The overview of the BioRED (Biomedical Relation Extraction Dataset) track at BioCreative VIII.

The BioRED track at BioCreative VIII calls for a community effort to identify, semantically categorize, and highlight the novelty factor of the relationships between biomedical entities in unstructured text. Relation extraction is crucial for many biomedical natural language processing (NLP) applications, from drug discovery to custom medical solutions. The BioRED track simulates a real-world application of biomedical relationship extraction, and as such, considers multiple biomedical entity types, normalized to their specific corresponding database identifiers, as well as defines relationships between them in the documents. The challenge consisted of two subtasks: (i) in Subtask 1, participants were given the article text and human expert annotated entities, and were asked to extract the relation pairs, identify their semantic type and the novelty factor, and (ii) in Subtask 2, participants were given only the article text, and were asked to build an end-to-end system that could identify and categorize the relationships and their novelty. We received a total of 94 submissions from 14 teams worldwide. The highest F-score performances achieved for the Subtask 1 were: 77.17% for relation pair identification, 58.95% for relation type identification, 59.22% for novelty identification, and 44.55% when evaluating all of the above aspects of the comprehensive relation extraction. The highest F-score performances achieved for the Subtask 2 were: 55.84% for relation pair, 43.03% for relation type, 42.74% for novelty, and 32.75% for comprehensive relation extraction. The entire BioRED track dataset and other challenge materials are available at https://ftp.ncbi.nlm.nih.gov/pub/lu/BC8-BioRED-track/ and https://codalab.lisn.upsaclay.fr/competitions/13377 and https://codalab.lisn.upsaclay.fr/competitions/13378. Database URL: https://ftp.ncbi.nlm.nih.gov/pub/lu/BC8-BioRED-track/https://codalab.lisn.upsaclay.fr/competitions/13377https://codalab.lisn.upsaclay.fr/competitions/13378.

Ultrasound evaluation of cardiac and diaphragmatic function at different positions during a spontaneous breathing trial predicting extubation outcomes: a retrospective cohort study.

BACKGROUND: The ratio (E/Ea) of mitral Doppler inflow velocity to annular tissue Doppler wave velocity by transthoracic echocardiography and diaphragmatic excursion (DE) by diaphragm ultrasound have been confirmed to predict extubation outcomes. However, few studies focused on the predicting value of E/Ea and DE at different positions during a spontaneous breathing trial (SBT), as well as the effects of △E/Ea and △DE (changes in E/Ea and DE during a SBT). METHODS: This study was a reanalysis of the data of 60 difficult-to-wean patients in a previous study published in 2017. All eligible participants were organized into respiratory failure (RF) group and extubation success (ES) group within 48 h after extubation, or re-intubation (RI) group and non-intubation (NI) group within 1 week after extubation. The risk factors for respiratory failure and re-intubation including E/Ea and △E/Ea, DE and △DE at different positions were analyzed by multivariate logistic regression, respectively. The receiver operating characteristic (ROC) curves of E/Ea (septal, lateral, average) and DE (right, left, average) were compared with each other, respectively. RESULTS: Of the 60 patients, 29 cases developed respiratory failure within 48 h, and 14 of those cases required re-intubation within 1 week. Multivariate logistic regression showed that E/Ea were all associated with respiratory failure, while only DE (right) and DE (average) after SBT were related to re-intubation. There were no statistic differences among the ROC curves of E/Ea at different positions, nor between the ROC curves of DE. No statistical differences were shown in △E/Ea between RF and ES groups, while △DE (average) was remarkably higher in NI group than that in RI group. However, multivariate logistic regression analysis showed that △DE (average) was not associated with re-intubation. CONCLUSIONS: E/Ea at different positions during a SBT could predict postextubation respiratory failure with no statistical differences among them. Likewise, only DE (right) and DE (average) after SBT might predict re-intubation with no statistical differences between each other.

The biomedical relationship corpus of the BioRED track at the BioCreative VIII challenge and workshop.

