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Qian Li,1,2 Caifeng Luo,1 Jianqin Ye,3 Zekun Bian,1 Weiyi Sun,1 Man Zhou,4 Mingzhu Rong4 1School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, People’s Republic of China; 2Department of Neurosurgery, Xiangcheng People’s Hospital, Suzhou, Jiangsu, People’s Republic of China; 3Department of Nursing, Xiangcheng People’s Hospital, Suzhou, Jiangsu, People’s Republic of China; 4Department of Neurology, Suzhou Municipal Hospital, Suzhou, Jiangsu, People’s Republic of ChinaCorrespondence: Caifeng Luo, School of Medicine, Jiangsu University, No. 301 Xuefu Road, Jingkou District, Zhenjiang, 212013, People’s Republic of China, Email lcf0105@163.comPurpose: Stroke is a major disease endangering the health of Chinese people, and patients need to rely on the care of family members, which brings heavy caregiving burdens and pressures to caregivers and families, thus disrupting the stable family structure. In view of this, this study was to analyse the current status of family resilience among caregivers of stroke patients in Chinese nuclear families, and to explore the correlation and mechanism of action among perceived stress, illness uncertainty and family resilience.Patients and Methods: This study used a cross-sectional research design. A total of 350 carers of stroke patients in nuclear families from four tertiary hospitals in Suzhou City, Jiangsu Province, China were selected by convenience sampling method and assessed by using demographic questionnaires, the Chinese Perceived Stress Scale (CPSS), the Parental Perceptions of Uncertainty Scale-Family (PPUS-FM), and a short Chinese version of the Family Resilience Assessment Scale (FRAS-C). Based on the above data, structural equation model was used to test the mediating role of perceived stress between illness uncertainty and family resilience.Results: Family resilience among caregivers of stroke patients in nuclear families was at the medium lower level, illness uncertainty was at the medium level, and p

Background: Controllability analysis is an approach developed for evaluating the ability of a brain region to modulate function in other regions, which has been found to be altered in major depressive disorder (MDD). Both depressive symptoms and cognitive impairments are prominent features of MDD, but the case–control differences of controllability between MDD and controls can not fully interpret the contribution of both clinical symptoms and cognition to brain controllability and linked patterns among them in MDD. Methods: Sparse canonical correlation analysis was used to investigate the associations between resting-state functional brain controllability at the network level and clinical symptoms and cognition in 99 first-episode medication-naïve patients with MDD. Findings: Average controllability was significantly correlated with clinical features. The average controllability of the dorsal attention network (DAN) and visual network had the highest correlations with clinical variables. Among clinical variables, depressed mood, suicidal ideation and behaviour, impaired work and activities, and gastrointestinal symptoms were significantly negatively associated with average controllability, and reduced cognitive flexibility was associated with reduced average controllability. Interpretation: These findings highlight the importance of brain regions in modulating activity across brain networks in MDD, given their associations with symptoms and cognitive impairments observed in our study. Disrupted control of brain reconfiguration of DAN and visual network during their state transitions may represent a core brain mechanism for the behavioural impairments observed in MDD. Funding: National Natural Science Foundation of China (82001795 and 82027808), National Key R&D Program (2022YFC2009900), and Sichuan Science and Technology Program (2024NSFSC0653).

Pollinating insects rely on floral resources for survival and reproduction. Early flowering plants offer food resources for pollinating insects when floral resources are scarce, but they may also distract pollinating insects from pollination-dependent crops. Here we assessed how the abundance of bees and the pollination success of Korla fragrant pear (Pyrus sinkiangensis) is influenced by early flowering apricot trees within pear orchards or in the landscape at large, and how this influence is moderated by apricot flowering. The abundance of bees was measured using colored pan traps and pollination success was assessed by recording the initial fruit set and seed set. The density of apricot trees and land use types in radii of 0.5, 1.0, 1.5, and 2.0 km around focal pear orchards were assessed by landscape survey. The abundance of wild bees and honeybees was significantly higher in pear orchards with interspersed apricot trees than in mono-pear orchards. Pear trees next to an apricot tree row (5 m) had significantly higher wild bee abundance than pear trees at further distances (15 m, 30 m, 50 m, and 100 m). However, the positive effect of apricot trees on bee abundance in pear trees was only observed during apricot blooming, and the presence of apricot trees within or adjacent to pear orchards did not influence pear pollination success. The density of apricot trees in the surrounding landscape of pear orchards did not influence bee abundance and initial fruit set in pear orchards but it decreased seed set. Overall, our findings indicate that apricot trees in pear orchards can enhance bee abundance, but this effect only occurs at a relatively small spatial scale and during a short time span, and does not result in marked differences in pollination success. This indicates that flowering resources need to be close to or within the focal crop to have a positive effect on pollinating insect abundance.

Jin-yu Shi,1,* Ting-ting Li,1,2,* Hui-ting Yang,1 Shi Zhang,2 Ran An,2 Liang Mao,2 Yang Li,2 Qian Li,2 Guang-yi Luan,2 Yan Shen,2 En-long Wang,2 Guang-hui Liu1,2 1First Clinical Medical College, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110847, People’s Republic of China; 2Department of Neurology, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110032, People’s Republic of China*These authors contributed equally to this workCorrespondence: Guang-hui Liu, First Clinical Medical College, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110847, People’s Republic of China; Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, No. 33, Beiling Street, Huanggu District, Shenyang, Liaoning, 110032, People’s Republic of China, Email guanghui04-09@163.comObjective: This study aimed to investigate the features and underlying principles of acupuncture points used in the treatment of headaches associated with blood stasis syndrome.Methods: Literature on the treatment of blood stasis headache with acupuncture and moxibustion was searched across three Chinese databases and one English database from January 1st, 2000, to January 1st, 2024. Relevant data including titles, journals, authors, keywords, interventions, main acupoints, and outcomes were extracted for further analysis.Results: A total of 112 papers with 102 complete prescriptions were analyzed. Of the 77 acupoints examined, 72 were meridian points, and 5 were extraordinary points, used 699 times in total. The top ten acupoints by frequency were Fengchi (GB20), Taiyang (EX-HN5), Baihui (GV20), Hegu (LI4), Shuaigu (GB8), Taichong (LR3), Xuehai (SP10), Touwei (ST8), Geshu (BL17), and Waiguan (TE5). Yang meridian points were used more frequently than Yin meridian points (82.8% vs 17.2%), with the Gallbladder Meridian of Foot Shaoyang being the most common. Nearly

