Deficiency of flavin-containing monooxygenase 3 protects kidney function after ischemia-reperfusion in mice

The kidney is vulnerable to ischemia and reperfusion (I/R) injury that can be fatal after major surgery. Currently, there are no effective treatments for I/R-induced kidney injury. Trimethylamine N-oxide (TMAO) is a gut-derived metabolite linked to many diseases, but its role in I/R-induced kidney injury remains unclear. Here, our clinical data reveals an association between preoperative systemic TMAO levels and postoperative kidney injury in patients after post-cardiopulmonary bypass surgery. By genetic deletion of TMAO-producing enzyme flavin-containing monooxygenase 3 (FMO3) and dietary supplementation of choline to modulate TMAO levels, we found that TMAO aggravated acute kidney injury through the triggering of endoplasmic reticulum (ER) stress and worsened subsequent renal fibrosis through TGFβ/Smad signaling activation. Together, our study underscores the negative role of TMAO in I/R-induced kidney injury and highlights the therapeutic potential through the modulation of TMAO levels by targeting FMO3, thereby mitigating acute kidney injury and preventing subsequent renal fibrosis.

[Pharmacodynamics of Qingxin Jieyu Granules for treatment of atherosclerosis and its regulatory mechanism for lipid metabolism]

OBJECTIVE

To elucidate the therapeutic mechanism of Qingxin Jieyu Granule (QXJYG) against atherosclerosis (AS) based on network pharmacology.

METHODS

The major targets and pathways of QXJYG against AS were analyzed using network pharmacology. Rat models of AS established by high-fat feeding combined with intraperitoneal vitamin D3 injection were treated daily with normal saline, atorvastatin (13.15 mg/kg), or QXJYG at 0.99, 1.98, and 3.96 g/kg for 8 weeks (n=6). Ultrasound and HE staining were used to assess the function and pathologies of the abdominal aorta. Blood lipids and serum levels of Ang Ⅱ, ET-1, TXA2, PGI2, and ox-LDL of the rats were detected using an automatic biochemical analyzer or ELISA. The expressions of LOX-1, PPARγ, RXRα, p-P65, VCAM-1 and ICAM-1 in the abdominal aorta were detected with immunohistochemistry.

RESULTS

The rat models of AS showed obvious abdominal aorta wall thickening, increased pulse wave velocity and pulse index, decreased inner diameter of the abdominal aorta, elevated levels of TC, LDL-C, Ang Ⅱ, ET-1 and TXA2, and lowered levels of HDL-C and PGI2. QXJYG and atorvastatin treatment of the rat models significantly alleviated histopathological changes of the abdominal aorta, decreased serum levels of TC, LDL-C, Ang Ⅱ, ET-1 and TXA2, and increased the levels of HDL-C and PGI2. Network pharmacology study suggested the therapeutic effect of QXJYG against AS was mediated by regulating lipid metabolism, PPAR and NF-κB pathways. Consistently, treatments with QXJYG were found to significantly decrease ox-LDL level and LOX-1, P-P65, VCAM-1 and ICAM-1 protein expressions while increasing PPARγ and RXRα expressions in the aorta of AS rats.

CONCLUSION

QXJYG alleviates lipid metabolism disorder and improves histopathological changes of the abdominal aorta of AS rats possibly by lowering ox-LDL level, reducing LOX-1 expression, activating PPARγ and RXRα, and inhibiting P65 phosphorylation to reduce VCAM-1 and ICAM-1 expression in the aorta.

Prophylactic supplementation with Bifidobacterium infantis or its metabolite inosine attenuates cardiac ischemia/reperfusion injury

Emerging evidence has demonstrated the profound impact of the gut microbiome on cardiovascular diseases through the production of diverse metabolites. Using an animal model of myocardial ischemia-reperfusion (I/R) injury, we found that the prophylactic administration of a well-known probiotic, Bifidobacterium infantis (B. infantis), exhibited cardioprotective effects in terms of preserving cardiac contractile function and preventing adverse cardiac remodeling following I/R and that these cardioprotective effects were recapitulated by its metabolite inosine. Transcriptomic analysis further revealed that inosine mitigated I/R-induced cardiac inflammation and cell death. Mechanistic investigations elucidated that inosine suppressed the production of pro-inflammatory cytokines and reduced the numbers of dendritic cells and natural killer cells, achieved through the activation of the adenosine A2A receptor (A2AR) that when inhibited abrogated the cardioprotective effects of inosine. Additionally, in vitro studies using C2C12 myoblasts revealed that inosine attenuated cell death by serving as an alternative carbon source for adenosine triphosphate (ATP) generation through the purine salvage pathway when subjected to oxygen-glucose deprivation/reoxygenation that simulated myocardial I/R injury. Likewise, inosine reversed the I/R-induced decrease in ATP levels in mouse hearts. Taken together, our findings indicate that B. infantis or its metabolite inosine exerts cardioprotective effects against I/R by suppressing cardiac inflammation and attenuating cardiac cell death, suggesting prophylactic therapeutic options for acute ischemic cardiac injury.

