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Although the development of disinfection technologies with novel mechanisms has stagnated, we demonstrate the bactericidal effects and mechanisms of high-speed nanodroplet generation technology. The first development of this technology in 2017 gushes out a water droplet of 10 nm in size at 50 m/s; however, the target surface does not become completely wet. Nanodroplets were exposed to biofilm models of Staphylococcus aureus , Pseudomonas aeruginosa , Escherichia coli , and Serratia marcescens . This phenomenon was verified when the nanodroplets collide with the surface of the bacteria at an impact pressure of ~75 MPa. S. aureus was exposed to nanodroplets for 30 seconds at 75 MPa, which exploded the bacterial body and completely sterilized. Eighteen MPa damaged the bacterial surface, causing peptidoglycan leakage. S. aureus was repaired and survives in this state. In contrast, in Gram-negative bacteria, nanodroplets with 18 MPa penetrated some biofilm-forming bacteria but did not hit all of them, and the viable count was not significantly reduced. Although all three bacterial species were completely sterilized at 75 MPa, the disinfectant effect was affected by the biomass of the biofilm formed. In summary, our findings prove that nanodroplets at 18 MPa on the bacterial surface were ineffective in killing bacteria, whereas at 75 MPa, all four bacterial species were completely sterilized. The disinfection mechanism involved a high-velocity collision of nanodroplets with the bacteria, physically destroying them. Our results showed that disinfection using this technology could be an innovative method that is completely different from existing disinfection techniques., Importance: Although existing disinfection techniques demonstrate bactericidal effects through chemical reactions, concerns regarding human toxicity and environmental contamination have been raised. To the best of our knowledge, this study is the first in the world to reveal that the use of this technology, with nanodroplets of less than 100 nm, can destroy and sterilize bacterial cells by colliding with biofilm-forming bacteria at 75 MPa. Furthermore, because this technology uses only water, it can solve the problems of human toxicity and environmental contamination caused by existing disinfection techniques. Because of its minimal water usage, it can be employed for sanitation worldwide without being limited to specific regions. Our report proposes an unprecedented physical disinfection approach that utilizes a high-speed nanodroplet generation technology.

Purpose: Partial stereotactic ablative boost radiotherapy (P-SABR) effectively treats bulky lung cancer; however, the planning process for P-SABR requires repeated dose calculations. To improve planning efficiency, we proposed a novel deep learning method that utilizes limited data to accurately predict the three-dimensional (3D) dose distribution of the P-SABR plan for bulky lung cancer., Methods: We utilized data on 74 patients diagnosed with bulky lung cancer who received P-SABR treatment. The patient dataset was randomly divided into a training set (51 plans) with augmentation, validation set (7 plans), and testing set (16 plans). We devised a 3D multi-scale dilated network (MD-Net) and integrated a scale-balanced structure loss into the loss function. A comparative analysis with a classical network and other advanced networks with multi-scale analysis capabilities and other loss functions was conducted based on the dose distributions in terms of the axial view, average dose scores (ADSs), and average absolute differences of dosimetric indices (AADDIs). Finally, we analyzed the predicted dosimetric indices against the ground-truth values and compared the predicted dose-volume histogram (DVH) with the ground-truth DVH., Results: Our proposed dose prediction method for P-SABR plans for bulky lung cancer demonstrated strong performance, exhibiting a significant improvement in predicting multiple indicators of regions of interest (ROIs), particularly the gross target volume (GTV). Our network demonstrated increased accuracy in most dosimetric indices and dose scores in different ROIs. The proposed loss function significantly enhanced the predictive performance of the dosimetric indices. The predicted dosimetric indices and DVHs were equivalent to the ground-truth values., Conclusion: Our study presents an effective model based on limited datasets, and it exhibits high accuracy in the dose prediction of P-SABR plans for bulky lung cancer. This method has potential as an automated tool for P-SABR planning and can help optimize treatments and improve planning efficiency., (© 2024 The Author(s). Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Radiation colitis is one of the most common complications in patients undergoing pelvic radiotherapy and there is no effective treatment in the clinic. Therefore, searching for effective agents for the treatment of radiation colitis is urgently needed. Herein, it is found that the essential element selenium (Se) is protective against radiation colitis through inhibiting X-ray-induced apoptosis, cell cycle arrest, and inflammation with the involvement of balancing the generation of reactive oxygen species after the irradiation. Mechanistically, Se, especially for selenium nanoparticles (SeNPs), induced selenoprotein expression and then functioned to effectively restrain DNA damage response, which reduced X-ray-induced intestinal injury. Additionally, SeNPs treatment also restrained the cyclic GMP-AMP synthas (cGAS)- stimulator of interferon genes (STING)-TBK1-IRF3 signaling pathway cascade, thereby blocking the transcription of inflammatory cytokine gene, IL-6 and TNF-α, and thus alleviating inflammation. Moreover, inducing selenoprotein expression, such as GPX4, with SeNPs in vivo can regulate intestinal microenvironment immunity and gut microbiota to attenuate radiation-induced colitis by inhibiting oxidative stress and maintaining microenvironment immunity homeostasis. Together, these results unravel a previously unidentified modulation role that SeNPs restrained radiation colitis with the involvement of inducing selenoprotein expression but suppressing cGAS-STING-TBK1-IRF3 cascade., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Background and Purpose: Aneurysmal Subarachnoid Hemorrhage (aSAH) poses a significant health burden globally, necessitating a deeper understanding of its etiology and potential preventive strategies. Recent research has suggested a possible link between gut microbiota composition and the risk of vascularity, prompting investigation into this association using Mendelian Randomization (MR) analysis. Here, we aimed to elucidate the causal relationship between gut microbiota composition and aSAH risk utilizing MR analysis., Methods: We employed four distinct MR methodologies, including inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode, to assess the causal nexus between gut microbiota composition and aSAH risk. Genetic instrumental variables (IVs) associated with gut microbiome composition were selected from a comprehensive multiethnic genome-wide association study (GWAS) involving 18,473 individuals across diverse geographic regions. Sensitivity analyses were conducted to detect potential heterogeneity and pleiotropy., Results: Our Mendelian Randomization (MR) analyses unveiled a substantial and statistically significant causal relationship between gut microbiota composition and the risk of Aneurysmal Subarachnoid Hemorrhage (aSAH). Employing the Inverse Variance Weighted (IVW) method, we observed negative associations between aSAH and specific taxonomic levels of gut microbiota. Specifically, the IVW approach identified significant associations with one order, Victivallales (P IVW =0.047, OR: 0.78, 95 % CI: 0.62-0.99), one family, Porphyromonadaceae (P IVW =0.03, OR: 0.64, 95 % CI: 0.43-0.95), one class, Lentisphaeria (P IVW =0.047, OR: 0.78, 95 % CI: 0.62-0.99), and three genera: Bilophila (P IVW =0.02, OR: 0.68, 95 % CI: 0.50-0.93), Fusicatenibacter (P IVW =0.04, OR: 0.69, 95 % CI: 0.49-0.98), and Ruminococcus1 (P IVW =0.01, OR: 0.51, 95 % CI: 0.32-0.84). These findings were consistent across various MR methodologies, underscoring the robustness of our results. Sensitivity analyses further validated the stability of our findings, with no evidence of heterogeneity or pleiotropy detected., Conclusion: Our study provides compelling evidence supporting a causal relationship between gut microbiota composition and the risk of aSAH. These findings underscore the potential therapeutic implications of modulating gut microbiota to prevent and manage aSAH. Further research is warranted to explore the underlying mechanisms and develop targeted interventions aimed at mitigating aSAH risk through gut microbiota modulation., Competing Interests: Declaration of competing interest There have been no financial associations with any organization that may hold an interest in the submitted work. Additionally, there are no other relationships or activities that could be perceived as influencing the submitted work., (Copyright © 2024 Elsevier Inc. All rights reserved.)

