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Currently, many countries and regions worldwide face the challenge of declining population growth due to persistently low rates of female reproduction. Since 2017, China's birth rate has hit historic lows and continued to decline, with the death rate now equaling the birth rate. Concerns have emerged regarding the potential impact of environmental contaminants on reproductive health, including pregnancy loss. Endocrine-disrupting chemicals (EDCs) like phthalate esters (PAEs), bisphenol A (BPA), triclosan (TCS), and perfluoroalkyl substances (PFASs) have raised attention due to their adverse effects on biological systems. While China's 14th Five-Year Plan (2021–2025) for national economic and social development included the treatment of emerging pollutants, including EDCs, there are currently no national appraisal standards or regulatory frameworks for EDCs and their mixtures. Addressing the risk of EDC mixtures is an urgent matter that needs consideration from China's perspective in the near future. In this Perspective, we delve into the link between EDC mixture exposure and pregnancy loss in China. Our focus areas include establishing a comprehensive national plan targeting reproductive-aged women across diverse urban and rural areas, understanding common EDC combinations in women and their surrounding environment, exploring the relationship between EDCs and pregnancy loss via epidemiology, and reconsidering the safety of EDCs, particularly in mixtures and low-dose scenarios. We envision that this study could aid in creating preventive strategies and interventions to alleviate potential risks induced by EDC exposure during pregnancy in China.

Abstract Background Neoadjuvant chemotherapy (NAC) is an effective treatment for locally advanced breast cancer (BC). However, there are no effective biomarkers for evaluating its efficacy. CDR1-AS, well known for its important role in tumorigenesis, is a famous circular RNA involved in the chemosensitivity of cancers other than BC. However, the predictive role of CDR1-AS in the efficacy and prognosis of NAC for BC has not been fully elucidated. We herein aimed to clarify this role. Methods The present study included patients treated with paclitaxel-cisplatin-based NAC. The expression of CDR1-AS was detected by real-time quantitative reverse transcription polymerase chain reaction testing. The predictive value of CDR1-AS expression was examined in pathological complete response (pCR) after NAC using logistic regression analysis. The relationship between CDR1-AS expression and survival was demonstrated using the Kaplan–Meier method, and tested by log-rank test and Cox proportional hazards regression model. Results The present study enrolled 106 patients with BC. Multivariate logistic regression analysis revealed that CDR1-AS expression was an independent predictive factor for pCR (odds ratio [OR] = 0.244; 95% confidence interval [CI] 0.081–0.732; p = 0.012). Furthermore, pCR benefits with low CDR1-AS expression were observed across all subgroups. The Kaplan–Meier curves and log-rank test suggested that the CDR1-AS high-expression group showed significantly better disease-free survival (DFS; log-rank p = 0.022) and relapse-free survival (RFS; log-rank p = 0.012) than the CDR1-AS low-expression group. Multivariate analysis revealed that CDR1-AS expression was an independent prognostic factor for DFS (adjusted HR = 0.177; 95% CI 0.034–0.928, p = 0.041), RFS (adjusted HR = 0.061; 95% CI 0.006–0.643, p = 0.020), and distant disease-free survival (adjusted HR = 0.061; 95% CI 0.006–0.972, p = 0.047). Conclusions CDR1-AS may be a potential novel predictive biomarker of pCR and survival benefit in patients with locally advanced BC receiving NAC. This may help identify specific chemosensitive individuals and build personalized treatment strategies.

Abstract BackgroundRemovable partial denture (RPD) design is crucial to long-term success in dental treatment, but shortcomings in RPD design training and competency acquisition among dental students have persisted for decades. Digital production is increasing in prevalence in stomatology, and a digital RPD (D-RPD) module, under the framework of the certified Objective Manipulative Skill Examination of Dental Technicians (OMEDT) system reported in our previous work, may improve on existing RPD training models for students. ObjectiveWe aimed to determine the efficacy of a virtual 3D simulation–based progressive digital training module for RPD design compared to traditional training. MethodsWe developed a prospective cohort study including dental technology students at the Stomatology College of Chongqing Medical University. Cohort 1 received traditional RPD design training (7 wk). Cohort 2 received D-RPD module training based on text and 2D sketches (7 wk). Cohort 3 received D-RPD module pilot training based on text and 2D sketches (4 wk) and continued to receive training based on 3D virtual casts of real patients (3 wk). RPD design tests based on virtual casts were conducted at 1 month and 1 year after training. We collected RPD design scores and the time spent to perform each assessment. ResultsWe collected the RPD design scores and the time spent to perform each assessment at 1 month and 1 year after training. The study recruited 109 students, including 58 (53.2%) female and 51 male (56.8%) students. Cohort 1 scored the lowest and cohort 3 scored the highest in both tests (cohorts 1-3 at 1 mo: mean score 65.8, SD 21.5; mean score 81.9, SD 6.88; and mean score 85.3, SD 8.55, respectively; PPPPPPP ConclusionsCohort 3 obtained the highest score at both time points with retention of competency at 1 year, indicating that progressive D-RPD training including virtual 3D simulation facilitated improved competency in RPD design. The adoption of D-RPD training may benefit learning outcomes.