Biodegradable MXene Quantum Dots with High Near-Infrared Photothermal Performance for Cancer Treatment

Photothermal therapy (PTT) offers significant potential in cancer treatment due to its short, simple, and less harmful nature. However, obtaining a photothermal agent (PTA) with good photothermal performance and biocompatibility remains a challenge. MXenes, which are PTAs, have shown promising results in cancer treatment. This study presents the preparation of Ti3C2 MXene quantum dots (MXene QDs) using a simple hydrothermal and ultrasonic method and their use as a PTA for cancer treatment. Compared to conventional MXene QDs synthesized using only the hydrothermal method, the ultrasonic process increased the degree of oxidation on the surface of the MXene QDs. This resulted in the presence of more hydrophilic groups such as hydroxyl groups on the MXene QD surfaces, leading to excellent dispersion in the aqueous system and biocompatibility of the prepared MXene QDs without the need for surface modification. The MXene QDs showed great photothermal performance with a photothermal conversion efficiency of 62.5%, resulting in the highest photothermal conversion efficiency among similar materials reported thus far. Both in vitro and in vivo experiments have proved the potent tumor inhibitory effect of the MXene QD-mediated PTT, with minimal harm to mice. Therefore, these MXene QDs hold a significant promise for clinical applications.

Performance of the neural network-based prediction model in closed-loop adaptive optics

Adaptive optics (AO) technology is an effective means to compensate for atmospheric turbulence, but the inherent delay error of an AO system will cause the compensation phase of the deformable mirror (DM) to lag behind the actual distortion, which limits the correction performance of the AO technology. Therefore, the feed-forward prediction of atmospheric turbulence has important research value and application significance to offset the inherent time delay and improve the correction bandwidth of the AO system. However, most prediction algorithms are limited to an open-loop system, and the deployment and the application in the actual AO system are rarely reported, so its correction performance improvement has not been verified in practice. We report, to our knowledge, the first successful test of a deep learning-based spatiotemporal prediction model in an actual 3 km laser atmospheric transport AO system and compare it with the traditional closed-loop control methods, demonstrating that the AO system with the prediction model has higher correction performance.

[Soil microorganisms and physicochemical properties in marshlands along the Yangtze River basin at different types of land use and their effects on distribution of Oncomelania hupensis snails]

OBJECTIVE

To investigating the microbial communities and physicochemical properties of soil and distribution of Oncomelania hupensis snails in marshlands along the Yangtze River basin at different types of land use, and to examine the effects of soil microorganisms and physicochemical properties on snail distribution, so as to provide insights into snail control and schistosomiasis prevention in marshland along the Yangtze River basin.

METHODS

Marshlands with four types of land use were selected along the Yangtze River basin on April 2021, including poplar forest-crops integrated planting, reed areas, agricultural cultivation lands and ditches. The distribution of snails and physicochemical properties of soil were investigated in marshlands with different types of land use, and the V3 to V4 regions of the bacterial 16S ribosomal RNA (16S rRNA) gene, fungal internal transcribed spacer-1 (ITS1) gene and algal ribulose-bisphosphate carboxylase (rbcL) gene in soils were subjected to high-throughput sequencing. The occurrence of frames with living snails and density of living snails were compared in marshland with different types of land use. The associations of soil microorganisms and physicochemical properties with the density of living snails were examined using Pearson correlation analysis, and the contributions of soil microorganisms and physicochemical properties to the density of living snails were evaluated using variance partitioning analysis.