Pingjiao Chen,1,* Jingyao Liang,2,3,* Changxing Li,1 Qian Li,2,3 Wenyan Liu,2,3 Junhui Zhu,2,3 Weifeng Chen,2,3 Xibao Zhang2,3 1Department of Dermatology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, People’s Republic of China; 2Institute of Dermatology, Guangzhou Medical University, Guangzhou, 510095, People’s Republic of China; 3Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou, 510095, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xibao Zhang, Department of Dermatology Guangzhou Institute of Dermatology, 56 Hengfu Road, Guangzhou, 510095, People’s Republic of China, Tel +8620-83593476, Email gzpfbfzs@163.comAbstract: Janus kinase (JAK) inhibitors are increasingly being used in dermatology due to their broad potential in managing both local and systemic inflammation. More recently, abrocitinib, an oral JAK 1 inhibitor, has shown promising clinical efficacy in the treatment of various skin disorders beyond moderate to severe atopic dermatitis (AD). We firstly presented three cases, each with diagnosis of pyoderma gangrenosum (PG), livedoid vasculopathy (LV), or hidradenitis suppurativa (HS), and conducted a comprehensive scoping review of the available literature on the use of abrocitinib in the treatment of diverse skin disorders. We summarized a total of 16 skin disorders, including our cases. The results indicated that abrocitinib, whether used as monotherapy or in combination with other treatments, was effective and well-tolerated in these disorders. These findings expanded the range of diseases for which abrocitinib may serve as an alternative therapeutic choice.Keywords: JAK inhibitors, abrocitinib, atopic dermatitis, pyoderma gangrenosum, livedoid vasculopathy, hidradenitis suppurativa

Yuye Chen,1 Yue Liu,2 Hong Lv,1 Qian Li,1 Jingjia Shen,1 Weiyun Chen,2 Jia Shi,1 Chenghui Zhou3 1Department of Anesthesiology, Fuwai Hospital, Chinese Academy of Medical Sciences&Peking Union Medical College/National Center for Cardiovascular Diseases, Beijing, 100037, People’s Republic of China; 2Department of Anesthesiology, Peking Union Medical College Hospital, Beijing, 100730, People’s Republic of China; 3Center for Anesthesiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, People’s Republic of ChinaCorrespondence: Chenghui Zhou, Center for Anesthesiology, Beijing Anzhen Hospital, Capital Medical University, No. 2 Anzhen Road, Chaoyang District, Beijing, 100029, People’s Republic of China, Tel +86-137-1889-4919, Email chenghuizhou@vip.163.com Jia Shi, Department of Anesthesiology, Fuwai Hospital, Chinese Academy of Medical Sciences&Peking Union Medical College/National Center for Cardiovascular Diseases, No. 167 North Lishi Road, Xicheng District, Beijing, 100037, People’s Republic of China, Email shijia@fuwai.comBackground: The potential myocardial protective effect of nicorandil (NICD) in patients undergoing percutaneous coronary intervention has been established. However, its efficacy in the context of cardiac surgery remains controversial. The present study aimed to evaluate the myocardial protective effect of perioperative NICD use in patients undergoing cardiac surgery with cardiopulmonary bypass (CPB).Methods: We retrospectively gathered data from patients undergoing cardiac bypass surgery between 12/2018 and 04/2021 in Fuwai Hospital. Subsequently, the patients were divided into two groups, NICD group and non-nicorandil (non-NICD) group. A 1, 3 propensity score matching (PSM) was conducted. The primary outcome was the incidence of myocardial injury. The secondary outcomes included the mechanical ventilation (MV) duration, intensive care unit (ICU) length of stay (LOS), hospital LOS, duration of chest drainage

Background: Spinal cord injury (SCI) is a devastating disease that causes extensive damage to oligodendrocytes and neurons leading to demyelination and axonal degeneration. In this study, we co-transplanted cell grafts containing oligodendrocyte progenitor cells (OPCs) derived from human-induced pluripotent stem cells (iPSCs) combined with human umbilical vein endothelial cells (HUVECs), which were reported to promote OPCs survival and migration, into rat contusion models to promote functional recovery after SCI. Methods: OPCs were derived from iPSCs and identified by immunofluorescence at different time points. Functional assays in vitro were performed to evaluate the effect of HUVECs on the proliferation, migration, and survival of OPCs by co-culture and migration assay, as well as on the neuronal axonal growth. A combination of OPCs and HUVECs was transplanted into the rat contusive model. Upon 8 weeks, immunofluorescence staining was performed to test the safety of transplanted cells and to observe the neuronal repairment, myelination, and neural circuit reconstruction at the injured area; also, the functional recovery was assessed by Basso, Beattie, and Bresnahan open-field scale, Ladder climb, SEP, and MEP. Furthermore, the effect of HUVECs on grafts was also determined in vivo. Results: Data showed that HUVECs promote the proliferation, migration, and survival of OPCs both in vitro and in vivo. Furthermore, 8 weeks upon engraftment, the rats with OPCs and HUVECs co-transplantation noticeably facilitated remyelination, enhanced functional connection between the grafts and the host and promoted functional recovery. In addition, compared with the OPCs-alone transplantation, the co-transplantation generated more sensory neurons at the lesion border and significantly improved the sensory functional recovery. Conclusions: Our study demonstrates that transplantation of OPCs combined with HUVECs significantly enhances both motor and sensory functional recovery after

Background: Spinal cord injury (SCI) is a devastating disease that causes extensive damage to oligodendrocytes and neurons leading to demyelination and axonal degeneration. In this study, we co-transplanted cell grafts containing oligodendrocyte progenitor cells (OPCs) derived from human-induced pluripotent stem cells (iPSCs) combined with human umbilical vein endothelial cells (HUVECs), which were reported to promote OPCs survival and migration, into rat contusion models to promote functional recovery after SCI. Methods: OPCs were derived from iPSCs and identified by immunofluorescence at different time points. Functional assays in vitro were performed to evaluate the effect of HUVECs on the proliferation, migration, and survival of OPCs by co-culture and migration assay, as well as on the neuronal axonal growth. A combination of OPCs and HUVECs was transplanted into the rat contusive model. Upon 8 weeks, immunofluorescence staining was performed to test the safety of transplanted cells and to observe the neuronal repairment, myelination, and neural circuit reconstruction at the injured area; also, the functional recovery was assessed by Basso, Beattie, and Bresnahan open-field scale, Ladder climb, SEP, and MEP. Furthermore, the effect of HUVECs on grafts was also determined in vivo. Results: Data showed that HUVECs promote the proliferation, migration, and survival of OPCs both in vitro and in vivo. Furthermore, 8 weeks upon engraftment, the rats with OPCs and HUVECs co-transplantation noticeably facilitated remyelination, enhanced functional connection between the grafts and the host and promoted functional recovery. In addition, compared with the OPCs-alone transplantation, the co-transplantation generated more sensory neurons at the lesion border and significantly improved the sensory functional recovery. Conclusions: Our study demonstrates that transplantation of OPCs combined with HUVECs significantly enhances both motor and sensory functional recovery after

This study aimed to assess the antioxidant activity of golden chlorella (GoC) and grape pomace (GrP) extracts both in vitro and in pea protein-based extrudates. We hypothesized that GoC/GrP would limit oxidation of proteins in the extrudates compared with commercial antioxidants. The results showed that GoC extract was effective in metal chelation and GrP extract possessed excellent radical scavenging activity and reducing power. Protein oxidation inevitably occurred after low-moisture extrusion in terms of elevated level of protein carbonyls and the gradual loss of thiols. LC-MS/MS revealed that the monoxidation and 4-hydroxynonenal adduction were the major oxidative modifications, and legumin was the most susceptible globulin for oxidation. The GoC/GrP extracts effectively retarded the oxidation progress in extrudates by lower intensity of oxidized peptides, whereas protein electrophoretic profiles remained unaffected. This study highlighted the great potential of GoC/GrP as natural antioxidants in plant-based foods.