Over the past few decades, conjugate heat transfer (CHT) technology has been instrumental in predicting temperature fields within aerospace engines, guiding engine design with its predictive capabilities. This paper comprehensively surveys the foundational technologies of CHT and their applications in engine design, backed by an extensive literature review. A novel coupling iteration methodology, su-F-TFTB, was proposed. Following this, it introduced grid splicing technology tailored for heat flux conservation, which significantly enhances the adaptability of CHT grids. Ultimately, this study employed the self-developed Aerospace Engine Numerical Simulation (AENS v4.0.1) software to perform CHT analyses on NASA-C3X turbine blades equipped with ten radial cooling systems. A comparative analysis of pressure distributions across various density meshes was undertaken to affirm mesh independence. Furthermore, the impacts of the Spalart–Allmaras (SA) one-equation model and k–ω Shear Stress Transport (SST) two-equation model on the temperature distribution in conjugate heat transfer were investigated. The results indicated that the k–ω SST model exhibited superior performance, aligning closely with NASA experimental data. This validation confirmed the effectiveness of the software.

Introduction: Mitochondrial quality control (MQC) is an important mechanism of neural repair after cerebral ischemia (CI). Recent studies have shown that caveolin-1 (Cav-1) is an important signaling molecule in the process of CI injury, but its mechanism of regulating MQC after CI is still unclear. Buyang Huanwu Decoction (BHD) is a classic traditional Chinese medicine formula that is often used to treat CI. Unfortunately, its mechanism of action is still obscure.Methods: In this study, we tested the hypothesis that BHD can regulate MQC through Cav-1 and exert an anti-cerebral ischemia injury effect. We used Cav-1 knockout mice and their homologous wild-type mice, replicated middle cerebral artery occlusion (MCAO) model and BHD intervention. Neurobehavioral scores and pathological detection were used to evaluate neurological function and neuron damage, transmission electron microscopy and enzymology detection of mitochondrial damage. Finally, western blot and RT-qPCR expression of MQC-related molecules were tested.Results: After CI, mice showed neurologic impairment, neuronal damage, and significant destruction of mitochondrial morphology and function, and MQC was imbalanced. Cav-1 deletion aggravated the damage to neurological function, neurons, mitochondrial morphology and mitochondrial function after CI, aggravated the imbalance of mitochondrial dynamics, and inhibited mitophagy and biosynthesis. BHD can maintain MQC homeostasis after CI through Cav-1 and improve CI injury.Discussion: Cav-1 can affect CI injury by regulating MQC, and this mechanism may be another target of BHD for anti-cerebral ischemia injury.

Abstract Parkinson’s disease (PD) is a multi-stage neurodegenerative disorder with largely unknown etiology. Recent findings have identified PD-associated autoimmune features including roles for T cells. To further characterize the role of T cells in PD, we performed RNA sequencing on PBMC and peripheral CD4 and CD8 memory T cell subsets derived from PD patients and age-matched healthy controls. When the groups were stratified by their T cell responsiveness to alpha-synuclein (α-syn) as a proxy for an ongoing inflammatory autoimmune response, the study revealed a broad differential gene expression profile in memory T cell subsets and a specific PD associated gene signature. We identified significant enrichment of transcriptomic signatures previously associated with PD, including for oxidative stress, phosphorylation, autophagy of mitochondria, cholesterol metabolism and inflammation, and the chemokine signaling proteins CX3CR1, CCR5, and CCR1. In addition, we identified genes in these peripheral cells that have previously been shown to be involved in PD pathogenesis and expressed in neurons, such as LRRK2, LAMP3, and aquaporin. Together, these findings suggest that features of circulating T cells with α-syn-specific responses in PD patients provide insights into the interactive processes that occur during PD pathogenesis and suggest potential intervention targets.

The network is a key concept which has been highly valued in connectivism. Research about the static characteristics of social networks in connectivist learning has been carried out in recent years, however, little knowledge exists regarding the principles of network evolution from a dynamic perspective. This article chose the first connectivist massive open and online course (cMOOC) in China, “Internet plus Education: Dialogue between Theory and Practice” as the research object, using the dynamic analysis method of social networks which is based on stochastic actor-oriented models, to reveal the influence of the individual attributes and network structural attributes on the dynamic evolution of social networks in a cMOOC. We found that: 1) the learners with the same sex, the same social identity, and the same type of behaviour tendency found it much easier to interact with each other; 2) there is a heterogeneous phenomenon with course identity, meaning that compared to communicating with other learners, learners are more inclined to reply to a facilitator; and 3) the reciprocity and transitivity have significant effects on social network evolution. This study is valuable for understanding the network evolution and has implications for the improvement of cMOOC design, in turn improving the online learning experience for cMOOC learners.

As a learning theory that reveals a new learning in the Internet environment, connectivism has become a popular academic topic at the forefront of online learning. The MOOC Research Team at the Distance Education Research Centre at Beijing Normal University designed and developed the first massive open online course, adapting a connectivist (cMOOC) approach in China. Using the data collected from six offerings of the cMOOC over 3 years, the big data paradigm was used for data analysis including complex network analysis, content analysis, text mining, behaviour sequence analysis, epistemic network analysis, and statistical and econometric models. This paper summarizes the findings of the patterns of connectivist learning, including a) the basic characteristics and evolutional patterns of complex networks, b) the characteristics and modes of knowledge production, c) the patterns of instructional interactions, and d) the relationships between pipe and content and between facilitators and learners. It is expected that the outcome of this study could make contributions to understanding the changes of online learning in depth and further promote the theoretical development and practical application of a connectivist approach.

