Causal relationship association of cheese intake with gestational hypertension and diabetes result from a Mendelian randomization study.

BACKGROUND: The evidence from observational studies has been inconclusive on the causal relationship between cheese intake and gestational hypertension or diabetes. AIM: To determine whether cheese consumption was causally related to hypertension and diabetes during pregnancy. METHODS: This was a two-sample Mendelian randomized (MR) study. Summary-level genetic data for cheese intake was exposure and corresponding outcome data for gestational hypertension and gestational diabetes were extracted from the IEU OpenGWAS database. MR analysis was conducted using inverse variance weighting. For sensitivity analyses, MR-Egger regression, weighted median, weighted mode, and leave-one-out methods were conducted. A fixed-effect model was used to meta-analyze two sample MR estimates. The traits of gestational hypertension were pregnancy hypertension (123579 individuals) and oedema, proteinuria and hypertensive disorders in pregnancy, childbirth and the puerperium (123579 individuals), and traits of gestational diabetes were gestational diabetes (123579 individuals) and diabetes mellitus in pregnancy (116363 individuals), respectively. RESULTS: Cheese intake per standard deviation increase has causally reduced the risks of gestational hypertension [odds ratio (OR) = 0.60, 95% confidence interval (CI): 0.47-0.76, P < 0.001] and gestational diabetes (OR = 0.41, 95%CI: 0.30-0.55, P < 0.001) in inverse variance weighted analysis. Sensitivity analysis showed no heterogeneity (all P > 0.05) nor horizontal pleiotropy (all P > 0.05) in the relationship between cheese intake and gestational hypertension, but heterogeneity presented (all P < 0.05) in relation to gestational diabetes in the two-sample MR analysis. CONCLUSION: Cheese intake was inversely associated with gestational hypertension and gestational diabetes in MR analysis, suggesting that cheese consumption may be beneficial in preventing hypertension and diabetes during pregnancy.

Mesenchymal stem cell-derived extracellular vesicles protect against abdominal aortic aneurysm formation by inhibiting NET-induced ferroptosis.

Neutrophil extracellular traps (NETs) play an important role in abdominal aortic aneurysm (AAA) formation; however, the underlying molecular mechanisms remain unclear. Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) may exert therapeutic effects on AAA through their immunomodulatory and regenerative abilities. This study aimed to examine the role and mechanism of MSC-EVs in regulating the development of NET-mediated AAA. Excessive release of NETs was observed in patients with AAA, and the levels of NET components were associated with the clinical outcomes of the patients. Datasets from the Gene Expression Omnibus database were analyzed and revealed that the PI3K/AKT pathway and ferroptosis were strongly associated with NETosis during AAA formation. Further experiments verified that NETs promoted AAA formation by inducing ferroptosis in smooth muscle cells (SMCs) by inhibiting the PI3K/AKT pathway. The PI3K agonist 740 Y-P, the ferroptosis inhibitor ferrostatin-1, and Padi4 deficiency significantly prevented AAA formation. MSC-EVs attenuated AAA formation by reducing NET release in an angiotensin II-induced AAA mouse model. In vitro experiments revealed that MSC-EVs reduced the release of NETs by shifting NETosis to apoptosis. Our study indicates an important role for NET-induced SMC ferroptosis in AAA formation and provides several potential targets for AAA treatment.

Stable seasonal migration patterns in giant pandas.

A critical function of animal movement is to maximize access to essential resources in temporally fluctuating and spatially heterogeneous environments. Seasonally mediated resource fluctuations may influence animal movements, enabling them to track changing resource distributions, resulting in annual migration patterns. The conservation-dependent giant panda ( Ailuropoda melanoleuca) displays seasonal movement patterns; however, the key factor driving these seasonal migration patterns remains poorly understood. Here, we used GPS tracking collars to monitor the movements of six giant pandas over a 12-year period across different elevations, and performed statistical analysis of seasonal migration directions, routes, habitat revisitation, home range overlap, first arrival events, and stability. Our results revealed a compelling pattern of seasonal migrations that facilitated the ability of the pandas to forage at the appropriate time and place to maximize nutritional intake. Our results indicated that pandas utilize spatial memory to locate reliable food resources, as evidenced by their annual return to the same or similar winter and summer home ranges and the consistently maintained percentage of home range overlap. These novel insights into giant panda foraging and movement ecology not only enhance our understanding of its ability to adapt to nutritionally poor dietary resources but also provide important information for the development of resource utilization-based protection and management strategies.