The automatic recognition of biomedical relationships is an important step in the semantic understanding of the information contained in the unstructured text of the published literature. The BioRED track at BioCreative VIII aimed to foster the development of such methods by providing the participants the BioRED-BC8 corpus, a collection of 1000 PubMed documents manually curated for diseases, gene/proteins, chemicals, cell lines, gene variants, and species, as well as pairwise relationships between them which are disease-gene, chemical-gene, disease-variant, gene-gene, chemical-disease, chemical-chemical, chemical-variant, and variant-variant. Furthermore, relationships are categorized into the following semantic categories: positive correlation, negative correlation, binding, conversion, drug interaction, comparison, cotreatment, and association. Unlike most of the previous publicly available corpora, all relationships are expressed at the document level as opposed to the sentence level, and as such, the entities are normalized to the corresponding concept identifiers of the standardized vocabularies, namely, diseases and chemicals are normalized to MeSH, genes (and proteins) to National Center for Biotechnology Information (NCBI) Gene, species to NCBI Taxonomy, cell lines to Cellosaurus, and gene/protein variants to Single Nucleotide Polymorphism Database. Finally, each annotated relationship is categorized as 'novel' depending on whether it is a novel finding or experimental verification in the publication it is expressed in. This distinction helps differentiate novel findings from other relationships in the same text that provides known facts and/or background knowledge. The BioRED-BC8 corpus uses the previous BioRED corpus of 600 PubMed articles as the training dataset and includes a set of newly published 400 articles to serve as the test data for the challenge. All test articles were manually annotated for the BioCreative VIII challenge by expert biocurators at the National Library of Medicine, using the original annotation guidelines, where each article is doubly annotated in a three-round annotation process until full agreement is reached between all curators. This manuscript details the characteristics of the BioRED-BC8 corpus as a critical resource for biomedical named entity recognition and relation extraction. Using this new resource, we have demonstrated advancements in biomedical text-mining algorithm development. Database URL: https://codalab.lisn.upsaclay.fr/competitions/16381.

C-reactive protein-albumin-lymphocyte index as a feasible nutrition-immunity-inflammation marker of the outcome of all-cause and cardiovascular mortality in elderly.

BACKGROUND & AIMS: The imbalance of nutrition-immunity-inflammation status might be associated with the mortality risk in the elderly. This study aimed to assess the relationship between the C-reactive protein (CRP)-albumin-lymphocyte (CALLY) index and all-cause and cardiovascular disease (CVD) mortality in the elderly. METHODS: The data from records of older adults (≥ 60 years) were derived from 1999 to 2010 and 2015-2018 National Health and Nutrition Examination Survey. Weighted Cox proportional hazard regression was used to analyze the relationship between CALLY and all-cause mortality and CVD mortality in three different models, and the linear trend was analyzed. A restricted cubic spline model was used to evaluate the nonlinear dose-response relationship and determine the critical threshold of CALLY to divide the population into two groups. Kaplan-Meier analysis and log-rank test were used to evaluate the cumulative survival rates of different groups. Subgroup analyses and sensitivity analyses were performed to ensure robustness. RESULTS: Compared to the first quartile of natural log-transformation (ln) CALLY, the highest quartile of ln CALLY was negatively correlated with the risk of all-cause mortality (HR = 0.67, 95% CI: 0.56-0.79. P < 0.05) and CVD mortality (HR = 0.65, 95% CI: 0.47-0.89. P < 0.05) in model 3. Ln CALLY was linear dose-response correlated with mortality. We determined that the critical threshold for ln CALLY in elderly was 1.00. Elderly with higher ln CALLY (≥ 1.00) had significantly increased survival rates (P < 0.05). CONCLUSION: CALLY showed a significant negative linear association with the risk of all-cause mortality and CVD mortality, and higher CALLY was beneficial to the survival outcomes of the elderly.

Association between standing height and physical disability among U.S. adults aged 60 years and older: findings from NHANES 2015-2018.