Cerebral ischemia-reperfusion injury (CIRI) is common in ischemic stroke and seriously affects the prognosis of patients. At present, N6-methyladenosine (m6A) modification of lncRNAs and mRNAs has been reported in other diseases, such as cancer, but its role in CIRI has not been clarified. In this study, we aimed to investigate the m6A lncRNA and m6A mRNA modification profiles in CIRI. First, we detected the total level of m6A and the changes in related m6A methyltransferases and demethylases in the brain tissue of rats with CIRI and then identified differentially modified lncRNAs and mRNAs in CIRI by lncRNA and mRNA epigenetic transcriptomic microarray. In addition, bioinformatics analysis was used to predict the underlying functions and related pathways of related lncRNAs and mRNAs. We found that the total m6A methylation level was significantly increased, and the expression of fat mass and obesity-associated protein (FTO) was downregulated after CIRI. In addition, a large number of m6A-modified lncRNAs and mRNAs appeared after CIRI, and these genes were mainly enriched for the Toll-like receptor signaling pathway, peroxisome proliferator-activated receptor (PPAR) signaling pathway, and mitogen-activated protein kinase (MAPK) signaling pathway. Our findings provide the basis and insights for further studies on m6A modification in CIRI.

BackgroundWe sought to explore the impact of changing treatment strategy based on circulating tumor cells (CTC) on postoperative survival of breast cancer.MethodsWe retrospectively analyzed records of patients who underwent surgery for early-stage breast cancer at Beijing Friendship Hospital from January 2016 to January 2018 and regularly underwent CTC examination after surgery. During the regular examination and CTC monitoring, the patients with positive CTC results and without distant metastasis had their treatment regimen changed.ResultsOf 109 patients who received CTC examination regularly after surgery, 61 (56.0%) were CTC-positive during postoperative follow-up, including 33 ER or PR-positive, and 28 ER and PR-negative patients. Of the 33 ER or PR-positive patients, 20 changed endocrine therapy drugs. Compared with those without replacement, those with changed endocrine therapy strategy had higher CTC clearance rates (90.0% vs. 53.8%, p=0.04) and significantly lower CTC-positive values (1.70 ± 1.72 vs. 0.62 ± 0.65, p = 0.04). Among the 28 patients who were CTC positive and ER and PR-negative, 11 used capecitabine. Compared with non-users, the capecitabine users had higher CTC clearance rates (100.0% vs. 52.9%, p=0.01) and more significant decrease in CTC-positive values (2.09 ± 1.14 vs. 0.82 ± 1.67, p=0.04). Disease-free survival (DFS) at 1, 3, and 5 years was significantly longer in those who changed treatment than in those who did not (respectively, 96.6% vs. 89.6%, 92.8% vs. 56.9%, 69.0% vs. 47.8%, p

The gut microbiota plays an important role in central nervous system (CNS) disorders. Apolipoprotein E (ApoE) can affect the composition of the gut microbiota and is closely related to the CNS. However, the mechanism by which ApoE affects cognitive dysfunction through the gut microbiota–brain axis has thus far not been investigated. In this study, we used wild-type mice and ApoE knockout (ApoE–/–) mice to replicate the aging model and examined the effects of ApoE deletion on cognitive function, hippocampal ultrastructure, synaptophysin (SYP) and postsynaptic density 95 (PSD-95) in aging mice. We also explored whether ApoE deletion affects the gut microbiota and the metabolite profile of the hippocampus in aging mice and finally examined the effect of ApoE deletion on lipids and oxidative stress in aging mice. The results showed that the deletion of ApoE aggravated cognitive dysfunction, hippocampal synaptic ultrastructural damage and dysregulation of SYP and PSD-95 expression in aging mice. Furthermore, ApoE deletion reduced gut microbial makeup in aging mice. Further studies showed that ApoE deletion altered the hippocampal metabolic profile and aggravated dyslipidemia and oxidative stress in aging mice. In brief, our findings suggest that loss of ApoE alters the composition of the gut microbiota, which in turn may affect cognitive function in aging mice through the gut microbiota–brain axis.

Abstract As the COVID-19 pandemic continues to affect the international community, very little is known about its impact on the health and day-to-day activities of people with Parkinson’s disease (PwPD). To better understand the emotional and behavioral consequences of the public health policies implemented to mitigate the spread of SARS-CoV-2 in PwPD, and to explore the factors contributing to accessing alternative health care mechanisms, such as telehealth, we administered an anonymous knowledge, attitude, and practice survey to PwPD and care partners, via the mailing lists of the Parkinson’s Foundation and Columbia University Parkinson’s Disease Center of Excellence with an average response rate of 19.3%. Sufficient information was provided by 1,342 PwPD to be included in the final analysis. Approximately half of respondents reported a negative change in PD symptoms, with 45–66% reporting mood disturbances. Telehealth use increased from 9.7% prior to the pandemic to 63.5% during the pandemic. Higher income and higher education were associated with telehealth use. Services were more often used for doctor’s appointment than physical, occupational, speech, or mental health therapies. Almost half (46%) of PwPD preferred to continue using telehealth always or sometimes after the coronavirus outbreak had ended. Having received support/instruction for telehealth and having a care partner, friend, or family member to help them with the telehealth visit increased the likelihood of continuous use of telehealth after the pandemic ended. Taken together, PD symptoms and management practices were markedly affected by COVID-19. Given the observed demographic limitations of telehealth, expanding its implementation to include additional physical, occupational, psychological, and speech therapies, increasing support for telehealth, as well as reaching underserved (low income) populations is urgently required.