Laplace approximation for conditional autoregressive models for spatial data of diseases.

Conditional autoregressive (CAR) distributions are used to account for spatial autocorrelation in small areal or lattice data to assess the spatial risks of diseases. The intrinsic CAR (ICAR) distribution has been primarily used as the priori distribution of spatially autocorrelated random variables in the framework of Bayesian statistics. The posterior distributions of spatial variates and unknown parameters of Bayesian ICAR models are estimated with the Markov chain Monte Carlo (MCMC) methods or integrated nested Laplace approximation (INLA), which may suffer from failures in numeric convergence. This study used the Laplace approximation, a fast computational method available in software Template Model Builder (TMB), for the maximum likelihood estimation (MLEs) of the ICAR model parameters. This study used the TMB to integrate out the latent spatial variates for the fast computations of marginal likelihood functions. This study compared the runtime and performance among the TMB, MCMC, and INLA implementations with three case studies of human diseases in the United Kingdom and the United States. The MLEs of the ICAR model with TMB were similar to those by the MCMC and INLA methods. The TMB implementation was faster than the MCMC (up to 100-200 times) and INLA (nine times) models. • This study built conditional autoregressive models in template model builder • TMB implementation was 100-200 times faster than the MCMC method • TMB implementation was also faster than Bayesian approximation with R INLA.

Seasonal climatic niche and migration movements of Double-crested Cormorants.

Avian migrants are challenged by seasonal adverse climatic conditions and energetic costs of long-distance flying. Migratory birds may track or switch seasonal climatic niche between the breeding and non-breeding grounds. Satellite tracking enables avian ecologists to investigate seasonal climatic niche and circannual movement patterns of migratory birds. The Double-crested Cormorant (Nannopterum auritum, hereafter cormorant) wintering in the Gulf of Mexico (GOM) migrates to the Northern Great Plains and Great Lakes and is of economic importance because of its impacts on aquaculture. We tested the climatic niche switching hypothesis that cormorants would switch climatic niche between summer and winter because of substantial differences in climate between the non-breeding grounds in the subtropical region and breeding grounds in the northern temperate region. The ordination analysis of climatic niche overlap indicated that cormorants had separate seasonal climatic niche consisting of seasonal mean monthly minimum and maximum temperature, seasonal mean monthly precipitation, and seasonal mean wind speed. Despite non-overlapping summer and winter climatic niches, cormorants appeared to be subjected to similar wind speed between winter and summer habitats and were consistent with similar hourly flying speed between winter and summer. Therefore, substantial differences in temperature and precipitation may lead to the climatic niche switching of fish-eating cormorants, a dietary specialist, between the breeding and non-breeding grounds.

Climate affects the outbreaks of a forest defoliator indirectly through its tree hosts.

Although spatial variation in climate can directly affect the survival and reproduction of forest insects and the tree species compositions of forests, little is known about the indirect effects of climate on outbreaks of forest insects through its effects on forest composition. In this study, we use structural equation modeling to examine the direct and indirect effects of climate, water capacity of the soil, host tree density, and non-host density on the spatial extent of Lymantria dispar outbreaks in the Eastern USA over a period of 44 years (1975-2018). Host species were subdivided into four taxonomic and ecologically distinct groups: red oaks (Lobatae), white oaks (Lepidobalanus), other preferred hosts, and intermediate (less preferred) hosts. We found that mean annual temperature had stronger effects than mean annual precipitation on the spatial extent of outbreaks, and that indirect effects of temperature (via its effects on oak density) on defoliation were stronger than direct effects. The density of non-host trees increased with increasing precipitation and, consistent with the 'associational resistance hypothesis', defoliation decreased with increasing density of non-host trees. This study offers quantitative evidence that geographic variation in climate can indirectly affect outbreaks of a forest insect through its effects on tree species composition.

Timing outweighs magnitude of rainfall in shaping population dynamics of a small mammal species in steppe grassland.

Climate change-induced shifts in species phenology differ widely across trophic levels, which may lead to consumer-resource mismatches with cascading population and ecosystem consequences. Here, we examined the effects of different rainfall patterns (i.e., timing and amount) on the phenological asynchrony of population of a generalist herbivore and their food sources in semiarid steppe grassland in Inner Mongolia. We conducted a 10-y (2010 to 2019) rainfall manipulation experiment in 12 0.48-ha field enclosures and found that moderate rainfall increases during the early rather than late growing season advanced the timing of peak reproduction and drove marked increases in population size through increasing the biomass of preferred plant species. By contrast, greatly increased rainfall produced no further increases in vole population growth due to the potential negative effect of the flooding of burrows. The increases in vole population size were more coupled with increased reproduction of overwintered voles and increased body mass of young-of-year than with better survival. Our results provide experimental evidence for the fitness consequences of phenological mismatches at the population level and highlight the importance of rainfall timing on the population dynamics of small herbivores in the steppe grassland environment.