The rise of business models based on the collection and processing of Big Data allows undertakings to offer customers different prices for the same goods at precisely the same time. This technique is called “AI-enabled price discrimination”. This thesis delves into the economic rationale and technical mechanism of AI-enabled price discrimination in digital markets and compares the legal consequences of (AI-enabled) price discrimination under EU and Chinese competition law (and beyond). This thesis also evaluates whether current legal regimes can effectively tackle concerns caused by anticompetitive and welfare- reducing AI-enabled price discrimination, and provides policy suggestions to the two jurisdictions for considering (AI-enabled) price discrimination as an infringement of competition law (and beyond).

Sacred forests are increasingly disappearing due to increasing land pressure and a decline in cultural values. Protecting the remaining sacred forests plays a crucial role in preserving biodiversity. The existence of remaining old forests often related to local people and their culture, but this relationship has rarely been quantified at large regional scales. This study analyzes the relationship between old forest and ethnic minorities based on the location of the old forest at a high spatial resolution (2 m). We found a significantly positive correlation (p < 0.01) between the proportion of ethnic minority population and old forest patch number, area, aggregation, and maximum patch area. However, there was no correlation with the connectivity of the old forest (p = 0.14). We further show that both environmental and anthropogenic factors are important for the distribution of old forests. Hydrothermal conditions contribute to the growth of forests, and local ethnic customs and the corresponding ecological wisdom contributes to the preservation of old forest remnants (r = 0.12, p < 0.05). Our findings highlight the significance of social dimensions for the conservation of old forests. We encourage that forest management should consider the role of indigenous people and their cultural wisdom for a better conservation and restoration of degraded ecosystems.

Yufeng Liu,1,&ast; Yan Chen,2,&ast; Zhongwen Zhi,1,&ast; Ping Wang,1 Mengchao Wang,1 Qian Li,1 Yuqian Wang,1 Liandong Zhao,1 Chun Chen1 1Department of Neurology, The Affiliated Huai’an Hospital of Xuzhou Medical University and The Second People’s Hospital of Huai’an, Huai’an, Jiangsu, 223002, People’s Republic of China; 2Department of Neurological Medicine, Siyang Hospital of Traditional Chinese Medicine, Siyang, Jiangsu, 223700, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Chun Chen; Liandong Zhao, Department of Neurology, The Affiliated Huai’an Hospital of Xuzhou Medical University and The Second People’s Hospital of Huai’an, No. 62, South Huaihai Road, Huai’an, Jiangsu, 223002, People’s Republic of China, Email hongzecc@163.com; zld202109@163.comPurpose: Stroke-associated pneumonia (SAP) usually complicates stroke and is linked to adverse prognoses. Triglycerides, total cholesterol, and body weight index (TCBI) is a new and simple calculated nutrition index. This study seeks to investigate the association between TCBI and SAP incidence, along with its predictive value.Patients and Methods: Nine hundred and sixty-two patients with acute ischemic stroke were divided into SAP group and Non-SAP group. The TCBI was divided into three layers: T1, TCBI < 948.33; T2, TCBI 948.33– 1647.15; T3, TCBI > 1647.15. Binary Logistic regression analysis was used to determine the relationship between TCBI levels and the incidence of SAP. Furthermore, restricted cubic splines (RCS) analysis was utilized to evaluate the influence of TCBI on the risk of SAP.Results: TCBI in the SAP group was markedly lower compared to that in the Non-SAP group (P < 0.001). The Logistic regression model revealed that, using T3 layer as the reference, T1 layer had the highest risk for SAP prevalence (OR = 2.962, 95% CI: 1.600– 5.485, P = 0.001), with confounding factors being controlled. The RCS model foun

Yuanyuan Su,1,* Ning Lu,2,* Pei Wang,3,* Qian Li,2 Hua Wen,2 Jie Zhang,2 Ling Fan,2 Jie Li,2 Zhaoxiang Yu,4 Manli Cui,2 Mingxin Zhang2 1Department of General Medicine, The People’s Hospital of Yubei District of Chongqing, Chongqing, People’s Republic of China; 2Department of Gastroenterology, The First Affiliated Hospital of Xi’an Medical University, Xi’an, Shaanxi, People’s Republic of China; 3Shaanxi University of Traditional Chinese Medicine, Xianyang, Shaanxi, People’s Republic of China; 4Department of General Surgery, The First Affiliated Hospital of Xi’an Medical University, Xi’an, Shaanxi, People’s Republic of China*These authors contributed equally to this workCorrespondence: Manli Cui, The First Affiliated Hospital of Xi’an Medical University, Xi’an, Shaanxi, Email cuiml1587@163.com; Mingxin Zhang, The First Affiliated Hospital of Xi’an Medical University, Xi’an, Shaanxi, Email zmx3115@xiyi.edu.cn.Objective: This study aims to explore the nexus between students’ psychological well-being and the manifestation of gastrointestinal symptoms (GISs) amid the health lockdown enforced in Xi’an, focusing on the student populace of Xi’an Medical College and Shaanxi University of Traditional Chinese Medicine.Materials and methods: A survey encompassing psychological parameters and GISs was administered to a randomized cohort of 1327 college students drawn from Xi’an Medical College and Shaanxi University of Traditional Chinese Medicine. The survey instrument was developed utilizing the Questionnaire Star platform. Subsequent to data collection, analysis was performed using GraphPad Prism 9 and SPSS 22.0.Results: Comparative analysis revealed statistically significant disparities (P < 0.05) in various GISs between the periods during and preceding the health lockdown, encompassing symptoms such a

Songli Ruan,1,&ast; Xin Wang,2,&ast; Chengjia Zhao,3,&ast; Qian Li,2 Wing Ming Li,2 Guohua Zhang,4,5 Jianshe Pan,4 Xue Yang2 1Mental Health Education and Guidance Center of College Students, Henan University of Urban Construction, Pingdingshan, People’s Republic of China; 2JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, People’s Republic of China; 3School of Mental Health, Wenzhou Medical University, Wenzhou, People’s Republic of China; 4Department of Psychiatry, The Affiliated Kangning Hospital, Wenzhou, People’s Republic of China; 5Zhejiang Provincial Clinical Research Center for Mental Disorders, The Affiliated Wenzhou Kangning Hospital, Wenzhou, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xue Yang, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, People’s Republic of China, Email sherryxueyang@cuhk.edu.hkBackground: Enhancing abstinence motivation of drugs is an effective strategy for the rehabilitation of people who used drugs and prevention of drug use relapse. However, little is known about its risk and protective factors. This study aimed to examine the potential intrapersonal (ie, impulsivity, depression, anxiety, sleep quality) and interpersonal factors (ie, perceived social support) of abstinence motivation among people who completed the community rehabilitation treatment.Methods: A total of 222 participants (mean age = 43; male = 89.2%) were recruited from eleven communities located in Wenzhou, China. Data were collected using a self-reported questionnaire in counselling room settings between April and June 2021.Results: The proportions of participants with depression, anxiety, and poor sleep quality were 38.8%, 19.5%, and 21.2%, respectively. Age and family history of physical disease were significant background factors of abstinence motivation. Impulsivity, depressive symptoms, anxiety sym