In contrast to the high efficiency of room temperature phosphorescence in crystal states, the generally utilized nanoparticles of organic materials in bioimaging demonstrated sharply decreased performance by orders of magnitude under physiological conditions, badly limiting the realization of their unique advantages. This case, especially for organic red/near-infrared (NIR) phosphorescence materials, is not only the challenge present in reality but more importantly, for the theoretical problem of deeply understanding and avoiding the quenching effect by oxygen and water toward excited triplet states. Herein, thanks to the intelligent molecular design by the introduction of abundant hydrophobic chains and highly-branched structures, bright and persistent red/NIR phosphorescence under physiological conditions has been realized, which demonstrated the shielding effect towards oxygen, and strengthened the intermolecular interactions to suppress the non-radiative transitions. Accordingly, the record phosphorescence intensity of nanoparticles in bioimage, up to 8.21 ± 0.36 × 108 p s-1 cm-2 sr-1, was achieved, to realize the clear phosphorescence imaging of liver and tumors in living mice, even lymph nodes in rabbit models with high SBRs. This work afforded an efficient way to achieve the bright red/NIR phosphorescence nanoparticles, guiding their further applications in biology and medicine., (© 2024 Wiley‐VCH GmbH.)

Background: Aneurysmal subarachnoid hemorrhage (aSAH) represents a critical health concern characterized by elevated mortality and morbidity rates. Although both genetic predisposition and lifestyle choices influence aSAH susceptibility, understanding the causative associations between cigarette smoking, alcohol consumption, and aSAH risk remains imperative. Mendelian randomization (MR) offers a robust methodological framework for dissecting these associations, leveraging genetic variants as instrumental variables., Objective: In this study, a two-sample Mendelian randomization (TSMR) approach was employed to elucidate the causal connections between genetically determined cigarette smoking, alcohol consumption, and aSAH risk., Methods: Genetic instruments associated with cigarette smoking and alcohol consumption were sourced from the genome-wide association study (GWAS) and Sequencing Consortium of Alcohol and Nicotine use (GSCAN). Using a genome-wide association study (GWAS) dataset that encompassed aSAH cases and controls of European ancestry, TSMR, which utilized the inverse variance weighting (IVW) method, was employed to estimate the causal effects. Rigorous criteria were applied for selecting instrumental variables to ensure a robust Mendelian randomization analysis., Results: A significant causal association was found between genetically determined cigarette smoking and an increased risk of aSAH, with a 1-standard deviation (SD) increase in cigarette use genetically linked to a 96% relative risk elevation [OR-IVW = 1.96, 95% confidence interval (CI) = 1.28-3.01, p = 0.0021]. However, genetically determined alcohol consumption did not exhibit a statistically significant association with aSAH risk (OR-IVW = 1.22, 95% CI = 0.61-2.45, p = 0.578)., Conclusion: The Mendelian randomization analysis revealed a causal nexus between cigarette smoking and an increased risk of aSAH, advocating for targeted smoking cessation interventions within genetically predisposed cohorts. The results regarding the relationship between alcohol consumption and aSAH were affected by insufficient statistical power. A prudent interpretation of the findings highlights the limitations of Mendelian randomization in elucidating intricate genetic epidemiological relationships. Ongoing research involving larger cohort sizes and advanced methodological approaches is essential for comprehending the genetic underpinnings of aSAH., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Lin, Yin, Li, Liu, Long and Liao.)

Objectives: Implementing personalization protocol in clinical routine necessitates diverse low-dose PET/CT scan protocols. This study explores the clinical feasibility of one-third (1/3) dose regimen and evaluates the diagnostic image quality and lesion detectability of BMI-based 1/3-injection doses for 2-[ 18 F]FDG PET/CT imaging., Methods: Seventy-four cancer patients underwent total-body 2-[ 18 F]FDG PET/CT examination, with 37 retrospectively enrolled as full-dose group (3.7 MBq/kg) and 37 prospectively enrolled as the 1/3-dose group (1.23 MBq/kg). The 1/3-dose group was stratified by BMI, with an acquisition time of 5 min (G5), 6 min (G6), and 8 min (G8) for BMI < 25, 25 ≤ BMI ≤ 29, and BMI > 29, respectively. Image quality was subjectively and objectively assessed, and lesion detectability was quantitatively analyzed., Results: Subjective assessments of 1/3-dose and full-dose PET images showed strong agreement among readers (κ > 0.88). In the 1/3-dose group, the Likert scores were above 4. G5, G6, and G8 showed comparable image quality, with G5 demonstrating higher lesion conspicuity than G6 and G8 (p = 0.045). Objective evaluation showed no significant differences in SUV max , liver SUV mean and TBR between 1/3- and full-dose groups (p > 0.05). No statistical differences were observed in the SUV max of primary tumor, SUV mean of liver and TBR across all BMI categories between the 1/3-dose and full-dose groups. Lesion detection rates showed no significant difference between the 1/3-dose (93.24%, 193/207) and full-dose groups (94.73%, 198/209) (p = 0.520)., Conclusion: A BMI-stratified 1/3-dose regimen is a feasible low-dose alternative with clinically acceptable lesion detectability equivalent to full-dose protocol, potentially expanding the applicability of personalized protocols., Clinical Relevance Statement: This study demonstrated that BMI-stratified 1/3-dose regimens for [ 18 F]FDG total-body PET/CT yielded equivalent outputs compared to the full-dose regimen, which aligns with clinical needs for personalization in dose and BMI., Key Points: Currently, limited personalized low-dose total-body PET/CT protocols are available, particularly for patients with varied BMI. Reducing the radiotracer dose to 1/3 the standard demonstrated comparable image quality and lesion detectability equivalent to full dose. BMI-stratified 1/3-dose regimen is a clinically feasible low-dose alternative., (© 2024. The Author(s), under exclusive licence to European Society of Radiology.)

Objective: Recurrence is the leading cause of tumor-related death in retroperitoneal liposarcoma (RPLPS). Variant subtypes of RPLPS determine different recurrence 18F]-fluoro-2-deoxy-D-glucose (18F-FDG) PET/computed tomography (PET/CT). This study analyzed the characteristics of different histologic subtypes of 18F-FDG PET/CT and their associations with recurrence and prognosis., Methods: Clinical-pathological information, 18F-FDG PET/CT data, recurrence, and progression-free survivals (PFS) of 83 patients with RPLPS were collected. Maximum and peak standardized uptake values (SUVmax and SUVpeak, respectively) and mean CT value (CTmean) of tumors were measured and correlated with histologic subtype. The predictability of SUVmax, SUVpeak, and CTmean for the histologic subtype was evaluated using receiver operating characteristics (ROC) max and SUVpeak for recurrence. Kaplan-Meier analysis was performed to max and SUVpeak were risk factors for recurrence., Results: Studied patients with different types of liposarcomas. Dedifferentiated liposarcomas (DDLPS) had higher SUVmax and SUVpeak than well-differentiated (WDLPS) and myxoid/round cell (MLPS) types. WDLPS had lower CTmean values compared to MLPS and DDLPS. Using ROC curves, determined cut-off values for SUVmax (5.1) to differentiate DDLPS, SUVpeak (3.0) for WDLPS, and CTmean (12.3 Hu) for WDLPS. These cut-offs were found to be best for predicting recurrence. Kaplan-Meier analysis showed that histologic subtype, SUVmax, and SUVpeak were all linked to recurrence-free survival., Conclusions: The use of SUV and CT features on 18F-FDG PET/CT imaging may increase confidence in subtype diagnosis. Patients with SUVmax > 5.1 or SUVpeak > 3.0 suggest a poor prognosis., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

A biochemical pathway consists of a series of interconnected biochemical reactions to accomplish specific life activities. The participating reactants and resultant products of a pathway, including gene fragments, proteins, and small molecules, coalesce to form a complex reaction network. Biochemical pathways play a critical role in the biochemical domain as they can reveal the flow of biochemical reactions in living organisms, making them essential for understanding life processes. Existing studies of biochemical pathway networks are mainly based on experimentation and pathway database analysis methods, which are plagued by substantial cost constraints. Inspired by the success of representation learning approaches in biomedicine, we develop the biochemical pathway prediction (BPP) platform, which is an automatic BPP platform to identify potential links or attributes within biochemical pathway networks. Our BPP platform incorporates a variety of representation learning models, including the latest hypergraph neural networks technology to model biochemical reactions in pathways. In particular, BPP contains the latest biochemical pathway-based datasets and enables the prediction of potential participants or products of biochemical reactions in biochemical pathways. Additionally, BPP is equipped with an SHAP explainer to explain the predicted results and to calculate the contributions of each participating element. We conduct extensive experiments on our collected biochemical pathway dataset to benchmark the effectiveness of all models available on BPP. Furthermore, our detailed case studies based on the chronological pattern of our dataset demonstrate the effectiveness of our platform. Our BPP web portal, source code and datasets are freely accessible at https://github.com/Glasgow-AI4BioMed/BPP., (© The Author(s) 2024. Published by Oxford University Press.)