BACKGROUND: Physical disability is an important cause of affecting the quality of life in the elderly. The association between standing height and physical disability is less studied. PURPOSE: The purpose of this study is to investigate the possible link between standing height and physical disability among U.S. adults aged 60 years and older. METHODS: The cross-sectional data were obtained from the US National Health and Nutrition Examination Survey (NHANES) 2015-2018. Physical disability was assessed by six questions: "Have serious difficulty hearing (SDH)?", "Have serious difficulty seeing (SDS)?", "Have serious difficulty concentrating (SDC)?", "Have serious difficulty walking (SDW)?", "Have difficulty dressing or bathing (DDB)?" and "Have difficulty doing errands alone (DDEA)?". Responses to these questions were "yes" or "no". Answer yes to one of the above six questions was identified as physical disability. Standing height (cm) was measured with an altimeter. Multivariate logistic regression was performed to examine the possible link between standing height and physical disability after adjustment for all covariates. RESULTS: A total of 2624 participants aged ≥ 60 years were included in our study, including 1279 (48.7%) females and 1345 (51.3%) males. The mean age of participants was 69.41 ± 6.82 years. After adjusting for all potential confounders, the inverse relationship between standing height and all physical disability (APD) was statistically significant (OR = 0.976, 95%CI:0.957-0.995). In addition, among six types of physical disability (SDH, SDS, SDC, SDW, DDB, DDEA), standing height was also a protective factor for SDW (OR = 0.961, 95%CI:0.939-0.983) and DDEA (OR = 0.944, 95%CI:0.915-0.975) in the full-adjusted model. CONCLUSION: The cross-sectional population based study demonstrates that standing height is a protective factor for physical disability among U.S. adults aged 60 years and older.

Structural variant landscapes reveal convergent signatures of evolution in sheep and goats.

BACKGROUND: Sheep and goats have undergone domestication and improvement to produce similar phenotypes, which have been greatly impacted by structural variants (SVs). Here, we report a high-quality chromosome-level reference genome of Asiatic mouflon, and implement a comprehensive analysis of SVs in 897 genomes of worldwide wild and domestic populations of sheep and goats to reveal genetic signatures underlying convergent evolution. RESULTS: We characterize the SV landscapes in terms of genetic diversity, chromosomal distribution and their links with genes, QTLs and transposable elements, and examine their impacts on regulatory elements. We identify several novel SVs and annotate corresponding genes (e.g., BMPR1B, BMPR2, RALYL, COL21A1, and LRP1B) associated with important production traits such as fertility, meat and milk production, and wool/hair fineness. We detect signatures of selection involving the parallel evolution of orthologous SV-associated genes during domestication, local environmental adaptation, and improvement. In particular, we find that fecundity traits experienced convergent selection targeting the gene BMPR1B, with the DEL00067921 deletion explaining ~10.4% of the phenotypic variation observed in goats. CONCLUSIONS: Our results provide new insights into the convergent evolution of SVs and serve as a rich resource for the future improvement of sheep, goats, and related livestock.

Recombination of Porcine Reproductive and Respiratory Syndrome Virus: Features, Possible Mechanisms, and Future Directions.

Recombination is a pervasive phenomenon in RNA viruses and an important strategy for accelerating the evolution of RNA virus populations. Recombination in the porcine reproductive and respiratory syndrome virus (PRRSV) was first reported in 1999, and many case reports have been published in recent years. In this review, all the existing reports on PRRSV recombination events were collected, and the genotypes, parental strains, and locations of the recombination breakpoints have been summarized and analyzed. The results showed that the recombination pattern constantly changes; whether inter- or intra-lineage recombination, the recombination hotspots vary in different recombination patterns. The virulence of recombinant PRRSVs was higher than that of the parental strains, and the emergence of virulence reversion was caused by recombination after using MLV vaccines. This could be attributed to the enhanced adaptability of recombinant PRRSV for entry and replication, facilitating their rapid propagation. The aim of this paper was to identify common features of recombinant PRRSV strains, reduce the recombination risk, and provide a foundation for future research into the mechanism of PRRSV recombination.