This study aimed to assess the antioxidant activity of golden chlorella (GoC) and grape pomace (GrP) extracts both in vitro and in pea protein-based extrudates. We hypothesized that GoC/GrP would limit oxidation of proteins in the extrudates compared with commercial antioxidants. The results showed that GoC extract was effective in metal chelation and GrP extract possessed excellent radical scavenging activity and reducing power. Protein oxidation inevitably occurred after low-moisture extrusion in terms of elevated level of protein carbonyls and the gradual loss of thiols. LC-MS/MS revealed that the monoxidation and 4-hydroxynonenal adduction were the major oxidative modifications, and legumin was the most susceptible globulin for oxidation. The GoC/GrP extracts effectively retarded the oxidation progress in extrudates by lower intensity of oxidized peptides, whereas protein electrophoretic profiles remained unaffected. This study highlighted the great potential of GoC/GrP as natural antioxidants in plant-based foods.

In addition to microbial spoilage and lipid peroxidation, protein oxidation is increasingly recognized as a major cause for quality deterioration of muscle-based foods. Although protein oxidation in muscle-based foods has attracted tremendous interest in the past decade, specific oxidative pathways and underlying mechanisms of protein oxidation in aquatic products remain largely unexplored. The present review covers the aspects of the origin and site-specific nature of protein oxidation, progress on the characterization of protein oxidation, oxidized proteins in aquatic products, and impact of protein oxidation on protein functionalities. Compared to meat protein oxidation, aquatic proteins demonstrate a less extent of oxidation on aromatic amino acids and are more susceptible to be indirectly oxidized by lipid peroxidation products. Different from traditional measurement of protein carbonyls and thiols, proteomics-based strategy better characterizes the targeted oxidation sites within proteins. The future trends using more robust and accurate targeted proteomics, such as parallel reaction monitoring strategy, to characterize protein oxidation in aquatic products are also given.

Deep learning-based monocular depth estimation (MDE), extensively applied in autonomous driving, is known to be vulnerable to adversarial attacks. Previous physical attacks against MDE models rely on 2D adversarial patches, so they only affect a small, localized region in the MDE map but fail under various viewpoints. To address these limitations, we propose 3D Depth Fool (3D$^2$Fool), the first 3D texture-based adversarial attack against MDE models. 3D$^2$Fool is specifically optimized to generate 3D adversarial textures agnostic to model types of vehicles and to have improved robustness in bad weather conditions, such as rain and fog. Experimental results validate the superior performance of our 3D$^2$Fool across various scenarios, including vehicles, MDE models, weather conditions, and viewpoints. Real-world experiments with printed 3D textures on physical vehicle models further demonstrate that our 3D$^2$Fool can cause an MDE error of over 10 meters., Comment: Accepted by CVPR 2024

Few-shot knowledge graph completion (FKGC) aims to query the unseen facts of a relation given its few-shot reference entity pairs. The side effect of noises due to the uncertainty of entities and triples may limit the few-shot learning, but existing FKGC works neglect such uncertainty, which leads them more susceptible to limited reference samples with noises. In this paper, we propose a novel uncertainty-aware few-shot KG completion framework (UFKGC) to model uncertainty for a better understanding of the limited data by learning representations under Gaussian distribution. Uncertainty representation is first designed for estimating the uncertainty scope of the entity pairs after transferring feature representations into a Gaussian distribution. Further, to better integrate the neighbors with uncertainty characteristics for entity features, we design an uncertainty-aware relational graph neural network (UR-GNN) to conduct convolution operations between the Gaussian distributions. Then, multiple random samplings are conducted for reference triples within the Gaussian distribution to generate smooth reference representations during the optimization. The final completion score for each query instance is measured by the designed uncertainty optimization to make our approach more robust to the noises in few-shot scenarios. Experimental results show that our approach achieves excellent performance on two benchmark datasets compared to its competitors.

Social media has become a ubiquitous tool for connecting with others, staying updated with news, expressing opinions, and finding entertainment. However, understanding the intention behind social media posts remains challenging due to the implicitness of intentions in social media posts, the need for cross-modality understanding of both text and images, and the presence of noisy information such as hashtags, misspelled words, and complicated abbreviations. To address these challenges, we present MIKO, a Multimodal Intention Kowledge DistillatiOn framework that collaboratively leverages a Large Language Model (LLM) and a Multimodal Large Language Model (MLLM) to uncover users' intentions. Specifically, we use an MLLM to interpret the image and an LLM to extract key information from the text and finally instruct the LLM again to generate intentions. By applying MIKO to publicly available social media datasets, we construct an intention knowledge base featuring 1,372K intentions rooted in 137,287 posts. We conduct a two-stage annotation to verify the quality of the generated knowledge and benchmark the performance of widely used LLMs for intention generation. We further apply MIKO to a sarcasm detection dataset and distill a student model to demonstrate the downstream benefits of applying intention knowledge., Comment: 11 pages, 5 figures

A comprehensive view of factors associated with AD/ADRD will significantly aid in studies to develop new treatments for AD/ADRD and identify high-risk populations and patients for prevention efforts. In our study, we summarized the risk factors for AD/ADRD by reviewing existing meta-analyses and review articles on risk and preventive factors for AD/ADRD. In total, we extracted 477 risk factors in 10 categories from 537 studies. We constructed an interactive knowledge map to disseminate our study results. Most of the risk factors are accessible from structured Electronic Health Records (EHRs), and clinical narratives show promise as information sources. However, evaluating genomic risk factors using RWD remains a challenge, as genetic testing for AD/ADRD is still not a common practice and is poorly documented in both structured and unstructured EHRs. Considering the constantly evolving research on AD/ADRD risk factors, literature mining via NLP methods offers a solution to automatically update our knowledge map.