Background: Recent evidence shows that inducing ferroptosis may improve efficacy of tumor therapy. However, ferroptosis-related genes have been little studied in patients with breast cancer especially in the neoadjuvant setting. ACSL4 and GPX4 have been well established as the positive and negative regulator of ferroptosis, respectively. This study aimed to explore the predictive value of ACSL4 and GPX4 for patients with breast cancer administered neoadjuvant chemotherapy. Methods: This study included patients treated with paclitaxel-cisplatin-based neoadjuvant chemotherapy. Immunohistochemistry staining of ACSL4 and GPX4 was carried out on the core needle biopsy specimens. Logistic regression was performed to explore the predictive biomarkers of pathological complete response (pCR). Survival analyses were examined by log-rank test and Cox proportional hazard regression. Findings: A total of 199 patients were included for the analyses. Both ACSL4 expression and ACSL4/GPX4 combination status could serve as independent predictive factors for pCR. The interaction for pCR was observed between ACSL4 and clinical tumor stage. Besides, ACSL4 expression, GPX4 expression, and their combination status were independent prognostic factors for disease-free survival. Analyses of the Kaplan-Meier Plotter database suggested that higher ACSL4 expression is related to better overall survival, and higher GPX4 expression is related to better distant metastasis-free survival. Pathway analyses revealed that ACSL4 and GPX4 might function in crucial pathways including apoptosis, autophagy, cell adhesion, lipid metabolism, etc. Interpretation: This study revealed the critical value of ACSL4 and GPX4 serving as novel predictive and prognostic biomarkers for patients with breast cancer receiving neoadjuvant chemotherapy. It might be a novel strategy to induce ferroptosis to promote chemosensitivity. Future studies are required to elucidate the potential mechanisms. Funding: This work was supported by Shanghai Natural Science Foundation [grant number 19ZR1431100], Clinical Research Plan of Shanghai Hospital Development Center [grant numbers SHDC2020CR3003A, 16CR3065B, and 12016231], Shanghai “Rising Stars of Medical Talent” Youth Development Program for Youth Medical Talents - Specialist Program [grant number 2018-15], Shanghai “Rising Stars of Medical Talent” Youth Development Program for Outstanding Youth Medical Talents [grant number 2018-16], Shanghai Collaborative Innovation Center for Translational Medicine [grant number TM201908], Multidisciplinary Cross Research Foundation of Shanghai Jiao Tong University [grant numbers YG2017QN49, ZH2018QNA42, and YG2019QNA28], Nurturing Fund of Renji Hospital [grant numbers PYMDT-002, PY2018-IIC-01, PY2018-III-15, and PYIII20-09], Science and Technology Commission of Shanghai Municipality [grant numbers 20DZ2201600 and 15JC1402700], and Shanghai Municipal Key Clinical Specialty.

Background: Homologous recombination deficiency is associated with platinum-based chemosensitivity, whereas few studies reported the predictive value of family history of cancer for breast cancer in the neoadjuvant setting. This study aimed to construct a novel family history scoring system and to explore its association with clinical outcomes for patients with breast cancer receiving neoadjuvant platinum-based chemotherapy. Methods: This study included 262 patients with locally advanced breast cancer enrolled in the SHPD001 and SHPD002 trials from October 2013 to June 2018. The Neo-Family History Score (NeoFHS) was calculated according to cancer type, age at diagnosis, kinship, and number of affected relatives. Findings: Clinical tumor stage (p=0·048), estrogen receptor status (p=0·001), progesterone receptor status (p=0·036), human epidermal growth factor receptor 2 status (p=0·013), and molecular subtype (p=0·016) were significantly related to NeoFHS. NeoFHS could serve as an independent predictive factor of pathological complete response (pCR) (OR=2·262, 95% CI 1·159-4·414, p=0·017) and an independent prognostic factor of relapse-free survival (adjusted HR=0·305, 95% CI 0·102-0·910, p=0·033). Alopecia (p=0·001), nausea (p=0·001), peripheral neuropathy (p=0·018), diarrhea (p=0·026), constipation (p=0·037) of any grade and leukopenia of grade 3 or greater (p=0·005) were more common in patients with higher NeoFHS. Interpretation: NeoFHS is a practical and effective biomarker for predicting not only pCR and survival outcomes but also chemotherapy-induced adverse events for neoadjuvant platinum-based chemotherapy in breast cancer. It may help screen candidate responders and guide safety managements. Funding: Shanghai Natural Science Foundation [grant number 19ZR1431100], Clinical Research Plan of Shanghai Hospital Development Center [grant numbers SHDC2020CR3003A, 16CR3065B, and 12016231], Shanghai “Rising Stars of Medical Talent” Youth Development Program for Youth Medical Talents - Specialist Program [grant number 2018-15], Shanghai “Rising Stars of Medical Talent” Youth Development Program for Outstanding Youth Medical Talents [grant number 2018-16], Shanghai Collaborative Innovation Center for Translational Medicine [grant number TM201908], Multidisciplinary Cross Research Foundation of Shanghai Jiao Tong University [grant numbers YG2017QN49, ZH2018QNA42, and YG2019QNA28], Nurturing Fund of Renji Hospital [grant numbers PYMDT-002, PY2018-IIC-01, PY2018-III-15, and PYIII20-09], Science and Technology Commission of Shanghai Municipality [grant numbers 20DZ2201600 and 15JC1402700], and Shanghai Municipal Key Clinical Specialty.