RESULTS

In marshlands with four types of land use, the greatest occurrence of frames with living snails [(4.94 ± 2.14)%] and density of living snails [(0.070 ± 0.026) snails/0.1 m2] were seen in ditches, and the lowest were found in [(1.23 ± 1.23)%] agricultural cultivation lands [(0.016 ± 0.019) snails/0.1 m2]. A total of 2 phyla, 5 classes, 8 orders, 9 families and 11 genera of algae were detected in soils at four types of land use, with Chlorophyta as the dominant phylum and Pseudoneochloris as the dominant genus. A total of 44 phyla, 134 classes, 281 orders, 338 families and 516 genera of bacteria were detected in soils at four types of land use, with Proteobacteria and Acidobacteriota as the dominant phyla and uncultured Acidobacterium, MND1, Mitrospira, Haliangium and Sphingomonas as dominant genera. A total of 11 phyla, 41 classes, 108 orders, 223 families and 408 genera of fungi were detected in soils at four types of land use, with phyla Ascomycota, Basidiomycota and Mortierellomycota presenting high relative abundances and genera Cladorrhinum, Mortierella and Humicola presenting high relative abundances. Pearson correlation analysis revealed that the density of living snails correlated negatively with the relative abundance of Proteobacteria (r = -0.965, P < 0.05) and soil electronic conductivity (r = -0.962, P < 0.05) and positively with soil moisture (r = 0.951, P < 0.05). Variance partitioning analysis demonstrated that the physicochemical properties and microorganisms of soil contributed 69% and 10% to the density of living snails, respectively.

CONCLUSIONS

The diversity of microbial communities varies in soils at different types of land use in marshland along the Yangtze River basin, and the physicochemical properties and microorganisms of soils may affect the distribution of O. hupensis snails.

Experimental demonstration of wavefront reconstruction and correction techniques for variable targets based on distorted grating and deep learning

This research presents a practical approach for wavefront reconstruction and correction adaptable to variable targets, with the aim of constructing a high-precision, general extended target adaptive optical system. Firstly, we delve into the detailed design of a crucial component, the distorted grating, simplifying the optical system implementation while circumventing potential issues in traditional phase difference-based collection methods. Subsequently, normalized fine features (NFFs) and structure focus features (SFFs) which both are independent of the imaging target but corresponded precisely to the wavefront aberration are proposed. The two features provide a more accurate and robust characterization of the wavefront aberrations. Then, a Noise-to-Denoised Generative Adversarial Network (N2D-GAN) is employed for denoising real images. And a lightweight network, Attention Mechanism-based Efficient Network (AM-EffNet), is applied to achieve efficient and high-precision mapping between features and wavefronts. A prototype of object-independent adaptive optics system is demonstrated by experimental setup, and the effectiveness of this method in wavefront reconstruction for different imaging targets has been verified. This research holds significant relevance for engineering applications of adaptive optics, providing robust support for addressing challenges within practical systems.

Prophylactic Supplementation with Lactobacillus Reuteri or Its Metabolite GABA Protects Against Acute Ischemic Cardiac Injury

The gut microbiome has emerged as a potential target for the treatment of cardiovascular disease. Ischemia/reperfusion (I/R) after myocardial infarction is a serious complication and whether certain gut bacteria can serve as a treatment option remains unclear. Lactobacillus reuteri (L. reuteri) is a well-studied probiotic that can colonize mammals including humans with known cholesterol-lowering properties and anti-inflammatory effects. Here, the prophylactic cardioprotective effects of L. reuteri or its metabolite γ-aminobutyric acid (GABA) against acute ischemic cardiac injury caused by I/R surgery are demonstrated. The prophylactic gavage of L. reuteri or GABA confers cardioprotection mainly by suppressing cardiac inflammation upon I/R. Mechanistically, GABA gavage results in a decreased number of proinflammatory macrophages in I/R hearts and GABA gavage no longer confers any cardioprotection in I/R hearts upon the clearance of macrophages. In vitro studies with LPS-stimulated bone marrow-derived macrophages (BMDM) further reveal that GABA inhibits the polarization of macrophages toward the proinflammatory M1 phenotype by inhibiting lysosomal leakage and NLRP3 inflammasome activation. Together, this study demonstrates that the prophylactic oral administration of L. reuteri or its metabolite GABA attenuates macrophage-mediated cardiac inflammation and therefore alleviates cardiac dysfunction after I/R, thus providing a new prophylactic strategy to mitigate acute ischemic cardiac injury.

Multi-line-of-sight Hartmann-Shack wavefront sensing based on image segmentation and K-means sorting

Multi-line-of-sight wavefront sensing, crucial for next-generation astronomy and laser applications, often increases system complexity by adding sensors. This research introduces, to the best of our knowledge, a novel method for multi-line-of-sight Hartmann-Shack wavefront sensing by using a single sensor, addressing challenges in centroid estimation and classification under atmospheric turbulence. This method contrasts with existing techniques that rely on multiple sensors, thereby reducing system complexity. Innovations include combining edge detection and peak extraction for precise centroid calculation, improved k-means clustering for robust centroid classification, and a centroid filling algorithm for subapertures with light loss. The method's effectiveness was confirmed through simulations for a five-line-of-sight system and experimental setup for two-line and three-line-of-sight systems, demonstrating its potential in real atmospheric aberration correction conditions. Experimental findings indicate that, when implemented in a closed-loop configuration, the method significantly reduces wavefront residuals from 1 λ to 0.1 λ under authentic atmospheric turbulence conditions. Correspondingly, the quality of the far-field spot is enhanced by a factor of 2 to 4. These outcomes collectively highlight the method's robust capability in enhancing optical system performance in environments characterized by genuine atmospheric turbulence.