EnzChemRED, a rich enzyme chemistry relation extraction dataset.

Expert curation is essential to capture knowledge of enzyme functions from the scientific literature in FAIR open knowledgebases but cannot keep pace with the rate of new discoveries and new publications. In this work we present EnzChemRED, for Enzyme Chemistry Relation Extraction Dataset, a new training and benchmarking dataset to support the development of Natural Language Processing (NLP) methods such as (large) language models that can assist enzyme curation. EnzChemRED consists of 1,210 expert curated PubMed abstracts in which enzymes and the chemical reactions they catalyze are annotated using identifiers from the UniProt Knowledgebase (UniProtKB) and the ontology of Chemical Entities of Biological Interest (ChEBI). We show that fine-tuning pre-trained language models with EnzChemRED can significantly boost their ability to identify mentions of proteins and chemicals in text (Named Entity Recognition, or NER) and to extract the chemical conversions in which they participate (Relation Extraction, or RE), with average F1 score of 86.30% for NER, 86.66% for RE for chemical conversion pairs, and 83.79% for RE for chemical conversion pairs and linked enzymes. We combine the best performing methods after fine-tuning using EnzChemRED to create an end-to-end pipeline for knowledge extraction from text and apply this to abstracts at PubMed scale to create a draft map of enzyme functions in literature to guide curation efforts in UniProtKB and the reaction knowledgebase Rhea. The EnzChemRED corpus is freely available at https://ftp.expasy.org/databases/rhea/nlp/.

The impact of positive-pressure breathing apparatus on muscle fatigue of volunteer firefighter.

Muscle fatigue is one of the leading causes that contributes tremendously to injuries among volunteer firefighters in the workplace. The purpose of this study was to investigate the impact of positive-pressure breathing apparatus on muscle fatigue in the shoulder, back, and legs of volunteer firefighters. A total of 60 volunteer firefighters were recruited to perform a running task on a motorized treadmill in a controlled laboratory environment. Surface electromyography and rating of perceived exertion scores were collected from all participants every 60 seconds during the running task. Results show that the median frequency values for all measured muscle groups were significantly lower, and the rating of perceived exertion score was significantly higher after running with the positive-pressure breathing apparatus. Meanwhile, there were no significant differences in the median frequency values for the upper trapezius, erector spinae, and biceps femoris between the initial and final periods of running task without load. However, the median frequency values with load for gastrocnemius, rectus femoris, and tibialis anterior exhibited a greater downward trend compared to those without load. Additionally, using a breathing apparatus can cause asymmetric muscle fatigue in bilateral upper trapezius, erector spinae, gastrocnemius, and tibialis anterior muscles. The decreased performance due to muscle fatigue increases the risk of accidents, thereby posing a threat to the safety of volunteer firefighters. This study offers valuable insights into the effects of positive-pressure breathing apparatus on muscle fatigue among volunteer firefighters. These results may serve as a reference for developing improved fatigue management strategies and optimizing the design features of breathing apparatus.

Effect of Recycled Fine Aggregates on the Mechanical and Drying Shrinkage Properties of Alkali-Activated Recycled Concrete.