ObjectiveLinc00665 is a novel long non-coding RNA that can promote the progression of breast cancer, but its value in predicting the efficacy of neoadjuvant chemotherapy (NAC) for breast cancer has not been reported. We aim to analyze the correlation between Linc00665 expression and pathological complete response (pCR) in breast cancer patients.Materials and MethodsThe present study examined the predictive role of Linc00665 expression in pCR after NAC using both univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curve and area under curve (AUC) were utilized to evaluate the performance of Linc00665 in predicting pCR. The Kyoto Encyclopedia of Gene and Genome (KEGG) analysis and Gene Set Enrichment Analysis (GSEA) were also conducted to determine the biological processes where Linc00665 may participate in.ResultsThe present study study totally enrolled 102 breast cancer patients. The univariate analysis showed that Linc00665 level, human epidermal growth factor receptor 2 (HER2) status and hormone receptor (HR) status were correlated with pCR. The multivariate analysis showed that Linc00665 expression was an independent predictor of pCR (OR = 0.351, 95% CI: 0.125–0.936, P = 0.040), especially in patients with HR-positive/HER2-negative subtype (OR = 0.272, 95% CI: 0.104–0.664, P = 0.005). The KEGG analysis indicated that Linc00665 may be involved in drug metabolism. The GSEA analysis revealed that Linc00665 is correlated to DNA damage repair.ConclusionLinc00665 may be a potential novel predictive biomarker for breast cancer in NAC, especially for HR-positive/HER2-negative patients.

Background: EPIC1 is an oncogenic long non-coding ribonucleic acid (RNA) that promotes cell growth and cell-cycle progression and inhibits apoptosis in several cancer cell lines. However, clinical studies on EPIC1 in breast cancer, specifically in the neoadjuvant setting, are relatively few. Methods: Patients treated with weekly paclitaxel–cisplatin-based neoadjuvant chemotherapy after core-needle biopsy were included in the study. Real-time quantitative polymerase chain reaction assays were performed to detect EPIC1 expression. Results: Among all patients included in this study ( n = 111), higher EPIC1 expression was associated with estrogen receptor negativity, human epidermal growth factor receptor 2 positivity, higher Ki67 index, and higher histologic grade. Multivariate analysis suggested that EPIC1 expression was an independent predictive factor for pathological complete response, with a significant interaction between EPIC1 expression and age. The Kaplan–Meier Plotter dataset suggested that the EPIC1 high-expression group showed a worse 10-year distant metastasis-free survival and post-progression survival when compared with the EPIC1 low-expression group. The Cancer Genome Atlas dataset suggested that the overall survival in the EPIC1 high-expression group was inferior to that in the EPIC1 low-expression group, specifically in hormone receptor (HorR)-positive patients and patients aged

Introduction: The Montreal Cognitive Assessment (MoCA), an instrument widely used for cognitive screening in Parkinson's disease (PD), is validated in Hebrew and English. However, it remains unknown whether the scores are comparable. Methods: The MoCA was analyzed in 483 Ashkenazi Jewish PD patients in Tel-Aviv and New York who had MoCA ≥21. Each section of the MoCA was compared between English and Hebrew. Linear regression models were used to test the association between MoCA performance and language. Results: Total MoCA scores were lower in Hebrew than in English (25.4 versus 26.1; P = 0.007), even after adjustment for age, sex, PD duration, genotype, levodopa equivalent dose, the Unified Parkinson's Disease Rating Scale (UPDRS-III), and Geriatric Depression Scale score in a linear model (P

Different from the group formation approaches led by teachers, learners' generative learning objectives and the independent choice of collaborative partners are important in the Internet learning environment. This study takes the cMOOC (connectivist massive open online course) 5.0 "Internet + education: dialogue between theory and practice" as a case course. Data on learners' interactive behaviours, generative texts, and personal attributes were collected through the course platform and questionnaires. Social network analysis and natural language processing were adopted to build a variety of collaborator relationship networks, and the quadratic assignment procedure was used to reveal the impact of the social, topic and attribute relationships of learners before collaboration on the collaborative relationship. The results show that individuals with close social relations, similar topics, similar age and learning experiences before collaboration are more likely to establish collaborative relationships; among them, close social relations and close ages are the key driving factors affecting the choice of partners. In addition, topic similarity can further promote the establishment of collaborative relationships among individuals with close social relations. The findings will help community-based courses optimise partner recommendation strategies and promote collaborative problem-solving and collective knowledge creation.