Entity alignment (EA) aims to identify entities across different knowledge graphs that represent the same real-world objects. Recent embedding-based EA methods have achieved state-of-the-art performance in EA yet faced interpretability challenges as they purely rely on the embedding distance and neglect the logic rules behind a pair of aligned entities. In this paper, we propose the Align-Subgraph Entity Alignment (ASGEA) framework to exploit logic rules from Align-Subgraphs. ASGEA uses anchor links as bridges to construct Align-Subgraphs and spreads along the paths across KGs, which distinguishes it from the embedding-based methods. Furthermore, we design an interpretable Path-based Graph Neural Network, ASGNN, to effectively identify and integrate the logic rules across KGs. We also introduce a node-level multi-modal attention mechanism coupled with multi-modal enriched anchors to augment the Align-Subgraph. Our experimental results demonstrate the superior performance of ASGEA over the existing embedding-based methods in both EA and Multi-Modal EA (MMEA) tasks., Comment: Ongoing work; 16 pages, 9 Tables, 8 Figures; Code: https://github.com/lyyf2002/ASGEA

Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the semantic web community's exploration into multi-modal dimensions unlocking new avenues for innovation. In this survey, we carefully review over 300 articles, focusing on KG-aware research in two principal aspects: KG-driven Multi-Modal (KG4MM) learning, where KGs support multi-modal tasks, and Multi-Modal Knowledge Graph (MM4KG), which extends KG studies into the MMKG realm. We begin by defining KGs and MMKGs, then explore their construction progress. Our review includes two primary task categories: KG-aware multi-modal learning tasks, such as Image Classification and Visual Question Answering, and intrinsic MMKG tasks like Multi-modal Knowledge Graph Completion and Entity Alignment, highlighting specific research trajectories. For most of these tasks, we provide definitions, evaluation benchmarks, and additionally outline essential insights for conducting relevant research. Finally, we discuss current challenges and identify emerging trends, such as progress in Large Language Modeling and Multi-modal Pre-training strategies. This survey aims to serve as a comprehensive reference for researchers already involved in or considering delving into KG and multi-modal learning research, offering insights into the evolving landscape of MMKG research and supporting future work., Comment: Ongoing work; 41 pages (Main Text), 55 pages (Total), 11 Tables, 13 Figures, 619 citations; Paper list is available at https://github.com/zjukg/KG-MM-Survey

Depto. de Química Analítica, Fac. de Ciencias Químicas, TRUE, pub

Deep learning methods can not only detect false data injection attacks (FDIA) but also locate attacks of FDIA. Although adversarial false data injection attacks (AFDIA) based on deep learning vulnerabilities have been studied in the field of single-label FDIA detection, the adversarial attack and defense against multi-label FDIA locational detection are still not involved. To bridge this gap, this paper first explores the multi-label adversarial example attacks against multi-label FDIA locational detectors and proposes a general multi-label adversarial attack framework, namely muLti-labEl adverSarial falSe data injectiON attack (LESSON). The proposed LESSON attack framework includes three key designs, namely Perturbing State Variables, Tailored Loss Function Design, and Change of Variables, which can help find suitable multi-label adversarial perturbations within the physical constraints to circumvent both Bad Data Detection (BDD) and Neural Attack Location (NAL). Four typical LESSON attacks based on the proposed framework and two dimensions of attack objectives are examined, and the experimental results demonstrate the effectiveness of the proposed attack framework, posing serious and pressing security concerns in smart grids., Comment: Accepted by TDSC

Full-parameter fine-tuning has become the go-to choice for adapting language models (LMs) to downstream tasks due to its excellent performance. As LMs grow in size, fine-tuning the full parameters of LMs requires a prohibitively large amount of GPU memory. Existing approaches utilize zeroth-order optimizer to conserve GPU memory, which can potentially compromise the performance of LMs as non-zero order optimizers tend to converge more readily on most downstream tasks. In this paper, we propose a novel optimizer-independent end-to-end hierarchical fine-tuning strategy, HiFT, which only updates a subset of parameters at each training step. HiFT can significantly reduce the amount of gradients and optimizer state parameters residing in GPU memory at the same time, thereby reducing GPU memory usage. Our results demonstrate that: (1) HiFT achieves comparable performance to parameter-efficient fine-tuning and standard full parameter fine-tuning. (2) HiFT supports various optimizers including AdamW, AdaGrad, SGD, etc. (3) HiFT can save more than 60\% GPU memory compared with standard full-parameter fine-tuning for 7B model. (4) HiFT enables full-parameter fine-tuning of a 7B model on single 48G A6000 with a precision of 32 using the AdamW optimizer, without using any memory saving techniques., Comment: under progress

Text-video retrieval is a challenging task that aims to identify relevant videos given textual queries. Compared to conventional textual retrieval, the main obstacle for text-video retrieval is the semantic gap between the textual nature of queries and the visual richness of video content. Previous works primarily focus on aligning the query and the video by finely aggregating word-frame matching signals. Inspired by the human cognitive process of modularly judging the relevance between text and video, the judgment needs high-order matching signal due to the consecutive and complex nature of video contents. In this paper, we propose chunk-level text-video matching, where the query chunks are extracted to describe a specific retrieval unit, and the video chunks are segmented into distinct clips from videos. We formulate the chunk-level matching as n-ary correlations modeling between words of the query and frames of the video and introduce a multi-modal hypergraph for n-ary correlation modeling. By representing textual units and video frames as nodes and using hyperedges to depict their relationships, a multi-modal hypergraph is constructed. In this way, the query and the video can be aligned in a high-order semantic space. In addition, to enhance the model's generalization ability, the extracted features are fed into a variational inference component for computation, obtaining the variational representation under the Gaussian distribution. The incorporation of hypergraphs and variational inference allows our model to capture complex, n-ary interactions among textual and visual contents. Experimental results demonstrate that our proposed method achieves state-of-the-art performance on the text-video retrieval task.

The seminal work by Impagliazzo and Rudich (STOC'89) demonstrated the impossibility of constructing classical public key encryption (PKE) from one-way functions (OWF) in a black-box manner. However, the question remains: can quantum PKE (QPKE) be constructed from quantumly secure OWF? A recent line of work has shown that it is indeed possible to build QPKE from OWF, but with one caveat -- they rely on quantum public keys, which cannot be authenticated and reused. In this work, we re-examine the possibility of perfect complete QPKE in the quantum random oracle model (QROM), where OWF exists. Our first main result: QPKE with classical public keys, secret keys and ciphertext, does not exist in the QROM, if the key generation only makes classical queries. Therefore, a necessary condition for constructing such QPKE from OWF is to have the key generation classically ``un-simulatable''. Previous discussions (Austrin et al. CRYPTO'22) on the impossibility of QPKE from OWF rely on a seemingly strong conjecture. Our work makes a significant step towards a complete and unconditional quantization of Impagliazzo and Rudich's results. Our second main result extends to QPKE with quantum public keys. The second main result: QPKE with quantum public keys, classical secret keys and ciphertext, does not exist in the QROM, if the key generation only makes classical queries and the quantum public key is either pure or ``efficiently clonable''. The result is tight due to all existing QPKEs constructions. Our result further gives evidence on why existing QPKEs lose reusability. To achieve these results, we use a novel argument based on conditional mutual information and quantum Markov chain by Fawzi and Renner (Communications in Mathematical Physics). We believe the techniques used in the work will find other usefulness in separations in quantum cryptography/complexity.