Anti-inflammation treatment for protection of hepatocytes and amelioration of hepatic fibrosis in rats.

Chronic inflammation is considered as an important pathophysiologic mechanism of hepatic cirrhosis, which induces hepatocyte injury and activates hepatic stellate cells (HSCs), thus resulting in hepatic fibrosis. Previous studies have reported that cyclooxygenase-2 (COX-2) inhibitor can effectively treat liver fibrosis, while somatostatin (SST) analogues inhibit the activation of HSCs. The present study aimed to investigate the effects of a COX-2 inhibitor, celecoxib, combined with a SST analogue, octreotide, for protection of hepatocytes and prevention of fibrosis in a rat model of hepatic fibrosis. Therefore, a hepatic fibrosis rat model was established following peritoneal injection of thioacetamide (TAA), and the rats were then treated with a combination of celecoxib and octreotide (TAA + C). Immunohistochemistry and western blotting assays were used to assess the expression levels of proteins associated with inflammation, epithelial-mesenchymal transition (EMT), proliferation, apoptosis and autophagy. H&E staining, transmission electron microscopy and scanning electron microscopy were used to evaluate the destruction of hepatocytes. Masson's Trichrome and Sirius Red were used to measure the degree of liver fibrosis. The results demonstrated that, compared with those of the control group, the degree of liver fibrosis and the expression of the intrahepatic inflammation factors were aggravated in the TAA group. Furthermore, the apoptosis rate, EMT and autophagy of hepatocytes were also increased in the TAA group. However, treatment with TAA + C restored the aforementioned increased levels compared with the TAA group. In conclusion, treatment of rats with the combination of celecoxib and octreotide could attenuate the progress of hepatic fibrosis via protection of hepatocytes by reducing apoptosis, EMT and autophagy in hepatocytes.

Topographic Anatomy of the Zygomatico-Orbital Artery: Implications for Improving the Safety of Temporal Augmentation.

BACKGROUND: Anatomical knowledge of the zygomatico-orbital artery and its most relevant clinical applications is essential for ensuring the safety of filler injection into the temporal region. The purpose of this study was to provide the precise position, detailed course, and relationship with surrounding structures of the zygomatico-orbital artery. METHODS: Fifty-eight patients who underwent head contrast-enhanced three-dimensional computed tomography and 10 fresh frozen cadavers were investigated. RESULTS: The zygomatico-orbital artery was identified in 93 percent of the samples in this work. Ninety-four percent of the zygomatico-orbital arteries derived directly from the superficial temporal artery, and the remaining arteries started from the frontal branch of the superficial temporal artery. According to the origin of the zygomatico-orbital artery, it was classified into type I and type II. Type I arteries were then classified into three subtypes. The trunk of the zygomatico-orbital artery was located between the deep temporal fascia and the superficial temporal fascia. Deep branches of the zygomatico-orbital artery pierced the superficial layer of the deep temporal fascia. The zygomatico-orbital artery originated from 11.3 mm in front of the midpoint of the apex of the tragus, and most of its trunks were located less than 20.0 mm above the zygomatic arch. The mean diameter of the zygomatico-orbital artery was 1.2 ± 0.2 mm. There were extensive anastomoses between the zygomatico-orbital artery and various periorbital arteries at the lateral orbital rim. CONCLUSION: The precise anatomical knowledge of the zygomatico-orbital artery described in this study could be helpful for cosmetic physicians for improving the safety of temporal augmentation.

LncRNA FENDRR Inhibits ox-LDL Induced Mitochondrial Energy Metabolism Disorder in Aortic Endothelial Cells via miR-18a-5p/PGC-1α Signaling Pathway.