Multiple serous cavity effusion screening based on smear images using vision transformer

Serous cavity effusion is a prevalent pathological condition encountered in clinical settings. Fluid samples obtained from these effusions are vital for diagnostic and therapeutic purposes. Traditionally, cytological examination of smears is a common method for diagnosing serous cavity effusion, renowned for its convenience. However, this technique presents limitations that can compromise its efficiency and diagnostic accuracy. This study aims to overcome these challenges and introduce an improved method for the precise detection of malignant cells in serous cavity effusions. We have developed a transformer-based classification framework, specifically employing the vision transformer (ViT) model, to fulfill this objective. Our research involved collecting smear images and corresponding cytological reports from 161 patients who underwent serous cavity drainage. We meticulously annotated 4836 patches from these images, identifying regions with and without malignant cells, thus creating a unique dataset for smear image classification. The findings of our study reveal that deep learning models, particularly the ViT model, exhibit remarkable accuracy in classifying patches as malignant or non-malignant. The ViT model achieved an impressive area under the receiver operating characteristic curve (AUROC) of 0.99, surpassing the performance of the convolutional neural network (CNN) model, which recorded an AUROC of 0.86. Additionally, we validated our models using an external cohort of 127 patients. The ViT model sustained its high-level screening performance, achieving an AUROC of 0.98 at the patient level, compared to the CNN model's AUROC of 0.84. The visualization of our ViT models confirmed their capability to precisely identify regions containing malignant cells in multiple serous cavity effusion smear images. In summary, our study demonstrates the potential of deep learning models, particularly the ViT model, in automating the screening process for serous cavity effusions. These models offer significant assistance to cytologists in enhancing diagnostic accuracy and efficiency. The ViT model stands out for its advanced self-attention mechanism, making it exceptionally suitable for tasks that necessitate detailed analysis of small, sparsely distributed targets like cellular clusters in serous cavity effusions.

Spiking Neural Network for Ultralow-Latency and High-Accurate Object Detection

Spiking Neural Networks (SNNs) have attracted significant attention for their energy-efficient and brain-inspired event-driven properties. Recent advancements, notably Spiking-YOLO, have enabled SNNs to undertake advanced object detection tasks. Nevertheless, these methods often suffer from increased latency and diminished detection accuracy, rendering them less suitable for latency-sensitive mobile platforms. Additionally, the conversion of artificial neural networks (ANNs) to SNNs frequently compromises the integrity of the ANNs' structure, resulting in poor feature representation and heightened conversion errors. To address the issues of high latency and low detection accuracy, we introduce two solutions: timestep compression and spike-time-dependent integrated (STDI) coding. Timestep compression effectively reduces the number of timesteps required in the ANN-to-SNN conversion by condensing information. The STDI coding employs a time-varying threshold to augment information capacity. Furthermore, we have developed an SNN-based spatial pyramid pooling (SPP) structure, optimized to preserve the network's structural efficacy during conversion. Utilizing these approaches, we present the ultralow latency and highly accurate object detection model, SUHD. SUHD exhibits exceptional performance on challenging datasets like PASCAL VOC and MS COCO, achieving a remarkable reduction of approximately 750 times in timesteps and a 30% enhancement in mean average precision (mAP) compared to Spiking-YOLO on MS COCO. To the best of our knowledge, SUHD is currently the deepest spike-based object detection model, achieving ultralow timesteps for lossless conversion.