In this paper, the workability, mechanical, ion leaching, and drying shrinkage properties of alkali-activated concrete with recycled coarse and fine aggregates were studied, and the pore structure and micro-morphology of different alkali-activated recycled aggregate concretes (AARACs) were characterized by using the mercury intrusion method and scanning electron microscopy, respectively. The experimental results showed that with the increase in the replacement rate of the recycled fine aggregate (RFA), the flowability showed a decreasing trend. Adding a certain amount of RFA improves the mechanical properties of the AARAC. The compressive strength at a curing age of 28 days was 65.3 MPa with 70 wt% RFA replacement. When the replacement rate of the RFA was 100 wt%, the maximum splitting tensile strength (4.5 MPa) was obtained at a curing age of 7 days. However, the addition of the RFA had little effect on the flexural strength of the AARAC. As an extension of the curing age, the splitting tensile strength, flexural strength, tension-to-compression ratio, and flexure-to-compression ratio all showed an increasing trend at first and then a decreasing trend. At a curing age of 7 days, the tension-to-compression ratio and flexure-to-compression ratio were both high (except for those of R100), indicating that the ductility and toughness of the specimen were improved. The addition of the RFA increased the drying shrinkage of the AARAC. At a curing age of 120 days, compared to the specimen without the RFA, the drying shrinkage rate of the specimen with the addition of 70 wt% RFA increased by 34.15%. As the curing age increased, the microstructure of the reaction products became denser, but the proportion of large-diameter pores increased. This study evaluated the application of RFA in AARAC. The experimental results showed that the RFA-based AARAC had acceptable mechanical and durability properties.

Bayesian network analysis of factors influencing type 2 diabetes, coronary heart disease, and their comorbidities.

OBJECTIVE: Bayesian network (BN) models were developed to explore the specific relationships between influencing factors and type 2 diabetes mellitus (T2DM), coronary heart disease (CAD), and their comorbidities. The aim was to predict disease occurrence and diagnose etiology using these models, thereby informing the development of effective prevention and control strategies for T2DM, CAD, and their comorbidities. METHOD: Employing a case-control design, the study compared individuals with T2DM, CAD, and their comorbidities (case group) with healthy counterparts (control group). Univariate and multivariate Logistic regression analyses were conducted to identify disease-influencing factors. The BN structure was learned using the Tabu search algorithm, with parameter estimation achieved through maximum likelihood estimation. The predictive performance of the BN model was assessed using the confusion matrix, and Netica software was utilized for visual prediction and diagnosis. RESULT: The study involved 3,824 participants, including 1,175 controls, 1,163 T2DM cases, 982 CAD cases, and 504 comorbidity cases. The BN model unveiled factors directly and indirectly impacting T2DM, such as age, region, education level, and family history (FH). Variables like exercise, LDL-C, TC, fruit, and sweet food intake exhibited direct effects, while smoking, alcohol consumption, occupation, heart rate, HDL-C, meat, and staple food intake had indirect effects. Similarly, for CAD, factors with direct and indirect effects included age, smoking, SBP, exercise, meat, and fruit intake, while sleeping time and heart rate showed direct effects. Regarding T2DM and CAD comorbidities, age, FBG, SBP, fruit, and sweet intake demonstrated both direct and indirect effects, whereas exercise and HDL-C exhibited direct effects, and region, education level, DBP, and TC showed indirect effects. CONCLUSION: The BN model constructed using the Tabu search algorithm showcased robust predictive performance, reliability, and applicability in forecasting disease probabilities for T2DM, CAD, and their comorbidities. These findings offer valuable insights for enhancing prevention and control strategies and exploring the application of BN in predicting and diagnosing chronic diseases.

PubTator 3.0: an AI-powered literature resource for unlocking biomedical knowledge.

PubTator 3.0 (https://www.ncbi.nlm.nih.gov/research/pubtator3/) is a biomedical literature resource using state-of-the-art AI techniques to offer semantic and relation searches for key concepts like proteins, genetic variants, diseases and chemicals. It currently provides over one billion entity and relation annotations across approximately 36 million PubMed abstracts and 6 million full-text articles from the PMC open access subset, updated weekly. PubTator 3.0's online interface and API utilize these precomputed entity relations and synonyms to provide advanced search capabilities and enable large-scale analyses, streamlining many complex information needs. We showcase the retrieval quality of PubTator 3.0 using a series of entity pair queries, demonstrating that PubTator 3.0 retrieves a greater number of articles than either PubMed or Google Scholar, with higher precision in the top 20 results. We further show that integrating ChatGPT (GPT-4) with PubTator APIs dramatically improves the factuality and verifiability of its responses. In summary, PubTator 3.0 offers a comprehensive set of features and tools that allow researchers to navigate the ever-expanding wealth of biomedical literature, expediting research and unlocking valuable insights for scientific discovery.