Tissue deformation poses a key challenge for accurate surgical scene reconstruction. Despite yielding high reconstruction quality, existing methods suffer from slow rendering speeds and long training times, limiting their intraoperative applicability. Motivated by recent progress in 3D Gaussian Splatting, an emerging technology in real-time 3D rendering, this work presents a novel fast reconstruction framework, termed Deform3DGS, for deformable tissues during endoscopic surgery. Specifically, we introduce 3D GS into surgical scenes by integrating a point cloud initialization to improve reconstruction. Furthermore, we propose a novel flexible deformation modeling scheme (FDM) to learn tissue deformation dynamics at the level of individual Gaussians. Our FDM can model the surface deformation with efficient representations, allowing for real-time rendering performance. More importantly, FDM significantly accelerates surgical scene reconstruction, demonstrating considerable clinical values, particularly in intraoperative settings where time efficiency is crucial. Experiments on DaVinci robotic surgery videos indicate the efficacy of our approach, showcasing superior reconstruction fidelity PSNR: (37.90) and rendering speed (338.8 FPS) while substantially reducing training time to only 1 minute/scene. Our code is available at https://github.com/jinlab-imvr/Deform3DGS., Comment: Early accepted at MICCAI 2024, 10 pages, 2 figures

Multi-modal relation extraction (MMRE) is a challenging task that aims to identify relations between entities in text leveraging image information. Existing methods are limited by their neglect of the multiple entity pairs in one sentence sharing very similar contextual information (ie, the same text and image), resulting in increased difficulty in the MMRE task. To address this limitation, we propose the Variational Multi-Modal Hypergraph Attention Network (VM-HAN) for multi-modal relation extraction. Specifically, we first construct a multi-modal hypergraph for each sentence with the corresponding image, to establish different high-order intra-/inter-modal correlations for different entity pairs in each sentence. We further design the Variational Hypergraph Attention Networks (V-HAN) to obtain representational diversity among different entity pairs using Gaussian distribution and learn a better hypergraph structure via variational attention. VM-HAN achieves state-of-the-art performance on the multi-modal relation extraction task, outperforming existing methods in terms of accuracy and efficiency.

We introduce a new notion of information complexity for multi-pass streaming problems and use it to resolve several important questions in data streams. In the coin problem, one sees a stream of $n$ i.i.d. uniform bits and one would like to compute the majority with constant advantage. We show that any constant pass algorithm must use $\Omega(\log n)$ bits of memory, significantly extending an earlier $\Omega(\log n)$ bit lower bound for single-pass algorithms of Braverman-Garg-Woodruff (FOCS, 2020). This also gives the first $\Omega(\log n)$ bit lower bound for the problem of approximating a counter up to a constant factor in worst-case turnstile streams for more than one pass. In the needle problem, one either sees a stream of $n$ i.i.d. uniform samples from a domain $[t]$, or there is a randomly chosen needle $\alpha \in[t]$ for which each item independently is chosen to equal $\alpha$ with probability $p$, and is otherwise uniformly random in $[t]$. The problem of distinguishing these two cases is central to understanding the space complexity of the frequency moment estimation problem in random order streams. We show tight multi-pass space bounds for this problem for every $p < 1/\sqrt{n \log^3 n}$, resolving an open question of Lovett and Zhang (FOCS, 2023); even for $1$-pass our bounds are new. To show optimality, we improve both lower and upper bounds from existing results. Our information complexity framework significantly extends the toolkit for proving multi-pass streaming lower bounds, and we give a wide number of additional streaming applications of our lower bound techniques, including multi-pass lower bounds for $\ell_p$-norm estimation, $\ell_p$-point query and heavy hitters, and compressed sensing problems., Comment: To appear in STOC 2024

Vulnerability detection is crucial for ensuring the security and reliability of software systems. Recently, Graph Neural Networks (GNNs) have emerged as a prominent code embedding approach for vulnerability detection, owing to their ability to capture the underlying semantic structure of source code. However, GNNs face significant challenges in explainability due to their inherently black-box nature. To this end, several factual reasoning-based explainers have been proposed. These explainers provide explanations for the predictions made by GNNs by analyzing the key features that contribute to the outcomes. We argue that these factual reasoning-based explanations cannot answer critical what-if questions: What would happen to the GNN's decision if we were to alter the code graph into alternative structures? Inspired by advancements of counterfactual reasoning in artificial intelligence, we propose CFExplainer, a novel counterfactual explainer for GNN-based vulnerability detection. Unlike factual reasoning-based explainers, CFExplainer seeks the minimal perturbation to the input code graph that leads to a change in the prediction, thereby addressing the what-if questions for vulnerability detection. We term this perturbation a counterfactual explanation, which can pinpoint the root causes of the detected vulnerability and furnish valuable insights for developers to undertake appropriate actions for fixing the vulnerability. Extensive experiments on four GNN-based vulnerability detection models demonstrate the effectiveness of CFExplainer over existing state-of-the-art factual reasoning-based explainers., Comment: This paper was accepted in the proceedings of the 33nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2024)

The ability to make good decisions is critical in life. Although anecdotal and preliminary evidence suggests that social comparison could impair decision making, surprisingly little attention has been paid to such dynamics within cognitive science. The present study aimed to address this gap by exploring, via a sample of 1.5 million chess games and a fuzzy regression discontinuity design, whether higher status of competitors could cause individuals to commit more errors. Critically, chess data includes overt symbols of social status, viz. titles conferred at arbitrary thresholds of ratings that represent playing strength, and an objective measure of errors could be calculated by contrasting the moves that players chose in games against the optimal moves determined by powerful chess engines. I found no evidence that the mere presence of status titles impacted error rates.

A half-cell that is composed of electrode and metal (e.g., lithium) is the most classical model for examining electrode performance in battery community, by which the voltage versus capacity profile is the important indicator. However, it is found that these results are not all reliable, as a misconception of electrode performance can be caused once the electrolyte is chemically unstable. As a paradigm, it is demonstrated that the diethyl carbonate (DEC) solvent can chemically react with lithium metal to form insoluble and soluble by-products, which can accumulate on the lithium anode to influence the lithium potential and/or migrate to the counter electrode to proceed with the uncompleted electrochemical reactions. The resultant voltage-capacity profile cannot reflect the actual electrode performance, such as the lithium storing capability within the graphite. The reason for this phenomenon is elucidated based on solvation chemistry, particularly the mechanism of mitigating it by introducing ethylene carbonatesolvent to form new hydrogen bonds. The viewpoint is further verified by employing the full cell and also extended in sodium and potassium batteries. This study shows the necessity of discerning the reliability of electrode performance and also sheds light on the importance of designing a compatible electrolyte to examine electrode performance.

Background Mitochondrial dysfunction in kidney cells has been implicated in the pathogenesis of chronic kidney disease (CKD). Estimation of mitochondrial DNA copy number (mtDNA-CN) is considered a convenient method for representing mitochondrial function in large samples. However, no study has investigated the association between mtDNA-CN and CKD in older adults with the highest prevalence. The objective is to examine cross-sectional and prospective associations between mtDNA-CN values and CKD risk in older adults to determine whether mtDNA-CN represents a novel potential biomarker for the recognition of CKD risk. Patients and methods In a Chinese community-based cohort of over 65-year-olds, we included 14,467 participants (52.6% females). CKD was defined by eGFR < 60 mL/min/1.73 m(2) or ICD-10 codes (patients = 3831 (26.5%)). Participants had peripheral blood levels of mtDNA-CN calculated from probe intensities of the Axiom CAS Array. Results The risk of CKD prevalence decreased with mtDNA-CN per 1-SD increment, independent of established risk factors for older CKD (odds ratio [OR] per SD 0.90, 95% confidence interval [CI] 0.86, 0.93, P < 0.001), and has comparable strength of association with these established risk factors. Furthermore, the progression of kidney function was stratified according to the worsening of eGFR categories. The risk of kidney function progression to a more severe stage gradually decreased as the mtDNA-CN increased (P trend < 0.001). Non-CKD participants in the highest quartile of mtDNA-CN had a lower risk of developing CKD compared to the lowest quartile within 2 years of follow-up, reducing the risk of CKD by 36% (95% CI 0.42, 0.97; P = 0.037). Conclusions Based on the analysis of the largest sample to date investigating the association between mtDNA-CN and CKD in older adults, higher levels of mtDNA-CN were found to be associated with a lower risk of CKD, suggesting that a reduced level of mtDNA-CN is a potential ris, Funding Agencies|The authors would like to thank all the participants in this study.