Atherosclerosis (AS) is the main cause of morbidity and mortality in the world. Mitochondrial dysfunction is closely related to AS. At present, several signaling pathways related to mitochondrial dysfunction have been found, one of which is around PGC-1α. PGC-1α is a transcription activator, which is related to mitochondrial biogenesis and antioxidant defense. In this study, we explored the effect of miR-18a-5p/PGC-1α signaling pathway on mitochondrial energy metabolism in HAECs with ox-LDL treatment. The results showed that the mitochondrial energy metabolism disorder in HAECs treated by ox-LDL was related to the downregulation of LncRNA FENDRR and PGC-1α. FENDRR could reverse ox-LDL induced mitochondrial energy metabolism disorder and upregulate the PGC-1α expression. FENDRR could be used as ceRNA to inhibit the miR-18a-5p expression and reduce the negative regulation of miR-18a-5p on PGC-1α. Downregulation of miR-18a-5p expression or upregulation of PGC-1α in ox-LDL treated HAECs could reverse mitochondrial energy metabolism disorder. In conclusion, these findings suggested that FENDRR/miR-18a-5p/PGC-1α signaling pathway regulated mitochondrial energy metabolism in HAECs; ox-LDL downregulated the expression of PGC-1α and cause mitochondrial energy metabolism disorder by inhibiting this signal pathway.

Warming-driven shifts in ecological control of fish communities in a large northern Chinese lake over 66 years.

Warming, land-use change, and habitat loss are three major threats to aquatic biodiversity worldwide under the influences of anthropogenic disturbances. Positive feedback between warming and bottom-up regulation may cause irreversible ecological regime shifts. Threshold dynamics of interspecific interactions have been rarely studied in freshwater fish communities using threshold community models. Here we use 66 years (1950-2015) of data to link four ecological regime shifts of 9-species fish communities to climatic and land use changes in Lake Hulun, the largest freshwater lake of Northern China. Overfishing caused the collapse of piscivorous fish populations and an ecological regime shift of Lake Hulun in the late 1950s. The first recorded algal bloom of Lake Hulun took place in 1986, with accelerated warming and rapid increases in livestock grazing. The dominance of planktivorous minnow populations reduced fish biodiversity in a nonlinear, threshold manner when annual mean ambient temperature was >0.12 °C. Multivariate environmental vector regression demonstrated that warming, eutrophication, and water-storage reduction (i.e., habitat loss) were related to three ecological regime shifts of Lake Hulun from 1960 to 2015. Multivariate autoregressive models (MAR) did not detect predation by piscivorous fish in Lake Hulun after 1960. Threshold MAR models indicated that dominant minnow populations and other prey fish populations switched from top-down to bottom-up control during the 1980s. Sustained positive feedback between warming, the dominance of planktivorous fish populations, and bottom-up regulation caused predator-prey role reversal, and probably resulted in three regime shifts of Lake Hulun over 56 years. This study provides a comprehensive analysis of ecological regime shifts in Hulun Lake fish communities, and has potential implications for fish species living in similar environments that are subject to global warming, land-use changes, and overfishing.

The Effects of Different UVA Photoperiods on the Growth Performance, Immune Responses, Antioxidant Status and Apoptosis-Related Gene Expression of the Pacific White Shrimp (Penaeus vannamei).

UVA is the most common type of solar UV radiation in aquatic environments; however, the effects it causes in shrimp farming in recirculating water systems (RAS) is unclear. Thus, the growth performance, immune responses, antioxidant status and apoptosis-related gene expression in Pacific white shrimp, Penaeus vannamei (body weight 9.56 ± 0.10 g), reared with 12L: 12D full spectrum light as background light under five UVA (peak at 400 nm) photoperiods (0L: 24D, 2L: 22D, 4L: 20D, 8L: 16D and 12L: 12D) at a light intensity of 1 W/m2 were investigated. The results showed that the 2L: 22D and 4L: 20D UVA photoperiods enhanced the growth performance and reduced the feed conversion ratio and the shrimp mortality. Shrimp exposed to UVA (2L: 22D and 4L: 20D) also displayed higher levels of hepatopancreas catalase (CAT), superoxide dismutase (SOD), acid phosphatase (ACP), phenol oxidase (PO) and lysozyme (LZM) compared to the 8L: 16D and 12L: 12D groups. The malondialdehyde (MDA) levels increased in line with the extension of the UVA irradiation time. The mRNA expression of apoptosis-related genes in all the UVA treatments were significantly higher than with the control treatment, except for the 2L: 22D group. The results of the 2L: 22D and 4L: 20D treatments were significantly higher than those of the control group, except for LGBP. In conclusion, 2L: 22D and 4L: 20D UVA photoperiods increased growth performance and decreased FCR, improved the innate immunity and antioxidant response and reduced the mortality rate in adult shrimp.