Understanding the genetic basis of disease is a fundamental aspect of medical research, as genes are the classic units of heredity and play a crucial role in biological function. Identifying associations between genes and diseases is critical for diagnosis, prevention, prognosis, and drug development. Genes that encode proteins with similar sequences are often implicated in related diseases, as proteins causing identical or similar diseases tend to show limited variation in their sequences. Predicting gene-disease association (GDA) requires time-consuming and expensive experiments on a large number of potential candidate genes. Although methods have been proposed to predict associations between genes and diseases using traditional machine learning algorithms and graph neural networks, these approaches struggle to capture the deep semantic information within the genes and diseases and are dependent on training data. To alleviate this issue, we propose a novel GDA prediction model named FusionGDA, which utilizes a pre-training phase with a fusion module to enrich the gene and disease semantic representations encoded by pre-trained language models. Multi-modal representations are generated by the fusion module, which includes rich semantic information about two heterogeneous biomedical entities: protein sequences and disease descriptions. Subsequently, the pooling aggregation strategy is adopted to compress the dimensions of the multi-modal representation. In addition, FusionGDA employs a pre-training phase leveraging a contrastive learning loss to extract potential gene and disease features by training on a large public GDA dataset. To rigorously evaluate the effectiveness of the FusionGDA model, we conduct comprehensive experiments on five datasets and compare our proposed model with five competitive baseline models on the DisGeNet-Eval dataset. Notably, our case study further demonstrates the ability of FusionGDA to discover hidden associations effectively. The complete code and datasets of our experiments are available at https://github.com/ZhaohanM/FusionGDA., (© The Author(s) 2024. Published by Oxford University Press.)

The properties of nanomaterials make them promising and advantageous for use in drug delivery systems, but challenges arise from the immune system's recognition of exogenous nanoparticles, leading to their clearance and reduced targeting efficiency. Drawing inspiration from nature, this paper explores biomimetic strategies to transform recognizable nanomaterials into a "camouflaged state." The focal point of this paper is the exploration of bionic nanoparticles, with a focus on cell membrane-coated nanoparticles. These biomimetic structures, particularly those mimicking red blood cells (RBCs), white blood cells (WBCs), platelets, and cancer cells, demonstrate enhanced drug delivery efficiency and prolonged circulation. This article underscores the versatility of these biomimetic structures across diverse diseases and explores the use of hybrid cell membrane-coated nanoparticles as a contemporary trend. This review also investigated exosomes and protein bionic nanoparticles, emphasizing their potential for specific targeting, immune evasion, and improved therapeutic outcomes. We expect that this continued development based on biomimetic nanomaterials will contribute to the efficiency and safety of disease treatment.

Objective. Domain adaptation has been recognized as a potent solution to the challenge of limited training data for electroencephalography (EEG) classification tasks. Existing studies primarily focus on homogeneous environments, however, the heterogeneous properties of EEG data arising from device diversity cannot be overlooked. This motivates the development of heterogeneous domain adaptation methods that can fully exploit the knowledge from an auxiliary heterogeneous domain for EEG classification. Approach. In this article, we propose a novel model named informative representation fusion (IRF) to tackle the problem of unsupervised heterogeneous domain adaptation in the context of EEG data. In IRF, we consider different perspectives of data, i.e. independent identically distributed (iid) and non-iid, to learn different representations. Specifically, from the non-iid perspective, IRF models high-order correlations among data by hypergraphs and develops hypergraph encoders to obtain data representations of each domain. From the non-iid perspective, by applying multi-layer perceptron networks to the source and target domain data, we achieve another type of representation for both domains. Subsequently, an attention mechanism is used to fuse these two types of representations to yield informative features. To learn transferable representations, the maximum mean discrepancy is utilized to align the distributions of the source and target domains based on the fused features. Main results. Experimental results on several real-world datasets demonstrate the effectiveness of the proposed model. Significance. This article handles an EEG classification situation where the source and target EEG data lie in different spaces, and what's more, under an unsupervised learning setting. This situation is practical in the real world but barely studied in the literature. The proposed model achieves high classification accuracy, and this study is important for the commercial applications of EEG-based BCIs., (© 2024 IOP Publishing Ltd.)

As a potential preclinical stage of Alzheimer's dementia, subjective cognitive decline (SCD) reveals a higher risk of future cognitive decline and conversion to dementia. However, it has not been clear whether SCD status increases the clinical progression of older adults in the context of amyloid deposition, cerebrovascular disease (CeVD), and psychiatric symptoms. We identified 99 normal controls (NC), 15 SCD individuals who developed mild cognitive impairment in the next 2 years (P-SCD), and 54 SCD individuals who did not (S-SCD) from ADNI database with both baseline and 2-year follow-up data. Total white matter hyperintensity (WMH), WMH in deep (DWMH) and periventricular (PWMH) regions, and voxel-wise grey matter volumes were compared among groups. Furthermore, using structural equation modelling method, we constructed path models to explore SCD-related brain changes longitudinally and to determine whether baseline SCD status, age, and depressive symptoms affect participants' clinical outcomes. Both SCD groups showed higher baseline amyloid PET SUVR, baseline PWMH volumes, and larger increase of PWMH volumes over time than NC. In contrast, only P-SCD had higher baseline DWMH volumes and larger increase of DWMH volumes over time than NC. No longitudinal differences in grey matter volume and amyloid was observed among NC, S-SCD, and P-SCD. Our path models demonstrated that SCD status contributed to future WMH progression. Further, baseline SCD status increases the risk of future cognitive decline, mediated by PWMH; baseline depressive symptoms directly contribute to clinical outcomes. In conclusion, both S-SCD and P-SCD exhibited more severe CeVD than NC. The CeVD burden increase was more pronounced in P-SCD. In contrast with the direct association of depressive symptoms with dementia severity progression, the effects of SCD status on future cognitive decline may manifest via CeVD pathologies. Our work highlights the importance of multi-modal longitudinal designs in understanding the SCD trajectory heterogeneity, paving the way for stratification and early intervention in the preclinical stage. PRACTITIONER POINTS: Both S-SCD and P-SCD exhibited more severe CeVD at baseline and a larger increase of CeVD burden compared to NC, while the burden was more pronounced in P-SCD. Baseline SCD status increases the risk of future PWMH and DWMH volume accumulation, mediated by baseline PWMH and DWMH volumes, respectively. Baseline SCD status increases the risk of future cognitive decline, mediated by baseline PWMH, while baseline depression status directly contributes to clinical outcome., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Lu doped Hf 0.5 Zr 0.5 O 2 (HZO) ferroelectric films were prepared on Pt/TiN/SiO 2 /Si substrate by chemical solution deposition method, and an interfacial engineering strategy for improving the ferroelectric property was explored by capping the Lu doped HZO films with a cerium oxide layer. Compared with the Lu doped HZO film without the CeO x coating layer, the Lu doped HZO film with the CeO x coating layer has a larger remanent polarization (2 P r = 34.72 µ C cm -2 ) and presents weaker wake-up behavior, which result from the higher orthogonal phase ratio and the lower oxygen vacancy of the CeO x coated Lu doped HZO film. In addition, the CeO x coating can remarkably improve the fatigue resistance and retention performance of the Lu doped HZO films. It is hoped that the results can provide an effective approach for the realization of high-performance and highly reliable hafnium oxide based ferroelectric thin films., (© 2024 IOP Publishing Ltd.)

