883 research outputs found
Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity Learning
Federated learning is an important privacy-preserving multi-party learning
paradigm, involving collaborative learning with others and local updating on
private data. Model heterogeneity and catastrophic forgetting are two crucial
challenges, which greatly limit the applicability and generalizability. This
paper presents a novel FCCL+, federated correlation and similarity learning
with non-target distillation, facilitating the both intra-domain
discriminability and inter-domain generalization. For heterogeneity issue, we
leverage irrelevant unlabeled public data for communication between the
heterogeneous participants. We construct cross-correlation matrix and align
instance similarity distribution on both logits and feature levels, which
effectively overcomes the communication barrier and improves the generalizable
ability. For catastrophic forgetting in local updating stage, FCCL+ introduces
Federated Non Target Distillation, which retains inter-domain knowledge while
avoiding the optimization conflict issue, fulling distilling privileged
inter-domain information through depicting posterior classes relation.
Considering that there is no standard benchmark for evaluating existing
heterogeneous federated learning under the same setting, we present a
comprehensive benchmark with extensive representative methods under four domain
shift scenarios, supporting both heterogeneous and homogeneous federated
settings. Empirical results demonstrate the superiority of our method and the
efficiency of modules on various scenarios
Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark
Federated learning has emerged as a promising paradigm for privacy-preserving
collaboration among different parties. Recently, with the popularity of
federated learning, an influx of approaches have delivered towards different
realistic challenges. In this survey, we provide a systematic overview of the
important and recent developments of research on federated learning. Firstly,
we introduce the study history and terminology definition of this area. Then,
we comprehensively review three basic lines of research: generalization,
robustness, and fairness, by introducing their respective background concepts,
task settings, and main challenges. We also offer a detailed overview of
representative literature on both methods and datasets. We further benchmark
the reviewed methods on several well-known datasets. Finally, we point out
several open issues in this field and suggest opportunities for further
research. We also provide a public website to continuously track developments
in this fast advancing field: https://github.com/WenkeHuang/MarsFL.Comment: 22 pages, 4 figure
W::Neo: A Novel Dual-Selection Marker for High Efficiency Gene Targeting in Drosophila
We have recently developed a so-called genomic engineering approach that allows for directed, efficient and versatile modifications of Drosophila genome by combining the homologous recombination (HR)-based gene targeting with site-specific DNA integration. In genomic engineering and several similar approaches, a “founder” knock-out line must be generated first through HR-based gene targeting, which can still be a potentially time and resource intensive process. To significantly improve the efficiency and success rate of HR-based gene targeting in Drosophila, we have generated a new dual-selection marker termed W::Neo, which is a direct fusion between proteins of eye color marker White (W) and neomycin resistance (Neo). In HR-based gene targeting experiments, mutants carrying W::Neo as the selection marker can be enriched as much as fifty times by taking advantage of the antibiotic selection in Drosophila larvae. We have successfully carried out three independent gene targeting experiments using the W::Neo to generate genomic engineering founder knock-out lines in Drosophila
Effects of soil grain size and solution chemistry on the transport of biochar nanoparticles
Biochar nanoparticles (BC-NP) have attracted significant attention because of their unique environmental behavior, some of which could potentially limit large-scale field application of biochar. Accurate prediction of the fate and transportability of BC-NP in soil matrix is the key to evaluating their environmental influence. This study investigated the effects of soil grain size and environmentally relevant solution chemistry, such as ionic strength (cation concentration, 0.1 mM–50 mM; cation type, Na+, and Ca2+), and humic acid (HA; 0–10 mg/L), on the transport behavior of BC-NP via systematic column experiments. The transportability of BC-NP in the soil-packed column decreased with decreasing soil grain size and was inversely proportional to soil clay content. At low cation concentrations (0.1–1.0 mM), a considerable proportion of BC-NP (15.95%–67.17%) penetrated the soil columns. Compared with Na+, Ca2+ inhibited the transportability of BC-NP in the soil through a charge shielding effect. With increasing HA concentration, the transportability of BC-NP increased, likely due to an enhanced repulsion force between BC-NP and soil particles. However, at a high HA concentration (10 mg/L), Ca2+ bridging reduced the transportability of BC-NP in the soil. Breakthrough curves of BC-NP were explained by the two-site kinetic retention model. The antagonistic effects of ionic strength and HA indicated that the transport behavior of BC-NP in the soil was governed by competitive effects of some environmental factors, including soil grain size, environmental solution chemistry, and natural organic matter content
Estimated pulse wave velocity is associated with all-cause and cardio-cerebrovascular disease mortality in stroke population: Results from NHANES (2003–2014)