Background Mitochondrial dysfunction in kidney cells has been implicated in the pathogenesis of chronic kidney disease (CKD). Estimation of mitochondrial DNA copy number (mtDNA-CN) is considered a convenient method for representing mitochondrial function in large samples. However, no study has investigated the association between mtDNA-CN and CKD in older adults with the highest prevalence. The objective is to examine cross-sectional and prospective associations between mtDNA-CN values and CKD risk in older adults to determine whether mtDNA-CN represents a novel potential biomarker for the recognition of CKD risk. Patients and methods In a Chinese community-based cohort of over 65-year-olds, we included 14,467 participants (52.6% females). CKD was defined by eGFR < 60 mL/min/1.73 m(2) or ICD-10 codes (patients = 3831 (26.5%)). Participants had peripheral blood levels of mtDNA-CN calculated from probe intensities of the Axiom CAS Array. Results The risk of CKD prevalence decreased with mtDNA-CN per 1-SD increment, independent of established risk factors for older CKD (odds ratio [OR] per SD 0.90, 95% confidence interval [CI] 0.86, 0.93, P < 0.001), and has comparable strength of association with these established risk factors. Furthermore, the progression of kidney function was stratified according to the worsening of eGFR categories. The risk of kidney function progression to a more severe stage gradually decreased as the mtDNA-CN increased (P trend < 0.001). Non-CKD participants in the highest quartile of mtDNA-CN had a lower risk of developing CKD compared to the lowest quartile within 2 years of follow-up, reducing the risk of CKD by 36% (95% CI 0.42, 0.97; P = 0.037). Conclusions Based on the analysis of the largest sample to date investigating the association between mtDNA-CN and CKD in older adults, higher levels of mtDNA-CN were found to be associated with a lower risk of CKD, suggesting that a reduced level of mtDNA-CN is a potential ris, Funding Agencies|The authors would like to thank all the participants in this study.

Background Mitochondrial dysfunction in kidney cells has been implicated in the pathogenesis of chronic kidney disease (CKD). Estimation of mitochondrial DNA copy number (mtDNA-CN) is considered a convenient method for representing mitochondrial function in large samples. However, no study has investigated the association between mtDNA-CN and CKD in older adults with the highest prevalence. The objective is to examine cross-sectional and prospective associations between mtDNA-CN values and CKD risk in older adults to determine whether mtDNA-CN represents a novel potential biomarker for the recognition of CKD risk. Patients and methods In a Chinese community-based cohort of over 65-year-olds, we included 14,467 participants (52.6% females). CKD was defined by eGFR < 60 mL/min/1.73 m(2) or ICD-10 codes (patients = 3831 (26.5%)). Participants had peripheral blood levels of mtDNA-CN calculated from probe intensities of the Axiom CAS Array. Results The risk of CKD prevalence decreased with mtDNA-CN per 1-SD increment, independent of established risk factors for older CKD (odds ratio [OR] per SD 0.90, 95% confidence interval [CI] 0.86, 0.93, P < 0.001), and has comparable strength of association with these established risk factors. Furthermore, the progression of kidney function was stratified according to the worsening of eGFR categories. The risk of kidney function progression to a more severe stage gradually decreased as the mtDNA-CN increased (P trend < 0.001). Non-CKD participants in the highest quartile of mtDNA-CN had a lower risk of developing CKD compared to the lowest quartile within 2 years of follow-up, reducing the risk of CKD by 36% (95% CI 0.42, 0.97; P = 0.037). Conclusions Based on the analysis of the largest sample to date investigating the association between mtDNA-CN and CKD in older adults, higher levels of mtDNA-CN were found to be associated with a lower risk of CKD, suggesting that a reduced level of mtDNA-CN is a potential ris, Funding Agencies|The authors would like to thank all the participants in this study.

Abstract. As the climate warms, the grounded ice sheet and floating ice shelves surrounding Antarctica are melting and releasing additional freshwater into the Southern Ocean. Nonetheless, almost all existing coupled climate models have fixed ice sheets and lack the physics required to represent the dominant sources of Antarctic melt. These missing ice dynamics represent a key uncertainty that is typically unaccounted for in current global climate change projections. Previous modelling studies that have imposed additional Antarctic meltwater have demonstrated regional impacts on Southern Ocean stratification, circulation, and sea ice, as well as remote changes in atmospheric circulation, tropical precipitation, and global temperature. However, these previous studies have used widely varying rates of freshwater forcing, have been conducted using different climate models and configurations, and have reached differing conclusions on the magnitude of meltwater–climate feedbacks. The Southern Ocean Freshwater Input from Antarctica (SOFIA) initiative brings together a team of scientists to quantify the climate system response to Antarctic meltwater input along with key aspects of the uncertainty. In this paper, we summarize the state of knowledge on meltwater discharge from the Antarctic ice sheet and ice shelves to the Southern Ocean and explain the scientific objectives of our initiative. We propose a series of coupled and ocean–sea ice model experiments, including idealized meltwater experiments, historical experiments with observationally consistent meltwater input, and future scenarios driven by meltwater inputs derived from stand-alone ice sheet models. Through coordinating a multi-model ensemble of simulations using a common experimental design, open data archiving, and facilitating scientific collaboration, SOFIA aims to move the community toward better constraining our understanding of the climate system response to Antarctic melt.

This work forms a part of the contribution to the ”1st FOWT comparative study” for modelling floating offshore wind turbine (FOWT) hydrodynamics based on the wave tank tests of a 1:70 scaled moored VolturnUS semi-submersible floater model. Two sets of test cases have been simulated-one is a static equilibrium test and the other is the heave decay test to determine the natural frequencies of the coupled floater mooring system. The numerical modelling is carried out in a numerical wave tank using high-fidelity computational fluid dynamics based on the OpenFOAM toolbox and the results are generally in good agreement with the experimental measurements. In addition, it was found that the mooring lines have a significant influence on the pitch natural frequencies of the coupled system but their impact on the heave natural frequencies was minimal.