MG-Trans: Multi-Scale Graph Transformer With Information Bottleneck for Whole Slide Image Classification

Multiple instance learning (MIL)-based methods have become the mainstream for processing the megapixel-sized whole slide image (WSI) with pyramid structure in the field of digital pathology. The current MIL-based methods usually crop a large number of patches from WSI at the highest magnification, resulting in a lot of redundancy in the input and feature space. Moreover, the spatial relations between patches can not be sufficiently modeled, which may weaken the model's discriminative ability on fine-grained features. To solve the above limitations, we propose a Multi-scale Graph Transformer (MG-Trans) with information bottleneck for whole slide image classification. MG-Trans is composed of three modules: patch anchoring module (PAM), dynamic structure information learning module (SILM), and multi-scale information bottleneck module (MIBM). Specifically, PAM utilizes the class attention map generated from the multi-head self-attention of vision Transformer to identify and sample the informative patches. SILM explicitly introduces the local tissue structure information into the Transformer block to sufficiently model the spatial relations between patches. MIBM effectively fuses the multi-scale patch features by utilizing the principle of information bottleneck to generate a robust and compact bag-level representation. Besides, we also propose a semantic consistency loss to stabilize the training of the whole model. Extensive studies on three subtyping datasets and seven gene mutation detection datasets demonstrate the superiority of MG-Trans.

Norovirus outbreaks in hospitals in China: a systematic review

BACKGROUND

Norovirus outbreaks in hospitals can potentially impair patient care and result in significant financial expenses. There is currently limited information on hospital norovirus outbreaks in the Chinese mainland.

AIM

To systematically review the published literature to describe the characteristics of norovirus outbreaks in Chinese mainland hospitals to facilitate prompt identification and control of outbreaks.

METHODS

A systematic review was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analysis standards. Databases including PubMed, Web of Science, and Chinese Journals Online databases (China National Knowledge Infrastructure (CNKI), Chinese Wan Fang digital database (WANFANG) were searched from inception to July 18th, 2022.

FINDINGS

A total of 41 norovirus Chinese hospital outbreaks occurring before July 18th, 2022 were reported in 32 articles. Most reported outbreaks were from Shanghai and Beijing, and occurred in December and January. Cases were mainly adults. The male:female ratio was 1.22:1. The majority of cases in norovirus outbreaks were hospitalized patients (56.82%); medical staff were affected in 15 outbreaks. Norovirus outbreaks occurred in both private and public hospitals, and in secondary and tertiary care centres, and occurred mainly in internal medicine and geriatric departments. Person-to-person transmission was the primary transmission mode and GII was more prevalent.

CONCLUSION

Norovirus outbreaks in hospitals can affect both patients and healthcare workers, sometimes causing serious financial losses. In order to have a more complete understanding of the disease burden caused by norovirus outbreaks, surveillance needs to be established in hospitals.

[Epidemiological and clinical characteristics of human ocular helaziasis in China from 2011 to 2022 based on bibliometrics]

OBJECTIVE

To understand the clinical and epidemiological characteristics of human ocular thelaziasis patients in China.

METHODS

Case reports regarding human ocular thelaziasis cases in China were retrieved in international and national electronic databases, including CNKI, VIP, CBM, Traditional Chinese Medical Literature Analysis and Retrieval System, Wanfang Database, PubMed and Web of Science from 2011 to 2022. Patients' gender, age, clinical symptoms, treatment, recurrence, site of infections, time of onset, affected eye, affected sites, number of infected Thelazia callipaeda, sex of T. callipaeda and source of infections were extracted for descriptive analyses.

RESULTS

A total of 85 eligible publications were included, covering 101 cases of human ocular thelaziasis, including 57 males (56.44%) and 44 females (43.56%) and aged from 3 months to 85 years. The main clinical manifestations included foreign body sensation (56 case-times, 22.49%), eye itching (38 case-times, 15.26%), abnormal or increased secretions (36 case-times, 14.46%), tears (28 case-times, 11.24%) and eye redness (28 case-times, 11.24%), and conjunctival congestion (50 case-times, 41.67%) was the most common clinical sign. The most common main treatment (99/101, 98.02%) was removal of parasites from eyes using ophthalmic forceps, followed by administration with ofloxacin and pranoprofen. In publications presenting thelaziasis recurrence, there were 90 cases without recurrence (97.83%) and 2 cases with recurrence (2.17%). Of all cases, 51.96% were reported in four provinces of Hubei, Shandong, Sichuan, Hebei and Henan, and ocular thelaziasis predominantly occurred in summer (42.19%) and autumn (42.19%). In addition, 56.45% (35/62) had a contact with dogs.

CONCLUSIONS

The human thelaziasis cases mainly occur in the continental monsoon and subtropical monsoon climate areas such as the Yellow River and the Yangtze River basin, and people of all ages and genders have the disease, with complex clinical symptoms and signs. Personal hygiene is required during the contact with dogs, cats and other animals, and individual protection is required during outdoor activities to prevent thelaziasis.