Deeply digging the interaction effect in multiple linear regressions using a fractional-power interaction term.

In multiple regression Y ~ ß0 + ß1X1 + ß2X2 + ß3X1 X2 + É›., the interaction term is quantified as the product of X1 and X2. We developed fractional-power interaction regression (FPIR), using ßX1 M X2 N as the interaction term. The rationale of FPIR is that the slopes of Y-X1 regression along the X2 gradient are modeled using the nonlinear function (Slope = ß1 + ß3MX1 M-1 X2 N), instead of the linear function (Slope = ß1 + ß3X2) that regular regressions normally implement. The ranges of M and N are from -56 to 56 with 550 candidate values, respectively. We applied FPIR using a well-studied dataset, nest sites of the crested ibis (Nipponia nippon).We further tested FPIR by other 4692 regression models. FPIRs have lower AIC values (-302 ± 5003.5) than regular regressions (-168.4 ± 4561.6), and the effect size of AIC values between FPIR and regular regression is 0.07 (95% CI: 0.04-0.10). We also compared FPIR with complex models such as polynomial regression, generalized additive model, and random forest. FPIR is flexible and interpretable, using a minimum number of degrees of freedom to maximize variance explained. We have provided a new R package, interactionFPIR, to estimate the values of M and N, and suggest using FPIR whenever the interaction term is likely to be significant. • Introduced fractional-power interaction regression (FPIR) as Y ~ ß0 + ß1X1 + ß2X2 + ß3X1 M X2 N + É› to replace the current regression model Y ~ ß0 + ß1X1 + ß2X2 + ß3X1 X2 + É›; • Clarified the rationale of FPIR, and compared it with regular regression model, polynomial regression, generalized additive model, and random forest using regression models for 4692 species; • Provided an R package, interactionFPIR, to calculate the values of M and N, and other model parameters.

Relationships between survival and habitat suitability of semi-aquatic mammals.

Spatial distribution and habitat selection are integral to the study of animal ecology. Habitat selection may optimize the fitness of individuals. Hutchinsonian niche theory posits the fundamental niche of species would support the persistence or growth of populations. Although niche-based species distribution models (SDMs) and habitat suitability models (HSMs) such as maximum entropy (Maxent) have demonstrated fair to excellent predictive power, few studies have linked the prediction of HSMs to demographic rates. We aimed to test the prediction of Hutchinsonian niche theory that habitat suitability (i.e., likelihood of occurrence) would be positively related to survival of American beaver (Castor canadensis), a North American semi-aquatic, herbivorous, habitat generalist. We also tested the prediction of ideal free distribution that animal fitness, or its surrogate, is independent of habitat suitability at the equilibrium. We estimated beaver monthly survival probability using the Barker model and radio telemetry data collected in northern Alabama, United States from January 2011 to April 2012. A habitat suitability map was generated with Maxent for the entire study site using landscape variables derived from the 2011 National Land Cover Database (30-m resolution). We found an inverse relationship between habitat suitability index and beaver survival, contradicting the predictions of niche theory and ideal free distribution. Furthermore, four landscape variables selected by American beaver did not predict survival. The beaver population on our study site has been established for 20 or more years and, subsequently, may be approaching or have reached the carrying capacity. Maxent-predicted increases in habitat use and subsequent intraspecific competition may have reduced beaver survival. Habitat suitability-fitness relationships may be complex and, in part, contingent upon local animal abundance. Future studies of mechanistic SDMs incorporating local abundance and demographic rates are needed.

Anti-Corrosion Property of Glass Flake Reinforced Chemically Bonded Phosphate Ceramic Coatings.

Glass flake (GF) was used as the reinforcement in chemically bonded phosphate ceramic (CBPC) coatings to promote anti-corrosion property. The crystalline phase, curing behavior, micromorphology and electrochemical performance of the coatings were studied. The results indicate that with the addition of magnesia (MgO), a new bonding phase (Mg3(PO4)2) can be formed, which can help the CBPCs achieve a more compact and denser structure. The effect of the magnesia and the GF additives on curing behavior is obvious: the heat of reaction of the phosphate ceramic materials increases with the addition of the magnesia and the GF, which emphasizes the higher crosslinking density in the phosphate ceramic materials. The phosphate ceramic coatings with the magnesia have a higher impedance value compared with the neat phosphate ceramic coating, while the highest impedance value is obtained with increased content of GF. The corrosion mechanism is mainly contributed by the new bonding phase and GF particles, which can hinder the permeation pathway and make the permeation more circuitous.