Functional brain networks have preserved architectures in rest and task; nevertheless, previous work consistently demonstrated task-related brain functional reorganization. Efficient rest-to-task functional network reconfiguration is associated with better cognition in young adults. However, aging and cognitive load effects, as well as contributions of intra- and internetwork reconfiguration, remain unclear. We assessed age-related and load-dependent effects on global and network-specific functional reconfiguration between rest and a spatial working memory (SWM) task in young and older adults, then investigated associations between functional reconfiguration and SWM across loads and age groups. Overall, global and network-level functional reconfiguration between rest and task increased with age and load. Importantly, more efficient functional reconfiguration associated with better performance across age groups. However, older adults relied more on internetwork reconfiguration of higher cognitive and task-relevant networks. These reflect the consistent importance of efficient network updating despite recruitment of additional functional networks to offset reduction in neural resources and a change in brain functional topology in older adults. Our findings generalize the association between efficient functional reconfiguration and cognition to aging and demonstrate distinct brain functional reconfiguration patterns associated with SWM in aging, highlighting the importance of combining rest and task measures to study aging cognition., Competing Interests: Competing Interests: The authors have declared that no competing interests exist., (© 2024 Massachusetts Institute of Technology.)

High performance solution-processable deep-blue emitters with a Commission International de l'Eclairage (CIE) coordinate of CIE y ≤0.08 are highly desired in ultrahigh-definition display. Although, deep-blue materials with hybridized local and charge-transfer (HLCT) excited-state feature are promising candidates, their rigidity and planar molecular structures limit their application in solution-processing technique. Herein, four novel deep-blue solution-processable HLCT emitters were first proposed by attaching rigid imide aliphatic rings as functional units onto the HLCT emitting core. The functional units not only improve solubility, enhance thermal properties and morphological stability of the emitting core, but also promote photoluminescence efficiency, balance charge carrier transport, and inhibit aggregation-caused quenching effect due to the weak electron-withdrawing property as well as steric hindrance. The corresponding solution-processable organic light-emitting diodes (OLEDs) substantiate an unprecedented maximum external quantum efficiency (EQE max ) of 11.5 % with an emission peak at 456 nm and excellent colour purity (full width at half maximum=56 nm and CIE y =0.09). These efficiencies represent the state-of-the-art device performance among the solution-processable blue OLEDs based on the "hot exciton" mechanism. This simple strategy opens up a new avenue for designing highly efficient solution-processable deep-blue organic luminescent materials., (© 2024 Wiley-VCH GmbH.)

Compact routing of multimode bus waveguides is of great significance for on-chip mode-division multiplexing (MDM) systems to realize high integration density and flexible layout. In this Letter, we propose and experimentally demonstrate a novel, to the best of our knowledge, multimode photonic jumper (MPJ) on a standard silicon-on-insulator (SOI) platform. It enables an ultra-compact connection between two parallel multimode waveguides (MWGs) with an arbitrary displacement. As a proof of concept, we describe two MPJs with displacements of 5.9 µm and 0.6 µm, each supporting three modes and featuring a longitudinal distance of around 14 µm. For both MPJs, the experimental results show insertion losses (ILs) below 0.086 dB and inter-modal cross talk (CT) below -17.6 dB over the wide wavelength range of 1525-1600 nm for all three modes.

Choroidal neovascularization (CNV), characterized as a prominent feature of wet age-related macular degeneration (AMD), is a primary contributor to visual impairment and severe vision loss globally, while the prevailing treatments are often unsatisfactory. The development of conventional treatment strategies has largely been based on the understanding that the angiogenic switch of endothelial cells is dictated by angiogenic growth factors alone. Even though treatments targeting vascular endothelial growth factor (VEGF), like Ranibizumab, are widely administered, more than half of the patients still exhibit inadequate or null responses, emphasizing the imperative need for solutions to this problem. Here, aiming to explore therapeutic strategies from a novel perspective of endothelial cell metabolism, a biocompatible nanomedicine delivery system is constructed by loading RGD peptide-modified liposomes with 2-deoxy-D-glucose (RGD@LP-2-DG). RGD@LP-2-DG displayed good targeting performance towards endothelial cells and excellent in vitro and in vivo inhibitory effects on neovascularization were demonstrated. Moreover, our mechanistic studies revealed that 2-DG interfered with N-glycosylation, leading to the inhibition of vascular endothelial growth factor receptor 2 (VEGFR2) and its downstream signaling. Notably, the remarkable inhibitory effect on neovascularization and biocompatibility of RGD@LP-2-DG render it a highly promising and clinically translatable therapeutic candidate for the treatment of wet AMD and other angiogenic diseases, particularly in patients who are unresponsive to currently available treatments., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

Vector autoregressive (VAR) modelling is widely employed in psychology for time series analyses of dynamic processes. However, the typically short time series in psychological studies can lead to overfitting of VAR models, impairing their predictive ability on unseen samples. Cross-validation (CV) methods are commonly recommended for assessing the predictive ability of statistical models. However, it is unclear how the performance of CV is affected by characteristics of time series data and the fitted models. In this simulation study, we examine the ability of two CV methods, namely,10-fold CV and blocked CV, in estimating the prediction errors of three time series models with increasing complexity (person-mean, AR, and VAR), and evaluate how their performance is affected by data characteristics. We then compare these CV methods to the traditional methods using the Akaike (AIC) and Bayesian (BIC) information criteria in their accuracy of selecting the most predictive models. We find that CV methods tend to underestimate prediction errors of simpler models, but overestimate prediction errors of VAR models, particularly when the number of observations is small. Nonetheless, CV methods, especially blocked CV, generally outperform the AIC and BIC. We conclude our study with a discussion on the implications of the findings and provide helpful guidelines for practice., (© 2023 The Authors. British Journal of Mathematical and Statistical Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.)

Background: It is controversial that Helicobacter pylori (H pylori) is involved in the pathogenesis or development of laryngopharyngeal reflux disease (LPRD)., Objective: To investigate the potential association between LPRD and H pylori infection., Material and Methods: A systematic review was performed of studies assessing the diagnosis or treatment of LPRD among patients with H pylori infection. Data sources are PubMed/MEDLINE, EMBASE[Ovid], Cochrane Library, and Web of Science, and ClinicalTrials.gov., Results: Fifteen studies were analyzed in the review, with all eligible for the meta-analysis. A significant association between H pylori infection and LPRD was detected for higher rates of H pylori infection in patients with LPRD than in non-LPRD patients (relative risk (RR), 1.35; 95% CI, 1.12-1.63; P = 0.002), and H pylori-positive patients had a higher prevalence of LPRD than H pylori-negative patients (RR, 1.19; 95% CI, 1.07-1.31; P = 0.001). The prevalence of H pylori among patients with LPRD was 49% (95% CI, 36-61), the prevalence of H pylori among patients with non-LPRD was 35% (95% CI, 23-49)., Conclusion and Significance: The limited evidence indicated the association between LPRD risk and increased H pylori infection. Different population races, diagnostic approach to LPRD, variant H pylori testing methods, age and sex may contribute to the heterogeneity. Further well-designed studies regarding the efficacy of H pylori eradication in the treatment of LPRD are strongly recommended in the future., Competing Interests: Declaration of Competing Interest None., (Copyright © 2024 The Voice Foundation. Published by Elsevier Inc. All rights reserved.)

Background: In the COVID-19 epidemic more patients presented with persistent postural-perceptual dizziness (PPPD), but it has received little attention by the doctors in China and many patients reject psychological measurements or scales. Therefore, there is an urgent need for an objective method to diagnose and evaluate PPPD., Objective: To investigate the effect of the COVID-19 epidemic on elderly PPPD patients and define the relationship between prefrontal alpha rhythm asymmetry (FAA) by Electroencephalography (EEG) and PPPD., Methods: This case-control study was conducted to discuss the differences of elderly outpatients (>60 years) with PPPD during the peak period of COVID-19 in 2020 and the corresponding period in 2019, and collect the prefrontal FAA value in PPPD during COVID-19 outbreak, which were compared to its FAA in healthy control., Results: Compared with the same period in 2019, the number of elderly PPPD patients during the epidemic period in 2020 increased significantly (16.4%, p  = 0.000, x 2  =31.802) . The left alpha wave signal power (F3) was significantly higher than the right alpha wave signal power (F4) ( Z = -3.073, p  = 0.002). In PPPD patients FAA were significantly lower in patients compared to control group ( Z = -11.535, p  = 0.000). There was a negative correlation between FAA and HAMA scores ( R 2  =0.906, p  < 0.05) and a negative correlation between FAA and HAMD scores ( R 2  =0.859, p  < 0.05), too., Conclusions: The increase in cases of elderly PPPD patients is most likely attributed to the mental health in older adults during the COVID-19 pandemic. Less left frontal brain activity in EEG may be related to elderly PPPD.