Crystal Growth of Defect-Free Single-Crystalline Fibers in Super-High Supersaturation Solution

By controlling the supersaturation and choosing high-quality seeds, we successfully suppress the prismatic growth of the tetragonal potassium dihydrogen phosphate (KDP) SCFs, realize the rapid growth along the [001] direction, and obtain SCFs less than 10 μm in width with lengths of centimeters. The experimental results show that there exist critical supersaturation points, 22.40% and 41.41% at 25 °C, for initiating the growth of KDP SCF on its pyramidal and prismatic faces, respectively, which are quite different from those of the bulk crystals. We use the mechanism of 2D nucleation on smooth faces to explain the peculiar phenomena, assuming that there is no 2D or 3D defect on the surfaces of the seed fiber crystal. The assumption is supported by AFM observation of the surface micromorphology of the SCFs. Our solution growth technique developed can be used to grow ultrafine SCFs unable to be achieved by existing melt growth techniques.

Highly Stable Spatio-Temporal Prediction Network of Wavefront Sensor Slopes in Adaptive Optics

Adaptive Optics (AO) technology is an effective means to compensate for wavefront distortion, but its inherent delay error will cause the compensation wavefront on the deformable mirror (DM) to lag behind the changes in the distorted wavefront. Especially when the change in the wavefront is higher than the Shack-Hartmann wavefront sensor (SHWS) sampling frequency, the multi-frame delay will seriously limit its correction performance. In this paper, a highly stable AO prediction network based on deep learning is proposed, which only uses 10 frames of prior wavefront information to obtain high-stability and high-precision open-loop predicted slopes for the next six frames. The simulation results under various distortion intensities show that the prediction accuracy of six frames decreases by no more than 15%, and the experimental results also verify that the open-loop correction accuracy of our proposed method under the sampling frequency of 500 Hz is better than that of the traditional non-predicted method under 1000 Hz.

[Evaluation of the clinical manifestations of COVID-19 in patients with aplastic anemia undergoing immunosuppressive therapy: a prospective cohort study (NICHE)]

Objective: To investigate the clinical features of coronavirus disease 2019 (COVID-19) in patients with aplastic anemia (AA) undergoing immunosuppressive therapy (IST) . Methods: In this prospective cohort study, we collected the demographic and clinical data of patients with AA and COVID-19 from December 1, 2022, to January 31, 2023. We described the clinical features of COVID-19 among patients with AA and evaluated the effects of IST on the signs and severity of COVID-19. Results: A total of 170 patients with AA and COVID-19 were included. The common early symptoms, including fever, dizziness or headache, muscle or body aches, and sore throat, disappeared within 1-2 weeks. Approximately 25% of the patients had persistent fatigue within 2 weeks. Many patients experienced cough after an initial 1-3 days of infection, which lasted for more than 2 weeks. There were no differences in the duration of total fever episodes and maximum body temperature when patients were stratified according to whether or not they underwent IST, by IST duration, or by use of anti-lymphocyte globulin (ALG) (P>0.05). No differences were observed in the occurrence of symptoms in either the early or recovery stages when patients with AA were stratified according to whether or not they underwent IST, or by IST duration (P>0.05). However, patients who received ALG had fewer fever episodes within 1 week after infection (P=0.035) and more sore throat episodes within 2 weeks after infection (P=0.015). There were no other significant differences in clinical symptoms between patients who did and patients who did not receive ALG (P>0.05) . Conclusion: The majority of patients with AA and COVID-19 recovered within 2 weeks of noticing symptoms when treated with IST.

Dual-Role of Polyelectrolyte-Tethered Benzimidazolium Cation in Promoting CO2 /Pure Water Co-Electrolysis to Ethylene

Electrochemical CO2 reduction reaction (CO2 RR), as a promising route to realize negative carbon emissions, is known to be strongly affected by electrolyte cations (i.e., cation effect). In contrast to the widely-studied alkali cations in liquid electrolytes, the effect of organic cations grafted on alkaline polyelectrolytes (APE) remains unexplored, although APE has already become an essential component of CO2 electrolyzers. Herein, by studying the organic cation effect on CO2 RR, we find that benzimidazolium cation (Beim+ ) significantly outperforms other commonly-used nitrogenous cations (R4 N+ ) in promoting C2+ (mainly C2 H4 ) production over copper electrode. Cyclic voltammetry and in situ spectroscopy studies reveal that the Beim+ can synergistically boost the CO2 to *CO conversion and reduce the proton supply at the electrocatalytic interface, thus facilitating the *CO dimerization toward C2+ formation. By utilizing the homemade APE ionomer, we further realize efficient C2 H4 production at an industrial-scale current density of 331 mA cm-2 from CO2 /pure water co-electrolysis, thanks to the dual-role of Beim+ in synergistic catalysis and ionic conduction. This study provides a new avenue to boost CO2 RR through the structural design of polyelectrolytes.