Bayesian network-based survival prediction model for patients having undergone post-transjugular intrahepatic portosystemic shunt for portal hypertension.

BACKGROUND: Portal hypertension (PHT), primarily induced by cirrhosis, manifests severe symptoms impacting patient survival. Although transjugular intrahepatic portosystemic shunt (TIPS) is a critical intervention for managing PHT, it carries risks like hepatic encephalopathy, thus affecting patient survival prognosis. To our knowledge, existing prognostic models for post-TIPS survival in patients with PHT fail to account for the interplay among and collective impact of various prognostic factors on outcomes. Consequently, the development of an innovative modeling approach is essential to address this limitation. AIM: To develop and validate a Bayesian network (BN)-based survival prediction model for patients with cirrhosis-induced PHT having undergone TIPS. METHODS: The clinical data of 393 patients with cirrhosis-induced PHT who underwent TIPS surgery at the Second Affiliated Hospital of Chongqing Medical University between January 2015 and May 2022 were retrospectively analyzed. Variables were selected using Cox and least absolute shrinkage and selection operator regression methods, and a BN-based model was established and evaluated to predict survival in patients having undergone TIPS surgery for PHT. RESULTS: Variable selection revealed the following as key factors impacting survival: age, ascites, hypertension, indications for TIPS, postoperative portal vein pressure (post-PVP), aspartate aminotransferase, alkaline phosphatase, total bilirubin, prealbumin, the Child-Pugh grade, and the model for end-stage liver disease (MELD) score. Based on the above-mentioned variables, a BN-based 2-year survival prognostic prediction model was constructed, which identified the following factors to be directly linked to the survival time: age, ascites, indications for TIPS, concurrent hypertension, post-PVP, the Child-Pugh grade, and the MELD score. The Bayesian information criterion was 3589.04, and 10-fold cross-validation indicated an average log-likelihood loss of 5.55 with a standard deviation of 0.16. The model's accuracy, precision, recall, and F1 score were 0.90, 0.92, 0.97, and 0.95 respectively, with the area under the receiver operating characteristic curve being 0.72. CONCLUSION: This study successfully developed a BN-based survival prediction model with good predictive capabilities. It offers valuable insights for treatment strategies and prognostic evaluations in patients having undergone TIPS surgery for PHT.

P2X7 receptor is essential for ST36-attenuated cardiac fibrosis upon beta-adrenergic insult.

P2X7 receptor (P2X7R) plays an important role in modulating inflammation and fibrosis, but information is limited whether Zusanli (ST36) can inhibit inflammation and fibrosis by regulating P2X7R. Isoprenaline at 5 mg/kg was subcutaneously injected to wild-type and P2X7R knockout mice for 7 days, while treatment groups received electroacupuncture (EA) stimulation at ST36 for 7 sessions. Following 7-session treatment, Masson's trichrome staining was performed to assess the fibrosis. Morphology, electrocardiogram, and echocardiography were carried out to evaluate the cardiac function and structure. Western blotting, hematoxylin and eosin staining, immunohistochemistry, and biochemical analysis of inflammatory cytokine and transmission electron microscopy were carried out to characterize the effect of ST36 on inflammation. P2X7R was overexpressed in ISO-treated mice. EA at ST36, but not at non-points, reduced ISO-induced cardiac fibrosis, increases in HW/BW, R+S wave relative to mice in ISO groups. In addition, EA at ST36 downregulated ISO-upregulated P2X7R and NLRP3 in ventricle. Moreover, EA reduced cytokines of IL-1ß, IL-6, and IL-18 in serum, and inhibited foam cell gathering, inflammatory cell infiltration, and autophagy. However, EA at ST36 failed to attenuate the cardiac fibrosis and hypertrophy in P2X7R knockout mice. In conclusion, EA at ST36 attenuated ISO-induced fibrosis possibly via P2X7R.