This paper delves into the problem of correlated time-series forecasting in practical applications, an area of growing interest in a multitude of fields such as stock price prediction and traffic demand analysis. Current methodologies primarily represent data using conventional graph structures, yet these fail to capture intricate structures with non-pairwise relationships. To address this challenge, we adopt dynamic hypergraphs in this study to better illustrate complex interactions, and introduce a novel hypergraph neural network model named CHNN for correlated time series forecasting. In more detail, CHNN leverages both semantic and topological similarities via an interaction model and hypergraph diffusion process, thereby constructing comprehensive collaborative correlation scores that effectively guide spatial message propagation. In addition, it incorporates short-term temporal information to generate efficient spatio-temporal feature maps. Lastly, a long-term temporal module is proposed to generate future predictions utilizing both temporal attention and a gated recurrent network. Comprehensive experiments conducted on four real-world datasets, i.e., Tiingo, Stocktwits, NYC-Taxi, and Social Network demonstrate that the proposed CHNN markedly outperforms a range of benchmark methods.

This multi-method longitudinal study sought to investigate linkage in parental neuroendocrine functioning - indicated by cortisol - over two measurement occasions. In addition, we examined how parental cortisol linkage may operate as an intermediate factor in the cascade of contextual risks and parenting. Participants were 235 families with a young child (Mage = 33.56, 36.00 years for mothers and fathers respectively), who were followed for two annual measurement occasions. Parental cortisol linkage was measured around a laboratory conflict discussion task at both measurement occasions (i.e., pre-discussion, 20- and 40-minute post-discussion for each measurement occasion). Maternal and paternal parenting behavior was observed during a parent-child discipline discussion task. Findings indicated similar levels of cortisol linkage between parents over the two measurement occasions. Furthermore, cortisol linkage between parents operated as an intermediate factor between contextual risks and more compromised parenting behavior. That is, greater contextual risks, indicated by greater neighborhood risk and interparental conflict, were linked to greater cortisol linkage between parents over time, which was in turn linked to greater authoritarian parenting during parent-child interaction. Findings highlighted the importance of understanding physiological-linkage processes with respect to the impact of contextual risks on family functioning and may have crucial implications for clinical work.

A notable ambiguity persists concerning whether distinct forms of parent-child triangulation (unstable coercive coalition, stable coalition, detouring-attacking, detouring supportive, parentification) might mediate the association between interparental conflict and early adolescent depressive symptoms similarly within the context of Chinese Confucianism. Filling this research gap, this study aimed to examine the mediating role of the five dimensions of parent-child triangulation in the association between interparental conflict and early adolescent depressive symptoms, as well as the moderating effect of grandparent support on this mediating pathway. Data were drawn from a sample of 761 Chinese adolescents (M age  = 12.82 ± 0.47, 49.1% girls). Structural equation model analyses indicated that unstable coercive coalition, stable coalition, and detouring-attacking behaviors partially mediated the association between interparental conflict and adolescent depressive symptoms, while detouring-supportive behaviors and parentification did not demonstrate such mediating effects. Unlike Western societies, a negative correlation was observed between interparental conflict and parentification in the context of China. Grandparent support mitigated the adverse effects of both interparental conflict and the unstable coercive coalition on early adolescent depressive symptoms., (© 2023. The Author(s).)

On-chip polarization handling is of great significance for optical interconnects to overcome polarization sensitivity. In this Letter, we propose and experimentally demonstrate a novel, to the best of our knowledge, on-chip polarization controller (PC) on a 220 nm silicon-on-insulator (SOI) platform. It is the first demonstration of a PC based on micro-ring resonators. Any input polarization states can be actively converted to the standard transverse-electric (TE) mode under the phase manipulation. Experimental results show that the insertion loss is less than 0.8 dB and the polarization dependent loss (PDL) is around 0.5 dB. The proposed device also exhibits excellent performances in wavelength tunability over the C band and 35 Gbps data transmission.

Diffuse correlation spectroscopy faces challenges concerning the contamination of cutaneous and deep tissue blood flow. We propose a long short-term memory network to directly quantify the flow rates of shallow and deep-layer tissues. By exploiting the different contributions of shallow and deep-layer flow rates to auto-correlation functions, we accurately predict the shallow and deep-layer flow rates (RMSE = 0.047 and 0.034 ml/min/100 g of simulated tissue, R 2  = 0.99 and 0.99, respectively) in a two-layer flow phantom experiment. This approach is useful in evaluating the blood flow responses of active muscles, where both cutaneous and deep-muscle blood flow increase with exercise., Competing Interests: The authors declare no conflicts of interest., (© 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.)

MicroRNAs (miRNAs) silence genes by binding to messenger RNAs, whereas long non-coding RNAs (lncRNAs) act as competitive endogenous RNAs (ceRNAs) that can relieve miRNA silencing effects and upregulate target gene expression. The ceRNA association between lncRNAs and miRNAs has been a research hotspot due to its medical importance, but it is challenging to verify experimentally. In this paper, we propose a novel deep learning scheme, i.e. sequence pre-training-based graph neural network (SPGNN), that combines pre-training and fine-tuning stages to predict lncRNA-miRNA associations from RNA sequences and the existing interactions represented as a graph. First, we utilize a sequence-to-vector technique to generate pre-trained embeddings based on the sequences of all RNAs during the pre-training stage. In the fine-tuning stage, we use Graph Neural Network to learn node representations from the heterogeneous graph constructed using lncRNA-miRNA association information. We evaluate our proposed scheme SPGNN on our newly collected animal lncRNA-miRNA association dataset and demonstrate that combining the $k$-mer technique and Doc2vec model for pre-training with the Simple Graph Convolution Network for fine-tuning is effective in predicting lncRNA-miRNA associations. Our approach outperforms state-of-the-art baselines across various evaluation metrics. We also conduct an ablation study and hyperparameter analysis to verify the effectiveness of each component and parameter of our scheme. The complete code and dataset are available on GitHub: https://github.com/zixwang/SPGNN., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Circular RNA (CircRNA) is a type of non-coding RNAs in which both ends are covalently linked. Researchers have demonstrated that many circRNAs can act as biomarkers of diseases. However, traditional experimental methods for circRNA-disease associations identification are labor-intensive. In this work, we propose a novel method based on the heterogeneous graph neural network and metapaths for circRNA-disease associations prediction termed as HMCDA. First, a heterogeneous graph consisting of circRNA-disease associations, circRNA-miRNA associations, miRNA-disease associations and disease-disease associations are constructed. Then, six metapaths are defined and generated according to the biomedical pathways. Afterwards, the entity content transformation, intra-metapath and inter-metapath aggregation are implemented to learn the embeddings of circRNA and disease entities. Finally, the learned embeddings are used to predict novel circRNA-disase associations. In particular, the result of extensive experiments demonstrates that HMCDA outperforms four state-of-the-art models in fivefold cross validation. In addition, our case study indicates that HMCDA has the ability to identify novel circRNA-disease associations., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Colorless polyimides (CPIs) are a key substrate material for flexible organic light-emitting diode (OLED) displays and have attracted worldwide attention. Here, in this paper, the dispersion and interfacial interaction of aromatic polyamide (PA) in CPI (synthesized from 4,4'-(hexafluoroisopropylidene) diphthalic anhydride (6FDA) and 2,2'-bis(trifluoromethyl)benzidine (TFMB)) were significantly improved by in situ polymerization, and colorless transparent macromolecular polyimide composites (CPI-PA x ) were successfully prepared by PA and CPI. By adjusting the ratio of PA to CPI, a high-performance engineering plastic with excellent film-forming properties was obtained. Molecular simulations confirmed the uniform distribution of PA in CPI and its interaction in polymers. In CPI-PA x , the CPI was locked by the PA chain, and numerous molecular chains were mutually entangled to form a hydrogen-bond network structure. Due to the strong interaction between the chains imparted by the hydrogen bonds of the PA, they do not slide under external forces and heating. In addition, the additive PA has excellent dimensional stability, thermal, and mechanical properties, and CPI has outstanding optical properties, so the synthesized CPI-PA x combines the comprehensive properties of PA and CPI. The CPI-PA x has excellent thermal and mechanical properties, with a thermal decomposition temperature of 499 °C, a glass transition temperature of 385 °C, a coefficient of thermal expansion of 0.8 ppm K -1 , a tensile strength of 50.9 MPa, and an elastic modulus of 3.9 GPa. Particularly, CPI-PA x has a 90% transmittance in the visible region. These data prove that the strategy of combining PA and CPI by in situ polymerization is an effective method to circumvent the bottleneck of CPI in the current flexible window application, and this design strategy is universal.