A Structure-Aware Hierarchical Graph-Based Multiple Instance Learning Framework for pT Staging in Histopathological Image

Pathological primary tumor (pT) stage focuses on the infiltration degree of the primary tumor to surrounding tissues, which relates to the prognosis and treatment choices. The pT staging relies on the field-of-views from multiple magnifications in the gigapixel images, which makes pixel-level annotation difficult. Therefore, this task is usually formulated as a weakly supervised whole slide image (WSI) classification task with the slide-level label. Existing weakly-supervised classification methods mainly follow the multiple instance learning paradigm, which takes the patches from single magnification as the instances and extracts their morphological features independently. However, they cannot progressively represent the contextual information from multiple magnifications, which is critical for pT staging. Therefore, we propose a structure-aware hierarchical graph-based multi-instance learning framework (SGMF) inspired by the diagnostic process of pathologists. Specifically, a novel graph-based instance organization method is proposed, namely structure-aware hierarchical graph (SAHG), to represent the WSI. Based on that, we design a novel hierarchical attention-based graph representation (HAGR) network to capture the critical patterns for pT staging by learning cross-scale spatial features. Finally, the top nodes of SAHG are aggregated by a global attention layer for bag-level representation. Extensive studies on three large-scale multi-center pT staging datasets with two different cancer types demonstrate the effectiveness of SGMF, which outperforms state-of-the-art up to 5.6% in the F1 score.

[Y-shaped osteotomy in the apical vertebra for treating congenital complex rigid scoliosis:at least 2-year follow-up]

Objective: To investigate the clinical outcome of the coronal Y-shaped osteotomy in the apical vertebra for treating congenital complex rigid scoliosis. Methods: A retrospective analysis was conducted on 66 cases who underwent Y-shaped osteotomy treatment for congenital complex rigid scoliosis in the uppermost vertebra at the Department of Orthopedics,the Second Hospital of Shanxi Medical University from June 2007 to August 2020. There were 19 males and 47 females,with an age of (13.1±5.3) years(range:2 to 30 years).Classification of congenital scoliosis:25 cases (37.9%) were incomplete,13 cases (19.7%) were dysarthritic,and 28 cases (42.4%) were mixed. There were 25 cases (37.9%) with thoracic or rib malformations. 45 cases (68.2%) were complicated with spinal cord malformation.The main radiological indicators included Cobb angle of the curvature,Cobb angle of the local bend,apical vertebral translation (AVT),trunk shift (TS),thoracic trunk shift (TTS),radiographic shoulder height (RSH),coronal balance and sagittal vertebral axis. The preoperative,postoperative immediate,and last follow-up radiological indicators were collected and the operation time,blood loss,hospitalization time,and operation-related complications were recorded. Data were compared by repeated measure ANOVA and paired-t test. Results: All patients underwent surgery successfully. The duration of the first surgery was (221.4±52.8) minutes,and the blood loss during the first surgery was (273.2±41.8) ml. The length of the first hospital stay was (8.8±1.7) days.Unilateral fixation was performed in 19 cases (28.8%),while bilateral fixation was performed in 47 cases (71.2%). The fused segments were 7.5±2.9,and the vertebral pedicle screw density was (68.5±20.6)%. The follow-up time for the 66 patients was (36.7±17.0) months(range:24 to 102 months).The main curve Cobb Angle was improved from (58.5±18.9)°before surgery to (21.1±11.8)°after surgery,and was (23.6±15.3) ° at the last follow-up(F=273.957,P<0.01),with a correction rate of 66.2%. Segmental curve Cobb Angle was improved from (47.9±18.0)° to (16.0±11.3)° after surgery,and was (16.8±12.8) °at the last follow-up (F=270.483,P<0.01)with a correction rate of 69.2%. The AVT,TS,TTS and RSH values improved significantly at the final follow-up (all P<0.05),while coronal balance and sagittal vertical axis were maintained without significant differences between pre-operation and post-operation(both P>0.05). A total of 5 patients underwent staged operation,all of which were residual scoliosis aggravated after the first stage of orthosis operation and had good prognosis after the second stage of operation. Conclusions: Y-shaped osteotomy for the treatment of congenital rigid scoliosis results in good clinical and radiological outcomes without serious complications. This procedure can be considered as an option for the treatment of congenital complex rigid scoliosis.