A new mode of knowledge production, known as the 'organic growth pattern', has emerged within the online learning environment. It exhibits several unique features, such as iterative growth, fuelled by collective intelligence, fuzzy complexity, etc. It is more valuable and adaptable to support knowledge innovation within rapidly changing fields. To reveal its new evolutional production pattern and the interaction mechanism of different generative topics, We take a dual perspective of content and behaviour into consideration. A total of 1855 interactive data points were collected from a connectivist massive open online course. The study employed methods, such as latent Dirichlet allocation, content analysis and lag sequential analysis. Results showed that (1) the paths of knowledge innovation were complex and diverse. The process typically began with an ill-structured question and was driven by collective contribution and cognitive conflict. (2) Knowledge production involved interactive evolution and collaborative growth of multiple generative topics. (3) The four stages of knowledge production were cyclic, with sense-making acting as a bridge between way-finding and innovation. Several implications of the findings are recommended to enhance the quality of knowledge growth, such as designing ill-structured questions, providing discussion activities from easy to difficult, introducing relevant topics, taking advantage of various platforms and mobilizing learners' or participants' quality attention-related behaviours.

The interactive mechanism between social and concept networks is a key question in connectivist learning, which explains the impact of interaction on cognitive development and knowledge generation. The successful practice of "Internet Change Education: Dialogue between Theory and Practice", the first cMOOC in China, provides data support and research context for exploring the learning rules. This study proposed an evaluation framework of individual social network status in cMOOCs and a model for concept network characteristics analysis in cMOOCs. Analysis from 10,598 interactive data points of cMOOC1.0 using complex network analysis, topic clustering algorithm and correlation analysis found that there was a correlation between a learner's individual network status and concept network characteristics, and there are two kinds of special connectivist learners in cMOOC learning: someone with higher network status but lower knowledge output, and someone with higher knowledge output but weaker network status. Furthermore, we put forward three practical suggestions: (1) facilitators should focus on guiding learners' expression and connection to important individuals; (2) according to different correlation trends, facilitators can flexibly tailor activity design strategies, such as providing additional wayfinding support for learners with low centrality; and (3) carry out adaptive learning evaluations and design diversified certificates. [ABSTRACT FROM AUTHOR]

Learners in connectivist learning are diverse. It's necessary to make a clear understanding of learners' participation types and characteristics for optimizing the learning support service and learning evaluation in connectivist learning. This study aims to describe different types of learners in connectivist learning from two dimensions of social network and concept network characteristics. We analyzed 10598 collected data output during a 12-week cMOOC "Internet Driven Education Reform: Dialogue between Theory and Practice" in China. Using social network analysis, Latent Dirichlet Allocation, the K-means cluster analysis and lag sequential analysis to identify different participation types, we found: 1) Five types of learners in cMOOCs were obtained, namely "connected creative learners", "social learners", "reflective learners", "wandering learners", "marginal learners"; 2) The outstanding learners of connected creative learners, social learners and reflective learners, are in the minority; 3) Most learner types are relatively stable, but there is a possibility of conversion between some different participation types. Based on the above conclusions, this study puts forward some suggestions on cMOOC design. This study gives insight into the characteristics of five types of learners in cMOOC, so that future designers and facilitators can understand, design and support more effective cMOOCs for learners. [ABSTRACT FROM AUTHOR]

Abstract We compared the protective effects of inactivated SARS-CoV-2 vaccines derived from the ancestral and the currently circulating BA.5.2 strains against infection with multiple variants in Syrian golden hamsters. Vaccination with BA.5.2 effectively protected against infection with the Omicron subvariants including XBB.1, but not the Alpha or Delta variant. In contrast, hamsters vaccinated with the ancestral strain demonstrated decent neutralization activity against both the Omicron and non-Omicron variants. Our findings might instruct future design and formulation of SARS-CoV-2 vaccines.

Introduction:Riemerella anatipestifer (R. anatipestifer) is an important pathogen in waterfowl, leading to substantial economic losses. In recent years, there has been a notable escalation in the drug resistance rate of R. anatipestifer. Consequently, there is an imperative need to expedite the development of novel antibacterial medications to effectively manage the infection caused by R. anatipestifer.Methods: This study investigated the in vitro and in vivo antibacterial activities of a novel substituted benzene guanidine analog, namely, isopropoxy benzene guanidine (IBG), against R. anatipestifer by using the microdilution method, time-killing curve, and a pericarditis model. The possible mechanisms of these activities were explored.Results and Discussion: The minimal inhibitory concentration (MIC) range of IBG for R. anatipestifer was 0.5–2 μg/mL. Time-killing curves showed a concentration-dependent antibacterial effect. IBG alone or in combination with gentamicin significantly reduced the bacterial load of R. anatipestifer in the pericarditis model. Serial-passage mutagenicity assays showed a low probability for developing IBG resistance. Mechanistic studies suggested that IBG induced membrane damage by binding to phosphatidylglycerol and cardiolipin, leading to an imbalance in membrane potential and the transmembrane proton gradient, as well as the decreased of intracellular adenosine triphosphate. In summary, IBG is a potential antibacterial for controlling R. anatipestifer infections.