An Antibacterial Bionic Periosteum with Angiogenesis-Neurogenesis Coupling Effect for Bone Regeneration.

The periosteum, rich in neurovascular networks, bone progenitor cells, and stem cells, is vital for bone repair. Current artificial periosteal materials face challenges in mechanical strength, bacterial infection, and promoting osteogenic differentiation and angiogenesis. To address these issues, we adjusted the electrospinning ratio of poly-ε-caprolactone and chitosan and incorporated Zn doping whitlockite with polydopamine coating into a nanofiber membrane. After a series of characterizations, optimal results were achieved with a poly-ε-caprolactone: chitosan ratio of 8:1 and 5% nanoparticle content. In vitro cell experiments and in vivo calvarial defect models, the sustained release of Mg2+ and Ca2+ promoted vascularization and new bone formation, respectively, while the release of Zn2+ was conducive to antibacterial and cooperated with Mg2+ to promote neurovascularization. Consequently, this antibacterial bionic periosteum with an angiogenesis-neurogenesis coupling effect demonstrates a promising potential for bone repair applications.

Research on mix design and mechanical performances of MK-GGBFS based geopolymer pastes using central composite design method.

In order to alleviate environmental problems and reduce CO2 emissions, geopolymers had drew attention as a kind of alkali-activated materials. Geopolymers are easier access to raw materials, green and environment friendly than traditional cement industry. Its special reaction mechanism and gel structure show excellent characteristics such as quick hardening, high strength, acid and alkali resistance. In this paper, geopolymer pastes were made with metakaolin (MK) and ground granulated blast furnace slag (GGBFS) as precursors. The effects of liquid-solid ratio (L/S) and modulus of sodium silicate (Ms) on the performances of MK-GGBFS based geopolymer paste (MSGP) were characterized by workability, strength and microstructural tests. The regression equations were obtained by central composite design method to optimize the mix design of MSGP. The goodness of fit of all the equations were more than 98%. Based on the results of experiments, the optimum mix design was found to have L/S of 0.75 and Ms of 1.55. The workability of MSGP was significantly improved while maintaining the strength under the optimum mix design. The initial setting time of MSGP decreased by 71.8%, while both of the fluidity and 28-d compressive strength increased by 15.3%, compared with ordinary Portland cement pastes. Therefore, geopolymers are promising alternative cementitious material, which can consume a large amount of MK and GGBFS and promote green and clean production.

Optimized strategy among diet, exercise, and pharmacological interventions for nonalcoholic fatty liver disease: A network meta-analysis of randomized controlled trials.

BACKGROUND: Emerging treatment methods, including exercise, diet, and drugs, for nonalcoholic fatty liver disease have been proposed. However, the differences in their efficacy have not been determined. We aimed to compare the effects of these treatments excluding surgery via a systematic review and network meta-analysis of randomized controlled trials. DATA SOURCE: The data sources included PubMed, Embase, Web of Science and Cochrane up to February 1st, 2023. The endpoints consisted of body mass index (BMI), serum markers of metabolism and liver injury markers, liver fat content, and stiffness. RESULTS: A total of 174 studies with 10,183 patients were included in this meta-analysis. In terms of improving BMI, Pan-agonist of peroxisome proliferator-activated receptors (PPAR) is the best treatment with the highest SUCRA (surface under the cumulative ranking) of 84.8% (mean = -3.40, 95% CI -5.55, -1.24) by the comparative effectiveness ranking. GLP-1 (glucagon-like peptide-1) has the best effect in improving the liver fat content based on the MRI-PDFF, steatosis score (SUCRA 99.7%, mean = -2.19, 95% CI -2.90, -1.48) and ballooning score (SUCRA 61.2%, mean = -0.82, 95% CI -4.46, 2.83). CONCLUSIONS: Pan-agonist of PPAR was the most efficacious regimen in lowering BMIs, whereas GLP-1R agonists achieved the highest efficacy of steatosis improvement in this network meta-analysis.