Rongcheng An,1 Yingwei Ou,1 Lingxiao Pang,1 Yongsheng Yuan,1 Qian Li,1 Hao Xu,2 Bin Sheng1 1Emergency and Critical Care Center, Department of Emergency Medicine, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital, Hangzhou Medical College), Hangzhou, People’s Republic of China; 2Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, People’s Republic of ChinaCorrespondence: Bin Sheng, Emergency and Critical Care Center, Department of Emergency Medicine, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital, Hangzhou Medical College), Hangzhou, People’s Republic of China, Tel +86 571 85893793, Email shengbin@hmc.edu.cnPurpose: Community-associated bloodstream infection (CA-BSI) is increasing in many community settings. However, the clinical significance and epidemiology of CA-BSI present in hospital admissions in China are not well established. In this work, we identified the risk factors in outpatients presenting with CA-BSI, and investigate the role of procalcitonin (PCT) and hypersensitive C-reactive protein (CRP) in diagnosing different types of the pathogen in patients with acute CA-BSI.Methods: A retrospective study enrolling 219 outpatients with CA-BSI from The Zhejiang People’s Hospital from January 2017 to December 2020 was performed. Susceptibility of the isolates obtained from these patients was examined. Subjecting receiver operating characteristic curves (ROC) were constructed to analyze the specificity and sensitivity of PCT, CRP, and WBC in determining infections caused by different bacterial genera. Risk factors for CA-BSI in the emergency setting were analyzed using essential information and simple identification of other pathogenic bacterial species through rapidly tested biomarkers.Results: A total of 219 patients were i

Ting Chen,1,2,&ast; Lei Zhang,3,&ast; Wenhua Huang,3,&ast; Huijun Zong,1,2 Qian Li,3 Yuling Zheng,3 Qingyu Lv,3 Decong Kong,3 Yuhao Ren,3 Yongqiang Jiang,3 Yan Li,1,2 Peng Liu3 1The PLA 307 Clinical College of Anhui Medical University, The Fifth Clinical Medical College of Anhui Medical University, Hefei, People’s Republic of China; 2Department of Critical Care Medicine, The Fifth Medical Center, Chinese PLA General Hospital, Beijing, 100071, People’s Republic of China; 3State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yan Li, The PLA 307 Clinical College of Anhui Medical University, The Fifth Clinical Medical College of Anhui Medical University, Hefei, 230032, People’s Republic of China, Email liyanmdhuxi@163.com Peng Liu, Beijing Institute of Microbiology and Epidemiology, Dongdajie Road 20, Beijing, 100071, People’s Republic of China, Tel +86-010-66948487, Email ammsliupeng@163.comBackground: The early identification of pathogens and their antibiotic resistance are essential for the management and treatment of patients affected by ventilator-associated pneumonia (VAP). However, microbiological culture may be time-consuming and has a limited culturability of many potential pathogens. In this study, we developed a rapid nanopore-based metagenomic next-generation sequencing (mNGS) diagnostic assay for detection of VAP pathogens and antimicrobial resistance genes (ARGs).Patients and Methods: Endotracheal aspirate (ETA) samples from 63 patients with suspected VAP were collected between November 2021 and July 2022. Receiver operating characteristic (ROC) curves were established to compare the pathogen identification performance of the target pathogen reads, reads percent of microbes (RPM) and relative abundance (RA). The evaluation of the accuracy of mNG

In this study, the spatial distribution and accumulation dynamics of volatile oil in Angelica sinensis roots was realized by fluorescence imaging combined with mass spectrometry imaging. The laser scanning confocal microscopy was used to determine the optimal excitation wavelength and the fluorescent stability of volatile oil in the sections of Angelica sinensis roots. The results demonstrated that 488 nm was the most suitable excitation wavelength for the identification and quantitative analysis of volatile oil. It was observed that volatile oil accumulated in the oil chamber of the phelloderm and secondary phloem, and the oil canal of the secondary xylem. The results also indicated that there were differences in content during different periods. Furthermore, the MALDI-TOF-MSI technology was used to study the spatial distribution and compare the chemical compositions of different parts of Angelica sinensis roots during the harvest period. A total of 55, 49, 50 and 30 compounds were identified from the head, body, tail of the root and root bark, respectively. The spatial distribution of phthalides, organic acids and other compounds were revealed in Angelica sinensis roots. The method developed in this study could be used for the in situ analysis of volatile oil in Angelica sinensis roots.

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become an urgent public health problem. Spike (S) protein mediates the fusion between the virus and the host cell membranes, consequently emerging as an important target of drug design. The lack of comparisons of in situ full-length S homotrimer structures in different states hinders understanding the structures and revealing the function, thereby limiting the discovery and development of therapeutic agents. Here, the steady-state structures of the in situ full-length S trimer in closed and open states (Sclosed and Sopen) were modeled with the constraints of density maps, associated with the analysis of the dynamic structural differences. Subsequently, we identified various regions with structure and property differences as potential binding pockets for ligands that promote the formation of inactive trimeric protein complexes. By using virtual screening strategy and a newly defined druggable cavity, five ligands were screened with potential bioactivities. Then molecular dynamic (MD) simulations were performed on apo protein structures and ligand bound complexes to reveal the conformational changes upon ligand binding. Our simulation results revealed that sulforaphane (SFN), which has the best binding affinity, could inhibit the conformational changes of S homotrimer that would occur during the viral membrane fusion. Our results could aid in the understanding of the regulation mechanism of S trimer aggregation and the structure-activity relationship, facilitating the development of potential antiviral agents.

The advent of van der Waals (vdW) ferromagnetic (FM) and antiferromagnetic (AFM) materials offers unprecedented opportunities for spintronics and magneto-optic devices. Combining magnetic Kerr microscopy and density functional theory calculations, the AFM-FM transition is investigated and a surprising abnormal magneto-optic anisotropy in vdW CrSBr associated with different magnetic phases (FM, AFM, or paramagnetic state) is discovered. This unique magneto-optic property leads to different anisotropic optical reflectivity from different magnetic states, permitting direct imaging of the AFM Néel vector orientation and the dynamic process of the AFM-FM transition within a magnetic field. Using Kerr microscopy, not only the domain nucleation and propagation process is imaged but also the intermediate spin-flop state in the AFM-FM transition is identified. The unique magneto-optic property and clear identification of the dynamics process of the AFM-FM phase transition in CrSBr demonstrate the promise of vdW magnetic materials for future spintronic technology.

The creation of van der Waals (vdW) ferromagnets with tunable Curie temperature (TC) and magnetic anisotropy is essential in developing vdW magnet-based devices. Here, we report an effective and reliable method for modulating the magnetic properties of vdW Fe5GeTe2 by site-specific Ga+ implantation. In this study, we report an easy axis in the ab-plane for bulk Fe5GeTe2 (TC = 310 K) and an axis out of the plane for thin Fe5GeTe2 flakes (TC = 290 K). Combining element-resolved photoemission electron microscopy and spatially resolved magneto-optic Kerr microscopy, we find that the implantation of a tiny amount of 10−3 Ga+·Å−3 in Fe5GeTe2 greatly enhances the TC from 290 to 360 K and switches the magnetic easy axis from the out-of-plane c axis to the ab-plane. The room-temperature x-ray magnetic circular dichroism signal is enhanced from 0% to 9% at an implantation level of 10−2 Ga+·Å−3. These results provide new opportunities for tailoring the magnetic properties of vdW materials beyond room temperature.