Object-independent wavefront sensing method based on an unsupervised learning model for overcoming aberrations in optical systems

This Letter introduces the idea of unsupervised learning into object-independent wavefront sensing for the first time, to the best of our knowledge, which can achieve fast phase recovery of arbitrary objects without labels. First, a fine feature extraction method which only depends on the wavefront aberrations is proposed. Then, a lightweight neural network and an optical feature system are combined to form an unsupervised learning model, and the neural network is promoted to be well trained by reversely outputting fine features. Simulation results prove that the proposed method can effectively overcome the aberrations (static or variable) existing in the optical system and achieve wavefront sensing of different objects with high precision and efficiency.

Applying machine learning methods for the analysis of two-dimensional mass spectra

In a measurement of isomeric yield-ratios in fission, the Phase-Imaging Ion-Cyclotron-Resonance technique, which projects the radial motions of ions in the Penning trap (JYFLTRAP) onto a position-sensitive micro-channel plate detector, has been applied. To obtain the yield ratio, that is the relative population of two states of an isomer pair, a novel analysis procedure has been developed to determine the number of detected ions in each state, as well as corrections for the detector efficiency and decay losses. In order to determine the population of the states in cases where their mass difference is too small to reach full separation, a Bayesian Gaussian Mixture model was implemented. The position-dependent efficiency of the micro-channel plate detector was calibrated by mapping it with 133 Cs+ ions, and a Gaussian Process was trained with the position data to construct an efficiency function that could be used to correct the recorded distributions. The obtained numbers of counts of excited and ground-state ions were used to derive the isomeric yield ratio, taking into account decay losses as well as feeding from precursors.

[Evaluation of the clinical efficacy of minimally invasive endoscopic surgery in the treatment of isolated non-syndromic sagittal synostosis in infants]

The current study aimed to evaluate the early efficacy in infants with isolated non-syndromic sagittal synostosis who underwent minimally invasive endoscopic-assisted surgery. The clinical data of infants with isolated non-syndromic sagittal synostosis who were admitted to the Department of Neurosurgery of the Children's Hospital of Nanjing Medical University and underwent endoscopic-assisted surgery from October 2018 to December 2021 were retrospectively analyzed. All the infants underwent minimally invasive endoscopic-assisted surgery, and were treated with supine sleeping position after surgery. Computer-aided reconstruction technique was used to reconstruct and measure the thin-slice CT scan images of the head before and 3 months after surgery, and the differences in cranial index (CI), cranial cavity volume and angle drawn between the cranial vertex, nasion, and opisthocranion (VNO angle) of preoperative and postoperative groups were analyzed. A total of 103 infants were included in the final analysis, including 85 males and 18 females. The age at surgery was (2.1±0.8) months, and the weight was (6.1±0.9) kg. The postoperative CI was (84±6)%, which increased obviously compared with the pre-operation [(70±5)%] (P<0.001). The cranial volume of post-operation was (947±130) cm³, which was larger than that of the pre-operation [(748±104) cm³] (P<0.001). The VNO angle after surgery was (45±4)°, which showed a significant reduction compared with the pre-operation [(55±4)°] (P<0.001). The correction of head shape was satisfactory. For the treatment of sagittal synostosis in infants, minimally invasive endoscopic-assisted surgery is safe and effective, and in the case of switching from an auxiliary helmet to a supine position, the postoperative correction efficacy of head shape is better.

Respiration-Responsive Colorful Room-Temperature Phosphorescent Materials and Assembly-Induced Phosphorescence Enhancement Strategies

It is still very challenging to obtain colorful and long-afterglow room-temperature phosphorescent (RTP) materials from pure organic polymers. Herein, it is found that chitosan (CS), a natural polymer, not only has its own RTP, but also reacts with different phosphorescent molecules to obtain a multicolor, long-afterglow RTP material. CS can emit RTP with a lifetime of 48 ms. In addition, CS is rich in amino groups, and grafting different phosphorescent molecules onto CS by an amidation reaction can modulate it to emit different colors of phosphorescence and obtain a series of colorful CS derivatives. The obtained polymer films also have ultra-long RTP due to the good film-forming ability. In addition, one of the CS derivatives selected with α-cyclodextrin is used to construct RTP materials with lifetimes of up to seconds. The host-guest interactions are used to suppress nonradiative relaxation and build crystalline domains, thus synergistically enhancing the RTP. Interestingly, the RTP properties of the CS derivative films are extremely sensitive to water and heat stimuli, because water broke the hydrogen bonds between adjacent CS molecules and thus altered the rigid environment in the material. Finally, they can be used as a stimuli-responsive ink and for monitoring environmental humidity.