediabetes stage. Methods Sixty participants were enrolled in this cross‐sectional study and were divided into the nondiabetes, prediabetes, and diabetes groups according to their medical history and A1c level. A full battery of neuropsychological tests was used to assess the global cognition, executive function, attention, verbal fluency, working memory, immediate memory, and delayed memory. FreeSurfer 6.0 was used for the hippocampus parcellation. Hippocampal subfield volumes were adjusted by intracranial volume. Analyses of covariance, multiple linear regression, and partial correlation analysis were used to explore the relationship between A1c level, cognitive function, and hippocampal subfields volume, in which age, sex, education years, body mass index, history of hypertension, level of cholesterol, and the presence of ApoE4‐positive status were adjusted. Results Significant differences in the total left hippocampal volume (p = 0.046) and left hippocampal tail volume (p = 0.014) were noted among three groups. Significant correlation was identified between the A1c level and the volume of left hippocampal tail (r = −0.334, p = 0.009) after adjusting all the covariants. Increased A1c level was significantly associated with executive dysfunction, as assessed by trail making test B (R = 0.503, p = 0.0016) and Stroop test C (R = 0.506, p = 0.001). Conclusions Our results support that the left hippocampal tail volume may be served as an early marker of diabetes‐related brain damage, associated with executive dysfunction. Clinicians should pay closer attention to adults in the prediabetes stage to prevent later cognitive impairment. This study examined the relationships among the plasma glycosylated hemoglobin level (A1c), hippocampal subfield volumes, and cognitive performance in participants with and without diabetes, as well as those in the prediabetes stage. Our findings support that for individuals with diabetes, the left posterior hippocampus, especially the hippocampal tail, may be affected early, associated with executive function loss.

Background The pathogenic mechanisms of vascular cognitive impairment (VCI) are complicated, involving brain atrophy, parenchymal damage, and functional dysconnectivity associated with vascular risk factors, cerebrovascular diseases, and mixed pathologies. The alterations of the cortical structural similarity in VCI and their relationships with specific gene expression patterns and neurobiological characteristics have not been fully investigated. Methods Individual Morphometric INverse Divergence (MIND) networks were constructed from structural MRI data from all participants. General linear model (GLM) and partial least squares (PLS) analysis were utilized to assess the alterations in MIND and the spatial associations of MIND differences with brain-wide transcriptional patterns. Finally, enrichment analysis of PLS weighted genes, along with cell-type-specific genes, and correlation analysis of MIND changes and neurotransmitter receptors, as well as mitochondrial metrics, were conducted to examine the neurobiological foundations of cortical morphometric similarity changes. Results A total of 245 individuals were enrolled, including 100 cognitively unimpaired (CU) individuals and 145 VCI patients. Compared with the CU subjects, individuals with VCI showed reduced MIND in the frontal, parietal, and cingulate lobes. The PLS2− weighted genes correlated with MIND changes in VCI overlapped with genes related to oligodendrocytes and neurons. They were also substantially enriched in neuronal system activities and the RHO GTPase cycle associated with signal transduction and cytoskeleton regulation. The differences in MIND between the two groups were spatially associated with the levels of multiple neurobiological features. Conclusions Our results improved the understanding of the transcriptional patterns and molecular features at the micro level that contribute to macroscale changes in morphological resemblance among individuals with VCI, offering potential clues for future diagnostic and therapeutic studies.

Although clinically, Alzheimer's disease (AD) and vascular dementia (VaD) are the two major types of dementia, it is unclear whether the biophotonic activities associated with cognitive impairments in these diseases share common pathological features. We used the ultraweak biophoton imaging system (UBIS) and synaptosomes prepared by modified percoll method to directly evaluate the functional changes in synapses and neural circuits in AD and VaD model animals. We found that biophotonic activities induced by glutamate were significantly reduced and spectral blueshifted in synaptosomes and brain slices. These changes could be partially reversed by pre-perfusion of the ifenprodil, a specific antagonist of the GluN2B subunit of N-methyl-D-aspartate receptors (NMDARs). Our findings suggest that AD and VaD pathology present similar but complex changes in biophotonic activities and transmission at synapses and neural circuits, implying that communications and information processing of biophotonic signals in the brain are crucial for advanced cognitive functions.

Enhancing the water flux while maintaining the high salt rejection of existing reverse osmosis membranes remains a considerable challenge. Herein, we report the use of a porous carbon nitride (C3N4) nanoparticle to potentially improve both the water flux and salt rejection of the state-of-the-art polyamide (PA) thin film composite (TFC) membranes. The organic–organic covalent bonds endowed C3N4 with great compatibility with the PA layer, which positively influenced the customization of interfacial polymerization (IP). Benefitting from the positive effects of C3N4, a more hydrophilic, more crumpled thin film nanocomposite (TFN) membrane with a larger surface area, and an increased cross-linking degree of PA layer was achieved. Moreover, the uniform porous structure of the C3N4 embedded in the ”ridge” sections of the PA layer potentially provided additional water channels. All these factors combined provided unprecedented performance for seawater desalination among all the PA-TFC membranes reported thus far. The water permeance of the optimized TFN membrane is 2.1-folds higher than that of the pristine PA-TFC membrane, while the NaCl rejection increased to 99.5% from 98.0%. Our method provided a promising way to improve the performance of the state-of-art PA-TFC membranes in seawater desalination.