Role of remnant cholesterol in the relationship between physical activity and diabetes mellitus: an intermediary analysis.

Objective: The purpose of this investigation was to evaluate the potential link between physical activity (PA) and the heightened susceptibility to diabetes mellitus (DM), by examining whether remnant cholesterol (RC) might act as a mediator in this correlation. Methods: The research utilized data from the National Health and Nutrition Examination Survey, spanning from 2005 to 2018. Various statistical analyses were conducted for continuous and categorical variables, including the t-test, ANOVA, and χ2 test. Logistic regression was employed to analyze the association between PA and DM across three distinct models. Mediation analysis was also conducted to assess the potential mediation effects of RC. Results: The study encompassed a total of 9,149 participants, and it was observed that individuals with DM exhibited lower levels of PA. Furthermore, PA levels were found to be associated with all participant characteristics except poverty income ratio, fasting blood glucose, and HOMA-IR (p < 0.05). After adjusting for covariates (Model 3), individuals with high PA levels demonstrated a decreased likelihood of developing DM compared to those in the low PA group (OR: 0.73, 95%CI: 0.54-0.99). A significant dose-response relationship was identified (p < 0.05). No interaction between PA and RC in relation to DM risk was detected, and RC was found to serve as a mediator in the connection between PA and DM. After considering covariates, the mediating effect of RC between PA and DM weakens. Discussion: Our findings suggest that higher levels of PA are linked to a reduced risk of DM in U.S. adults, with RC likely playing a mediating role.

The mediating effect of self-directed learning ability between professional identity and burnout among nursing students.

Objectives: Burnout influences students' academic performance and mental health. This study analyzed the relationship between professional identity, self-directed learning ability, and burnout, and examined the mediating effect of self-directed learning ability between professional identity and burnout among nursing students. Methods: 884 nursing students were recruited at two medical universities in China. Demographic information, Academic Burnout Scale, Professional Identity Questionnaire for Nursing Students, and Self-directed Learning Instrument were distributed to collect data. Results: Both professional identity (ß = -0.17) and self-directed learning ability (ß = -0.43) showed negative associations with students' burnout. Meanwhile, there was a partial mediating effect of self-directed learning ability between professional identity and burnout (-0.24, 95% CI = -0.30, -0.20). Conclusions: Nursing educators should emphasize on developing effective strategies to improve nursing students' professional identity and self-directed learning ability to prevent or reduce their burnout.

Bezafibrate alleviates diabetes-induced spermatogenesis dysfunction by inhibiting inflammation and oxidative stress.

The metabolic disorders caused by diabetes can lead to various complications, including male spermatogenesis dysfunction. Exploring effective therapeutics that attenuate diabetes mellitus (DM)-induced male subfertility is of great importance. Pharmaceuticals targeting PPARα activation such as bezafibrate have been regarded as an important strategy for patients with diabetes. In this study, we use streptozocin (STZ) injection to establish a type 1 DM mice model and use bezafibrate to treat DM mice and evaluate the effects of bezafibrate on the spermatogenic function of the DM male mice. Bezafibrate treatment exhibited protective effects on DM-induced spermatogenesis deficiency, as reflected by increased testis weight, improved histological morphology of testis, elevated sperm parameters, increased serum testosterone concentration as well as increased mRNA levels of steroidogenesis enzymes. Meanwhile, testicular cell apoptosis, inflammation accumulation and oxidative stress status were also shown to be alleviated by bezafibrate compared with the DM group. In vivo and in vitro studies, PPARα specific inhibitor and PPARα knockout mice were further used to investigate the role of PPARα in the protective effects of bezafibrate on DM-induced spermatogenesis dysfunction. Our results indicated that the protection of bezafibrate on DM-induced spermatogenesis deficiency was abrogated by PPARα inhibition or deletion. Our study suggested that bezafibrate administration could ameliorate DM-induced spermatogenesis dysfunction and may represent a novel practical strategy for male infertility.