Machine learning of large-scale spatial distributions of wild turkeys with high-dimensional environmental data.

Species distribution modeling often involves high-dimensional environmental data. Large amounts of data and multicollinearity among covariates impose challenges to statistical models in variable selection for reliable inferences of the effects of environmental factors on the spatial distribution of species. Few studies have evaluated and compared the performance of multiple machine learning (ML) models in handling multicollinearity. Here, we assessed the effectiveness of removal of correlated covariates and regularization to cope with multicollinearity in ML models for habitat suitability. Three machine learning algorithms maximum entropy (MaxEnt), random forests (RFs), and support vector machines (SVMs) were applied to the original data (OD) of 27 landscape variables, reduced data (RD) with 14 highly correlated covariates being removed, and 15 principal components (PC) of the OD accounting for 90% of the original variability. The performance of the three ML models was measured with the area under the curve and continuous Boyce index. We collected 663 nonduplicated presence locations of Eastern wild turkeys (Meleagris gallopavo silvestris) across the state of Mississippi, United States. Of the total locations, 453 locations separated by a distance of ≥2 km were used to train the three ML algorithms on the OD, RD, and PC data, respectively. The remaining 210 locations were used to validate the trained ML models to measure ML performance. Three ML models had excellent performance on the RD and PC data. MaxEnt and SVMs had good performance on the OD data, indicating the adequacy of regularization of the default setting for multicollinearity. Weak learning of RFs through bagging appeared to alleviate multicollinearity and resulted in excellent performance on the OD data. Regularization of ML algorithms may help exploratory studies of the effects of environmental factors on the spatial distribution and habitat suitability of wildlife.

Latitude and daily-weather effects on gobbling activity of wild turkeys in Mississippi.

Weather has been recognized as a density independent factor influencing the abundance, distribution, and behavior of vertebrates. Male wild turkeys' (Meleagris gallopavo) breeding behavior includes vocalizations and courtship displays to attract females, the phenology of which can vary with latitude. State biologists design spring turkey-hunting season frameworks centered on annual vocalization patterns to maximize hunter engagement. The Mississippi Department of Wildlife, Fisheries, and Parks has traditionally instituted a statewide, 7-week, spring harvest season. However, hunters routinely argue that different peaks in gobbling activity across the state exist. The objective of this study was to determine whether differences in peak gobbling activity existed across a latitudinal gradient of Mississippi and assess the effect of weather on gobbling. During 2008 and 2009, we conducted a statewide gobbling survey. We used generalized additive mixed models to describe the probability and frequency of gobbling activity within northern and southern regions of the state. We also investigated the effect of daily weather conditions on gobbling activity. Our results revealed an approximate 10-14-day difference in peak gobbling activity between southern and northern Mississippi. The majority of all gobbling activity occurred within the current spring harvest framework. Perhaps more importantly, gobbling activity was more prevalent on days of regionally dry conditions (i.e., less humid) according to the Spatial Synoptic Classification. Our results provide information on gobbling activity phenology relative to hunting-season dates and weather-response information. Our approach may be particularly applicable in states with relatively shorter seasons or highly variable daily weather conditions that moderate gobbling frequency.

Rheological Behavior and Microstructure Characteristics of SCC Incorporating Metakaolin and Silica Fume.

This study explores the effects of metakaolin (MK) and silica fume (SF) on rheological behaviors and microstructure of self-compacting concrete (SCC). The rheology, slump flow, V-funnel, segregation degree (SA), and compressive strength of SCC are investigated. Microstructure characteristics, including hydration product and pore structure, are also studied. The results show that adding MK and SF instead of 4%, 6% and 8% fly ash (FA) reduces flowability of SCC; this is due to the fact that the specific surface area of MK and SF is larger than FA, and the total water demand increases as a result. However, the flowability increases when replacement ratio is 2%, as the small MK and SF particles will fill in the interstitial space of mixture and more free water is released. The fluidity, slump flow, and SA decrease linearly with the increase of yield stress. The total amount of SF and MK should be no more than 6% to meet the requirement of self-compacting. Adding MK or SF to SCC results in more hydration products, less Ca(OH)2 and refinement of pore structure, leading to obvious strength and durability improvements. When the total dosage of MK and SF admixture is 6%, these beneficial effects on workability, mechanical performance, and microstructure are more significant when SF and MK are applied together.