In recent years, research on the preservation of historical architecture has gained significant attention, where the effectiveness of semantic segmentation is particularly crucial for subsequent repair, protection, and 3D reconstruction. Given the sparse and uneven nature of large-scale historical building point cloud scenes, most semantic segmentation methods opt to sample representative subsets of points, often leading to the loss of key features and insufficient segmentation accuracy of architectural components. Moreover, the geometric feature information at the junctions of components is cluttered and dense, resulting in poor edge segmentation. Based on this, this paper proposes a unique semantic segmentation network design called MSFA-Net. To obtain multiscale features and suppress irrelevant information, a double attention aggregation module is first introduced. Then, to enhance the model’s robustness and generalization capabilities, a contextual feature enhancement and edge interactive classifier module are proposed to train edge features and fuse the context data. Finally, to evaluate the performance of the proposed model, experiments were conducted on a self-curated ancient building dataset and the S3DIS dataset, achieving OA values of 95.2% and 88.7%, as well as mIoU values of 86.2% and 71.6%, respectively, further confirming the effectiveness and superiority of the proposed method.

Background and Aims: Butyric acid is an intestinal microbiota-produced short-chain fatty acid, which exerts salutary effects on alleviating nonalcoholic fatty liver disease (NAFLD). However, the underlying mechanism of butyrate on regulating hepatic lipid metabolism is largely unexplored. Methods: A mouse model of NAFLD was induced with high-fat diet feeding, and sodium butyrate (NaB) intervention was initiated at the eighth week and lasted for 8 weeks. Hepatic steatosis was evaluated and metabolic pathways concerning lipid homeostasis were analyzed. Results: Here, we report that administration of NaB by gavage once daily for 8 weeks causes an augmentation of insulin-induced gene (Insig) activity and inhibition of lipogenic gene in mice fed with high-fat diet. Mechanistically, NaB is sufficient to enhance the interaction between Insig and its upstream kinase AMP-activated protein kinase (AMPK). The stimulatory effects of NaB on Insig-1 activity are abolished in AMPKα1/α2 double knockout (AMPK−/−) mouse primary hepatocytes. Moreover, AMPK activation by NaB is mediated by LKB1, as evidenced by the observations showing NaB-mediated induction of phosphorylation of AMPK, and its downstream target acetyl-CoA carboxylase is diminished in LKB1–/– mouse embryonic fibroblasts. Conclusions: These studies indicate that NaB serves as a negative regulator of hepatic lipogenesis in NAFLD and that NaB attenuates hepatic steatosis and improves lipid profile and liver function largely through the activation of LKB1-AMPK-Insig signaling pathway. Therefore, NaB has therapeutic potential for treating NAFLD and related metabolic diseases.

In order to investigate the noise impacts of wind turbines with a high single-machine capacity (2MW) on the residents living around, a face-to-face questionnaire survey was conducted. The moderating factors of noise annoyance, noise exposure-response relationships as well as noise impacts on sleep and self-reported health were investigated. Results showed that noise sensitivity, attitude towards wind turbines' visual impact on the landscape, general opinion on wind turbines and noise intensity had statistically significant impacts on annoyance due to wind turbine noise. Compared with wind turbines with lower single-machine capacity in relevant studies, those with higher single-machine capacity in this study induced higher annoyance at the same Lden, which was relative to the visibility of wind turbines, background noise levels of wind farm area, etc. Noise sensitivity, noise annoyance and noise intensity, which had no significant correlation with self-reported health effects, were statistically significantly correlated with sleep disturbance on respondents. [ABSTRACT FROM AUTHOR]

Background: Parkinson's disease (PD) is a common heterogeneous neurodegenerative disorder in elder population. Parkinson's disease dementia (PDD) is one of the most common non-motor manifestations in PD patients. No comprehensive review has been conducted to assess risk factors for PDD. Methods: A systemic search for studies on PDD risk factors was performed. Cohort and case--control studies that clearly defined PDD and presented relevant data were included. The data were analyzed to generate a pooled effect size and 95% confidence interval (CI). Publication bias was assessed using the Egger's test and the Begg's test . Results: A systematic search was conducted and yielded 5195 articles. After screening, 25 studies were included in the current analysis. Development of PDD was positively associated with age (odds ratio [OR] 1.07, 95% CI 1.03-1.13), male (OR 1.33, 95% CI 1.08-1.64), higher Unified Parkinson's Disease Rating Scale (UPDRS) part III scores (relative risk [RR] 1.04, 9 % CI 1.01-1.07), hallucination (OR 2.47, 95% CI 1.36-4.47), REM sleep behavior disorder (RBD) (OR 8.38, 95% CI 3.87-18.08), smoking (ever vs. never) (RR 1.93, 95% CI 1.15-3.26) and hypertension (OR 1.57, 95% CI 1.11-2.22). An inverse association was found between education (RR 0.94, 95% CI 0.91-0.98) and PDD. Other reported factors, including age of onset, disease duration of PD, Hoehn and Yahr stage and diabetes mellitus were not significantly associated with PDD. Conclusions: Advanced age, male, higher UPDRS III scores, hallucination, RBD, smoking and hypertension increase the risk of PDD, whereas higher education is a protective factor for PDD. [ABSTRACT FROM AUTHOR]

Fatty liver disease: Bacterial metabolite protects liver by maintaining gut integrity A molecule made by beneficial microbes in the gut helps protect against a severe form of fatty liver disease by preventing bacterial toxins from leaking out of the intestines into the bloodstream. A research team in China led by Yu Li from the Shanghai Institute of Nutrition and Health (CAS) and Jian-Gao Fan from Xinhua Hospital (SJTU) showed in a rat model of non-alcoholic steatohepatitis that indole-3-propionic acid (IPA), a metabolite produced by gut bacteria, helps maintain the integrity of the intestinal inner lining. The more robust intestinal barrier ensures that bacterial toxins do not enter the bloodstream and eventually reach the liver, where they can trigger injury-inducing inflammation. The findings reveal an interaction between the gut microbiome and the liver, and suggest a role for IPA in the treatment of fatty liver disease.