Salt mines feature both autochthonous and allochthonous microbial communities introduced by industrialization. It is important to generate the information on the diversity of the microbial communities present in the salt mines and how they are shaped by the environment representing ecological diversification. Brine from Mahai potash mine (Qianghai, China), an extreme hypersaline environment, is used to produce potash salts for hundreds of millions of people. However, halophiles preserved in this niche during deposition are still unknown. In this study, using high-throughput 16S rRNA gene amplicon sequencing and estimation of physicochemical variables, we examined brine samples collected from locations with the gradient of industrial activity intensity and discrete hydrochemical compositions in the Mahai potash mine. Our findings revealed a highly diverse bacterial community, mainly composed of Pseudomonadota in the hypersaline brines from the industrial area, whereas in the natural brine collected from the upstream Mahai salt lake, most of the 16S rRNA gene reads were assigned to Bacteroidota . Halobacteria and halophilic methanogens dominated archaeal populations. Furthermore, we discovered that in the Mahai potash mining area, bacterial communities tended to respond to anthropogenic influences. In contrast, archaeal diversity and compositions were primarily shaped by the chemical properties of the hypersaline brines. Conspicuously, distinct methanogenic communities were discovered in sets of samples with varying ionic compositions, indicating their strong sensitivity to the brine hydrochemical alterations. Our findings provide the first taxonomic snapshot of microbial communities from the Mahai potash mine and reveal the different responses of bacteria and archaea to environmental variations in this high-altitude aquatic ecosystem.

All‑trans retinoic acid (ATRA) has been implicated in the differentiation of hepatic stellate cells (HSCs). In the present study, the liver‑targeting hyaluronic acid micelles (ADHG) were prepared for co‑delivery of ATRA and doxorubicin (DOX) to block the HSC‑hepatoma interrelation. To simulate the tumor microenvironment, an in vitro dual‑cell model and an in vivo co‑implantation mouse model were established for anticancer studies. The experimental methods involved the MTT assay, wound‑healing assay, cellular uptake, flow cytometry and and in vivo antitumor study. The results revealed that the HSCs in the research models notably promoted tumor proliferation and migration. Furthermore, ADHG were readily internalized by cancer cells and HSCs simultaneously, and widely distributed in cancer regions. The in vivo antitumor studies demonstrated that ADHG could notably decrease HSC activation and extracellular matrix deposition, as well as constrain tumor growth and metastasis. Therefore, ATRA could facilitate DOX‑induced anti‑proliferation and anti‑metastasis effects, and ADHG are a promising nano‑sized formulation for the combination therapy of hepatocellular carcinoma.

Comprehensively regulating the TME is now regarded as a promising approach for cancer treatment. Herein, a novel "three-in-one" effect is presented for simultaneously killing tumor cells, inhibiting the EMT of CAFs, and improving immune responses. In this study, bortezomib (BTZ) is selected for the treatment of breast cancer; it has multiple pharmacological mechanisms for killing tumor cells through the NF-κB signaling pathway, inhibiting the activity of CAFs by activating caspase-3, and enhancing the function of CD8+ T cells by regulating the expression of immune-stimulating factors. To improve the druggability of BTZ in solid tumors, BTZ-loaded lipid/glycocholic acid mixed micelles (BTZ-LGs) were prepared to verify the "three-in-one" effect in killing tumor cells, inhibiting CAFs, and improving immune responses. In the present work, BTZ-LGs were verified to show enhanced in vitro cytotoxicity in both 4T1 cells and 4T1/NIH3T3 co-cultured cells, as well as a superior in vivo treatment effect in different tumor-bearing mouse models. Additionally, BTZ-LGs could regulate the expression of α-SMA, caspase-3, E-cadherin, and N-cadherin, indicating their good inhibiting ability on both tumor cells and CAFs. More importantly, immunological analysis revealed that BTZ-LGs promoted the expression of the immunostimulatory factor IL-2 in tumor tissues, activated anti-tumor T cells, and overcame tumor-induced CD8+ T cell dysfunction. All these findings suggest that BTZ-LGs can achieve a "three-in-one" effect in terms of killing tumor cells, suppressing CAFs, and improving immune responses. This simple and multi-effective therapeutic strategy offers a promising approach for cancer therapy.

Background and Objectives: There is an increasing awareness of the "Heart-Brain Connection," whereby cardiovascular function is connected with cognition. Diffusion-MRI studies reported higher brain free water (FW) was associated with cerebrovascular disease (CeVD) and cognitive impairment. In this study, we investigated whether higher brain FW was related to blood cardiovascular biomarkers and whether FW mediated the associations between blood biomarkers and cognition., Methods: Participants recruited from 2 Singapore memory clinics between 2010 and 2015 underwent collection of blood samples and neuroimaging at baseline and longitudinal neuropsychological assessments up to 5 years. We examined the associations of blood cardiovascular biomarkers (high-sensitivity cardiac troponin-T [hs-cTnT], N-terminal pro-hormone B-type natriuretic peptide [NT-proBNP], and growth/differentiation factor 15 [GDF-15]) with brain white matter (WM) and cortical gray matter (GM) FW derived from diffusion MRI using whole brain voxel-wise general linear regression. We then assessed the relationships among baseline blood biomarkers, brain FW, and cognitive decline using path models., Results: A total of 308 older adults (76 with no cognitive impairment, 134 with cognitive impairment no dementia, and 98 with Alzheimer disease dementia and vascular dementia; mean [SD] age: 72.1 [8.3]) were included. We found that blood cardiovascular biomarkers were associated with higher FW in widespread WM regions and in specific GM networks including the default mode, executive control, and somatomotor networks at baseline ( p < 0.01, family-wise error corrected). Baseline FW in widespread WM and network-specific GM fully mediated the associations of blood biomarkers with longitudinal cognitive decline over 5 years. Specifically, in GM, higher FW in the default mode network mediated the relationship with memory decline (hs-cTnT: β = -0.115, SE = 0.034, p = 0.001; NT-proBNP: β = -0.154, SE = 0.046, p = 0.001; GDF-15: β = -0.073, SE = 0.027, p = 0.006); by contrast, higher FW in the executive control network was responsible for executive function decline (hs-cTnT: β = -0.126, SE = 0.039, p = 0.001; NT-proBNP: β = -0.110, SE = 0.038, p = 0.004; GDF-15: β = -0.117, SE = 0.035, p = 0.001). Similar full mediation effects of brain FW were also identified for baseline cognition., Discussion: Results suggested a role of brain FW in linking cardiovascular dysfunction to cognitive decline. These findings provide new evidence for brain-heart interactions, paving the way for prediction and monitoring of domain-specific cognitive trajectory., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

With the increased use of time series data in human research, ranging from ecological momentary assessments to data passively obtained, researchers can explore dynamic processes more than ever before. An important question researchers must ask themselves is, do I think all individuals have similar processes? If not, how different, and in what ways? Dr. Peter Molenaar's work set the foundation to answer these questions by providing insight into individual-level analysis for processes that are assumed to differ across individuals in at least some aspects. Currently, such assumptions do not have a clear taxonomy regarding the degree of homogeneity in the patterns of relations among variables and the corresponding parameter values. This paper provides the language with which researchers can discuss assumptions inherent in their analyses. We define strict homogeneity as the assumption that all individuals have an identical pattern of relations as well as parameter values; pattern homogeneity assumes the same pattern of relations but parameter values can differ; weak homogeneity assumes there are some (but not all) generalizable aspects of the process; and no homogeneity explicitly assumes no population-level similarities in dynamic processes across individuals. We demonstrate these assumptions with an empirical data set of daily emotions in couples.