BackgroundArterial stiffness is a significant determinant and evaluation of cardio-cerebrovascular disease and all-cause mortality risk in the stroke population. Estimated pulse wave velocity (ePWV) is a well-established indirect measure of arterial stiffness. We examined the association of ePWV with all-cause and cardio-cerebrovascular disease (CCD) mortality in the stroke population in a large sample of US adults.MethodsThe study design was a prospective cohort study with data from the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2014, between the ages of 18–85 years, with follow-up through December 31, 2019. 1,316 individuals with stroke among 58,759 participants were identified and ultimately, 879 stroke patients were included in the analysis. ePWV was calculated from a regression equation using age and mean blood pressure according to the following formula: ePWV = 9.587 − (0.402 × age) + [4.560 × 0.001 × (age2)] − [2.621 × 0.00001 × (age2) × MBP] + (3.176 × 0.001 × age × MBP) − (1.832 × 0.01 × MBP). Survey-weighted Cox regression models were used to assess the association between ePWV and all-cause and CCD mortality risk.ResultsThe high ePWV level group had a higher increased risk of all-cause mortality and CCD mortality compared to the low ePWV level group after fully adjusting for covariates. With an increase in ePWV of 1 m/s, the risk of all-cause and CCD mortality increased by 44%–57% and 47%–72% respectively. ePWV levels were linearly correlated with the risk of all-cause mortality (P for nonlinear = 0.187). With each 1 m/s increase in ePWV, the risk of all-cause mortality increased by 44% (HR 1.44, 95% CI: 1.22–1.69; P < 0.001). When ePWV was <12.1 m/s, an increase in ePWV per 1 m/s was associated with a 119% (HR 2.19, 95% CI: 1.43–3.36; P < 0.001) increase in CCD mortality risk; when ePWV was ≥12.1 m/s, an increase in ePWV per 1 m/s was not associated with in CCD mortality risk.ConclusionePWV is an independent risk factor for all-cause and CCD mortality in stroke patients. Higher levels of ePWV are associated with higher all-cause mortality and CCD mortality in stroke patients
3, 3′, 5-triiodo-L-thyronine increases in vitro chondrogenesis of mesenchymal stem cells from human umbilical cord stroma through SRC2
[Abstract] Our group focuses on the study of mesenchymal stem cells (MSCs) from human umbilical cord stroma or Warthońs jelly and their directed differentiation toward chondrocyte-like cells capable of regenerating damaged cartilage when transplanted into an injured joint. This study aimed to determine whether lactogenic hormone prolactin (PRL) or 3, 3′, 5-triiodo-L-thyronine (T3), the active thyroid hormone, modulates chondrogenesis in our in vitro model of directed chondrogenic differentiation, and whether Wnt signalling is involved in this modulation. MSCs from human umbilical cord stroma underwent directed differentiation toward chondrocyte-like cells by spheroid formation. The addition of T3 to the chondrogenic medium increased the expression of genes linked to chondrogenesis like collagen type 2, integrin alpha 10 beta 1, and Sox9 measured by quantitative real time polymerase chain reaction (qRT-PCR) analysis. Levels of collagen type 2 and aggrecane analyzed by immunohistochemistry, and staining by Safranin O were increased after 14 days in spheroid culture with T3 compared to those without T3 or only with PRL. B-catenin, Frizzled, and GSK-3β gene expressions were significantly higher in spheroids cultured with chondrogenic medium (CM) plus T3 compared to CM alone after 14 days in culture. The increase of chondrogenic differentiation was inhibited when the cells were treated with T3 plus ML151, an inhibitor of the T3 steroid receptor. This work demonstrates, for first time, that T3 promotes differentiation towards chondrocytes-like cells in our in vitro model, that this differentiation is mediated by steroid receptor co-activator 2 (SRC2) and does not induce hypertrophy.Instituto de Salud Carlos III; PI11/0279
Activating enhancer binding protein 2 epsilon (AP-2ε)-deficient mice exhibit increased matrix metalloproteinase 13 expression and progressive osteoarthritis development
Characterization of Lenticulostriate Arteries and Its Associations With Vascular Risk Factors in Community-Dwelling Elderly
Lenticulostriate arteries (LSAs) supply blood to important subcortical areas and are, therefore, essential for maintaining the optimal functioning of the brain’s most metabolically active nuclei. Past studies have demonstrated the potential for quantifying the morphology of LSAs as biomarkers of vascular fragility or underlying arteriopathies. Thus, the current study aims to evaluate the morphological features of LSAs, their potential value in cerebrovascular risk stratification, and their concordance with other vascular risk factors in community-dwelling elderly people. A total of 125 community-dwelling elderly subjects who underwent a brain MRI scan were selected from our prospectively collected imaging database. The morphological measures of LSAs were calculated on the vascular skeletons obtained by manual tracing, and the number of LSAs was counted. Additionally, imaging biomarkers of small vessel disease were evaluated, and the diameters of major cerebral arteries were measured. The effects of vascular risk factors on LSA morphometry, as well as the relationship between LSA measures and other imaging biomarkers, were investigated. We found that smokers had shorter (p = 0.04) and straighter LSAs (p < 0.01) compared to nonsmokers, and the presence of hypertension is associated with less tortuous LSAs (p = 0.03) in community-dwelling elderly. Moreover, the middle cerebral artery diameter was positively correlated with LSA count (r = 0.278, p = 0.025) and vessel tortuosity (r = 0.257, p = 0.04). The posterior cerebral artery diameter was positively correlated with vessel tortuosity and vessel length. Considering the scarcity of noninvasive methods for measuring small artery abnormalities in the brain, the LSA morphological measures may provide valuable information to better understand cerebral small vessel degeneration during aging
Self-Assemblage and Quorum in the Earthworm Eisenia fetida (Oligochaete, Lumbricidae)
Despite their ubiquity and ecological significance in temperate ecosystems, the behavioural ecology of earthworms is not well described. This study examines the mechanisms that govern aggregation behaviour specially the tendency of individuals to leave or join groups in the compost earthworm Eisenia fetida, a species with considerable economic importance, especially in waste management applications. Through behavioural assays combined with mathematical modelling, we provide the first evidence of self-assembled social structures in earthworms and describe key mechanisms involved in cluster formation. We found that the probability of an individual joining a group increased with group size, while the probability of leaving decreased. Moreover, attraction to groups located at a distance was observed, suggesting a role for volatile cues in cluster formation. The size of earthworm clusters appears to be a key factor determining the stability of the group. These findings enhance our understanding of intra-specific interactions in earthworms and have potential implications for extraction and collection of earthworms in vermicomposting processes
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