Background: Nonalcoholic fatty liver disease (NAFLD) is associated with altered production of secreted proteins. Increased understanding of secreted proteins could lead to improved prediction and treatment of NAFLD. Here, we aimed to discover novel secreted proteins in humans that are associated with hepatic fat content using unbiased proteomic profiling strategy, and how the identified Thbs1 modulates lipid metabolism and hepatic steatosis. Method: NAFLD patients were enrolled and treated with lifestyle intervention. Patients who underwent liver biopsy were enrolled for analyzing the correlation between circulating Thbs1 and liver steatosis. Mice were fed on high-fat, high-sucrose diet and treated with recombinant Thbs1. Primary hepatocytes isolated from CD36 knockout (CD36-/-) mice and their wild-type littermates (controls) were treated with glucose plus insulin for 24 h together with or without recombinant Thbs1. Finding: Serum Thbs1 levels are increased in participants with NAFLD and positively associated with liver steatosis grades. Improvement of liver steatosis after lifestyle intervention was accompanied with significant reduction of serum Thbs1 levels. Pharmacological administration of recombinant human Thbs1 attenuates hepatic steatosis in diet-induced obese mice. Treatment with Thbs1 protein or stably overexpression of Thbs1 causes a significant reduction of lipid accumulation in primary hepatocytes or HepG2 cells exposed to high glucose plus insulin, suggesting that Thbs1 regulates lipid metabolism in a hepatocyte-autonomous manner. Mechanistically, Thbs1 inhibits cleavage and processing of SREBP-1, leading to a reduction of target lipogenic gene expression and hepatic steatosis. Inhibitory effects of Thbs1 on lipogenesis and triglyceride accumulation are abrogated in CD36 deficient primary hepatocytes exposed to high glucose plus insulin. Interestingly, beneficial effects of Thbs1 on lipid accumulation are observed in primary hepatocytes treated with a Thbs1 nonapeptide mimetic ABT-526. Interpretation: Thbs1 is a biomarker for NAFLD in humans, and pharmacological and genetic approaches for the modulation of Thbs1 activity may have the therapeutic potential for treating hepatic steatosis. Fund: A full list of funding bodies that contributed to this study can be found in the Funding Sources section.

Insulin-related gene (Insig) negatively regulates hepatic fatty acid synthesis, a process involved in development of non-alcoholic fatty liver disease (NAFLD). Here, the authors show that AMPK activation by metformin promotes Insig phosphorylation, stabilizing it and inhibiting lipogenic gene expression. This is protective against steatosis in diabetic mice.

With the development of information technology, network security has increasingly become a focal point for users and organizations, and encrypted data transmission has gradually become mainstream. This trend has driven the proportion of encrypted traffic on the Internet to rise continuously. However, data encryption, while ensuring privacy and security, has also become a means for illegal content to evade network supervision. To achieve the detection and analysis of encrypted traffic, it has become necessary to efficiently identify encrypted traffic. However, the presence of compressed traffic has significantly interfered with the identification of encrypted traffic. To address this issue, an encrypted traffic identification scheme based on sliding windows and randomness features was designed to efficiently and accurately identify encrypted traffic. Specifically, the scheme involved sampling the payloads of data packets in sessions using a sliding window mechanism to obtain data block sequences that reflect the information patterns of the original traffic. For each data block, randomness measurement algorithms were utilized to extract sample features and construct randomness features for the original payload. Additionally, a decision tree model based on the CART algorithm was designed, which significantly improved the accuracy of identifying encrypted and compressed traffic and greatly reduced the false negative rate for encrypted traffic identification. A balanced dataset was constructed by randomly sampling data from several authoritative websites, and experiments demonstrated the feasibility and efficiency of the proposed scheme.

Extreme stimuli are often more salient in perception and memory than moderate stimuli. In risky choice, when people learn the odds and outcomes from experience, the extreme outcomes (best and worst) also stand out. This additional salience leads to more risk-seeking for relative gains than for relative losses--the opposite of what people do when queried in terms of explicit probabilities. Previous research has suggested that this pattern arises because the most extreme experienced outcomes are more prominent in memory. An important open question, however, is what makes these extreme outcomes more prominent? Here we assess whether extreme outcomes stand out because they fall at the edges of the experienced outcome distributions or because they are distinct from other outcomes. Across four experiments, proximity to the edge determined what was treated as extreme: Outcomes at or near the edge of the outcome distribution were both better remembered and more heavily weighted in choice. This prominence did not depend on two metrics of distinctiveness: lower frequency or distance from other outcomes. This finding adds to evidence from other domains that the values at the edges of a distribution have a special role. [ABSTRACT FROM AUTHOR]