To improve the lithium-ion transporting ability in lithium-ion batteries, a high-performance polyimide-based lithium-ion battery separator (PI-mod) was prepared by chemically grafting poly(ethylene glycol) (PEG) onto the surface of a heat-resistant polyimide nanofiber matrix with the assistance of amino-rich polyethyleneimine (PEI). The resulted PEI-PEG polymer coating exhibited unique gel-like properties with an electrolyte uptake rate of 168%, an area resistance as low as 2.60 Ω·cm 2 , and an ionic conductivity up to 2.33 mS·cm -1 , which are 3.5, 0.10, and 12.3 times that of the commercial separator Celgard 2320, respectively. Meanwhile, the heat-resistant polyimide skeleton can effectively avoid thermal shrinkage of the modified separator even after 200 °C treatment for 0.5 h, which ensures the safety of the battery working under extreme conditions. The modified PI separator possessed a high electrochemical stability window of 4.5 V. Compared with the batteries from the commercial separator Celgard 2320 and the pure polyimide matrix, the assembled coin cell with the PI-mod separator showed much better rate capabilities and capacity retention due to the high electrolyte affinity of the PEI-PEG polymer coating. The developed strategy of using the electrolyte-swollen polymer to modify the thermal-resistant separator network provides an efficient way for establishing high-power lithium-ion batteries with good safety performance.

Psychotic symptoms occur in a majority of schizophrenia patients and in ~50% of all Parkinson's disease (PD) patients. Altered grey matter (GM) structure within several brain areas and networks may contribute to their pathogenesis. Little is known, however, about transdiagnostic similarities when psychotic symptoms occur in different disorders, such as in schizophrenia and PD. The present study investigated a large, multicenter sample containing 722 participants: 146 patients with first episode psychosis, FEP; 106 individuals in at-risk mental state for developing psychosis, ARMS; 145 healthy controls matching FEP and ARMS, Con-Psy; 92 PD patients with psychotic symptoms, PDP; 145 PD patients without psychotic symptoms, PDN; 88 healthy controls matching PDN and PDP, Con-PD. We applied source-based morphometry in association with receiver operating curves (ROC) analyses to identify common GM structural covariance networks (SCN) and investigated their accuracy in identifying the different patient groups. We assessed group-specific homogeneity and variability across the different networks and potential associations with clinical symptoms. SCN-extracted GM values differed significantly between FEP and Con-Psy, PDP and Con-PD, PDN and Con-PD, as well as PDN and PDP, indicating significant overall grey matter reductions in PD and early schizophrenia. ROC analyses showed that SCN-based classification algorithms allow good classification (AUC ~0.80) of FEP and Con-Psy, and fair performance (AUC ~0.72) when differentiating PDP from Con-PD. Importantly, the best performance was found in partly the same networks, including the thalamus. Alterations within selected SCNs may be related to the presence of psychotic symptoms in both early schizophrenia and PD psychosis, indicating some commonality of underlying mechanisms. Furthermore, results provide evidence that GM volume within specific SCNs may serve as a biomarker for identifying FEP and PDP., (© 2023. The Author(s).)

Background: Currently, the most common surgical modalities used for recurrent respiratory papillomatosis (RRP) resection are microdebrider, carbon dioxide (CO 2 ) laser and potassium-titanyl-phosphate (KTP) laser. However, complication rates vary among different surgical modalities and have been controversial in different studies., Objective of Review: This study systematically reviews the available studies which reported intra-operative and post-operative complications, aiming to compare the safety of microdebrider, CO 2 laser and KTP laser., Type of Review: Meta-analysis., Search Strategy: Seven electronic databases (PubMed/MEDLINE, EMBASE[Ovid], Scopus, Cochrane Library and Web of Science) were searched from inception through 28 April 2022. Randomised controlled, prospective or retrospective observational studies that recorded the complications of three different surgical modalities for RRP resection were included in the meta-analysis., Evaluation Method: Outcomes of interest were intra-operative and post-operative complications, and complication rate was calculated to evaluate the safety of surgical methods., Results: Twenty different studies were included in quantitative synthesis. Only one study compared outcomes of those three kinds of treatment modalities simultaneously, two studies compared microdebrider and CO 2 laser, and the remaining studies focussed on only one of three treatments. The weighted average complication rate for microdebrider was 0.03 (95% confidence interval [CI] 0.00-0.21), n = 6, for CO 2 laser treatment was 0.16 (95% CI 0.09-0.25), n = 14 and for KTP laser treatment was 0.04 (95% CI 0.00-0.14), n = 4., Conclusion: The limited evidence demonstrated that CO 2 lasers in the surgical treatment of RRP may lead to more surgical complications, and microdebrider and KTP lasers may be safer. However, the heterogeneous data limit any strong comparison of outcomes of different treatment of laryngeal papillomas. Future randomised controlled trials that directly compare the safety of different surgical modalities are needed., (© 2022 John Wiley & Sons Ltd.)

Clear cell renal cell carcinoma (ccRCC), the most common malignant subtype of renal cell carcinoma, is characterized by the accumulation of lipid droplets in the cytoplasm. RNASET2 is a protein coding gene with a low expression level in ovarian cancers, but it is overexpressed in poorly differentiated neuroendocrine carcinomas. There is a correlation between RNASET2 upregulation and triglyceride expression levels in human serum but is unknown whether such an association is a factor contributing to lipid accumulation in ccRCC. Herein, we show that RNASET2 expression levels in ccRCC tissues and cell lines are significantly higher than those in both normal adjacent tissues and renal tubular epithelial cells. Furthermore, its upregulation is associated with increases in ccRCC malignancy and declines in patient survival. We also show that an association exists between increases in both cytoplasmic lipid accumulation and HIF-2α transcription factor upregulation, and increases in both RNASET2 and triglyceride expression levels in ccRCC tissues. In addition, DGAT1 and DGAT2, two key enzymes involved in triglyceride synthesis, are highly expressed in ccRCC tissues. By contrast, RNASET2 knockdown inhibited their expression levels and lowered lipid droplet accumulation, as well as suppressing in vitro cell proliferation, cell invasion, and migration. In conclusion, our data suggest HIF2α upregulates RNASET2 transcription in ccRCC cells, which promotes both the synthesis of triglycerides and ccRCC migration. As such, RNASET2 may have the potential as a biomarker or target for the diagnosis and treatment of ccRCC., (© 2023 The Authors. FEBS Open Bio published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Hybridized local and charge-transfer (HLCT) emitters have attracted extensive attention, but the insolubility and severe self-aggregation tendency restrict their applications in solution-processable organic light-emitting diodes (OLEDs), particularly deep-blue OLEDs. Herein, two novel benzoxazole-based solution-processable HLCT emitters (BPCP and BPCPCHY) are designed and synthesized, in which benzoxazole acts as an acceptor, carbazole acts as a donor, and hexahydrophthalimido (HP, with a large intramolecular torsion angle and spatial distortion characteristics) acts as a bulky modified end-group with weak electron-withdrawing effects. Both BPCP and BPCPCHY exhibit HLCT characteristics and emit near ultraviolet in toluene at 404 and 399 nm. Compared to the BPCP, the BPCPCHY solid shows much better thermal stability ( T g , 187 vs 110 °C), higher oscillator strengths of the S 1 -to-S 0 transition (0.5346 vs 0.4809), and faster k r (1.1 × 10 8 vs 7.5 × 10 7 s -1 ) and thus a much higher Φ PL in the neat film. The introduction of HP groups greatly suppresses the intra-/intermolecular charge-transfer effect and self-aggregation trends, and the BPCPCHY neat films placed in air for 3 months can still maintain an excellent amorphous morphology. The solution-processable deep-blue OLEDs utilizing BPCP and BPCPCHY achieved a CIE y of 0.06 with maximum external quantum efficiency (EQE max ) values of 7.19 and 8.53%, respectively, which are among the best results of the solution-processable deep-blue OLEDs based on the "hot exciton" mechanism. All of the above results indicate that benzoxazole is an excellent acceptor for constructing deep-blue HLCT materials, and the strategy of introducing HP as a modified end-group into an HLCT emitter provides a new perspective to develop solution-processable efficient deep-blue OLEDs with high morphological stability.

It is an essential task to construct brain templates and analyze their anatomical structures in neurological and cognitive science. Generally, templates constructed from magnetic resonance imaging (MRI) of a group of subjects can provide a standard reference space for analyzing the structural and functional characteristics of the group. With recent development of artificial intelligence (AI) techniques, it is desirable to explore AI registration methods for quantifying age-specific brain variations and tendencies across different ages. In this article, we present an AI-based age-specific template construction (called ASTC) framework for longitudinal structural brain analysis using T1-weighted MRIs of 646 subjects from 18 to 82 years old collected from four medical centers. Altogether, 13 longitudinal templates were constructed at a 5-year age interval using ASTC, and tissue segmentation and substructure parcellation were performed for analysis across different age groups. The results indicated consistent changes in brain structures along with aging and demonstrated the capability of ASTC for longitudinal neuroimaging study., (© 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Background: Surgical debulking remains the mainstay of treatment of adult-onset recurrent respiratory papillomatosis (AO-RRP). But there are no guidelines for decision-making of surgical modality., Objectives: This retrospective study aims to obtain a better understanding of AO-RRP, and select the best surgical modality for RRP among microdebrider, CO 2 laser, and KTP laser., Material and Methods: Medical records of 72 AO-RRP patients were reviewed, with at least a 6-month follow-up. We focused on demographic data, the median treatment intervals (MTI) (Days), the survival curves, and treatment-related complications., Results: Seventy-two AO-RRP and a total of 172 surgical procedures were included, with either the microdebrider ( n  = 46), CO 2 laser ( n  = 102), or KTP laser ( n  = 24). The MTI of all patients was 230.0[132.0, 455.0] (median[P25-P75]), with microdebrider group (267.50[152.5, 449.5]), CO 2 laser group (247.5[145.5, 474.7]), and KTP laser group (107.5[68.3, 330.5]), and there were no significant differences among three surgical modalities on MTI or survival curves ( p  > .05). The duration of surgery was 44.9[25.6] in the microdebriders group, 48.4 [29.5] in the CO2 laser group, and 51.3[18.4] in the KTP laser group, but there was no significant difference in the operation duration among the three groups ( p  > .05). Postoperative glottic webs and scar formations were found in 4.3% of patients in microdebrider group, 16.7% of patients in CO 2 laser group, and 8.3% of patients in KTP group., Conclusion and Significance: Microdebrider surgery for RRP took the shortest time and had the lowest rate of postoperative complications. However, different surgical modalities are equally effective in controlling recurrence after RRP surgery.

Electroencephalogram (EEG) classification has attracted great attention in recent years, and many models have been presented for this task. Nevertheless, EEG data vary from subject to subject, which may lead to the performance of a classifier degrades due to individual differences. To collect enough labeled data to model would address the issue, but it is often time-consuming and labor-intensive. In this paper, we propose a new multi-source transfer learning method based on domain adversarial neural network for EEG classification. Specifically, we design a domain adversarial neural network, which includes a feature extractor, a classifier, and a domain discriminator, and therefore reduce the domain shift to achieve the purpose. In addition, a unified multi-source optimization framework is constructed to further improve the performance, and the result for EEG classification is induced by the weighted combination of the predictions from multiple source domains. Experiments on three publicly available EEG datasets validate the advantages of the proposed method.

Background: Fibroblastic reticular cells (FRCs) are a type of stromal cells located in the T zone in secondary lymphoid organs. Previous studies showed that FRCs possess the potential to promote myeloid differentiation. We aim to investigate whether FRCs in lymph nodes (LNs) could induce tolerogenic macrophage generation and further influence T-cell immunity at an early stage of allogeneic hematopoietic stem cell transplantation (allo-HSCT)., Methods: LNs were assayed to confirm the existence of proliferating macrophages after allo-HSCT. Ex vivo-expanded FRCs and bone marrow cells were cocultured to verify the generation of macrophages. Real-time quantitative PCR and ELISA assays were performed to observe the cytokines expressed by FRC. Transcriptome sequencing was performed to compare the difference between FRC-induced macrophages (FMs) and conventional macrophages. Mixed lymphocyte reaction and the utilization of FMs in acute graft-versus-host disease (aGVHD) mice were used to test the inhibitory function of FMs in T-cell immunity in vitro and in vivo., Results: We found a large number of proliferating macrophages near FRCs in LNs with tolerogenic phenotype under allo-HSCT conditions. Neutralizing anti-macrophage colony-stimulating factor receptor antibody abolished FMs generation in vitro. Phenotypic analysis and transcriptome sequencing suggested FMs possessed immunoinhibitory function. Mixed lymphocyte reaction proved that FMs could inhibit T-cell activation and differentiation toward Th1/Tc1 cells. Injection of FMs in aGVHD mice effectively attenuated aGVHD severity and mortality., Conclusions: This study has revealed a novel mechanism of immune regulation through the generation of FRC-induced tolerogenic macrophages in LNs at an early stage of allo-HSCT., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Mitochondria are important organelles that play key roles in generating the energy needed for life and in pathways such as apoptosis. Direct targeting of antitumor drugs, such as doxorubicin (DOX), to mitochondria into cells is an effective approach for cancer therapy and inducing cancer cell death. To achieve targeted and effective delivery of antitumor drugs to tumor cells, to enhance the therapeutic effect, and to reduce the side effects during the treatment, we prepared a cationic amphiphilic polymer with aggregation-induced emission (AIE) characteristic. The polymer could be localized to mitochondria with excellent organelle targeting, and it showed good mitochondrial targeting with low toxicity. The polymer could also self-assemble into doxorubicin-loaded micelles in phosphate buffer, with a particle size of about 4.3 nm, an encapsulation rate of 11.03%, and micelle drug loading that reached 0.49%. The results of in vitro cytotoxicity experiments showed that the optimal dosage was 2.0 μg/mL, which had better inhibitory effect on tumor cells and less biological toxicity on heathy cells. Therefore, the cationic amphiphilic polymer can partially replace expensive commercial mitochondrial targeting reagents, and it can be also used as a drug loading tool to directly target mitochondria in cells for corresponding therapeutic research.

Acoustic analysis of the voice, as an objective, quantitative, non-invasive and reproducible method for the evaluation of voice quality, can be used to detect and analyze the acoustic characteristics of normal, artistic or pathological voice. With the development of medicine, physics, statistics, and artificial intelligence technology, there are new advances in the study of voice acoustic analysis, especially in terms of acoustic parameters. In addition, artificial neural networks can be used to perform complex multi-parameter analysis, which greatly improves the efficiency of acoustic analysis. This paper provides an overview of the methods of acoustic analysis and its latest development., Competing Interests: The authors of this article and the planning committee members and staff have no relevant financial relationships with commercial interests to disclose., (Copyright© by the Editorial Department of Journal of Clinical Otorhinolaryngology Head and Neck Surgery.)

Objective. Deep transfer learning has been widely used to address the nonstationarity of electroencephalogram (EEG) data during motor imagery (MI) classification. However, previous deep learning approaches suffer from limited classification accuracy because the temporal and spatial features cannot be effectively extracted. Approach. Here, we propose a novel end-to-end deep subject adaptation convolutional neural network (SACNN) to handle the problem of EEG-based MI classification. Our proposed model jointly optimizes three modules, i.e. a feature extractor, a classifier, and a subject adapter. Specifically, the feature extractor simultaneously extracts the temporal and spatial features from the raw EEG data using a parallel multiscale convolution network. In addition, we design a subject adapter to reduce the feature distribution shift between the source and target subjects by using the maximum mean discrepancy. By minimizing the classification loss and the distribution discrepancy, the model is able to extract the temporal-spatial features to the prediction of a new subject. Main results. Extensive experiments are carried out on three EEG-based MI datasets, i.e. brain-computer interface (BCI) competition IV dataset IIb, BCI competition III dataset IVa, and BCI competition IV dataset I, and the average accuracy reaches to 86.42%, 81.71% and 79.35% on the three datasets respectively. Furthermore, the statistical analysis also indicates the significant performance improvement of SACNN. Significance. This paper reveals the importance of the temporal-spatial features on EEG-based MI classification task. Our proposed SACNN model can make fully use of the temporal-spatial information to achieve the purpose., (© 2022 IOP Publishing Ltd.)