Turning Social Capital into Economic Capital: the Sales Effect of Friendship Group Participation in Social Commerce Websites

Friendship groups have been widely adopted in social commerce platforms because of the powerful and pervasive influence of groups on decision making. Despite their widespread use, the sales effects of seller participation in friendship groups (FGP) have received limited research attention. Using a quasi-experimental design with 373,964 products from 8,250 sellers on a leading social commerce platform, we find that FGP increase sellers\u27 product sales performance through the formation of relational and cognitive capital. In addition, we find that seller guarantee, product guarantee and product rating strengthen the sales effect of FGP, while the number of seller followers weakens the sales effect of FGP. Our study contributes to the literature by examining how, why, and when FGP affect sales performance in social commerce. We also provides guidance for sellers and platforms to use friendship groups and group marketing to improve sales performance in social commerce

Etude en rupture d'un composite à fibres végétales d'Alfa

National audienceThe behavior under monotonic loading of reinforced natural fibre composites begins to be fairly well known today. However, the fracture behavior is still poorly controlled. This work describes a numerical approach developed to simulate the propagation mechanism of a matrix crack in natural fibre reinforced composites.To this end, the fracture behavior of a REV; constituted of alfa fibre, with linear anisotropic behavior, surrounded by a matrix with non-linear viscoelastic behavior, was investigated using a finite element model. The analysis of the fracture behavior of the composite alfa fibre / epoxy resin shows that under uniaxial longitudinal or transverse load to the fibre, a crack initiated in the matrix is propagated perpendicularly to the direction of the load. Near the interface, the energy release rate decreases and this energy is higher in the presence of interfacial debonding areas generated by problems of fibre wettability. Reaching the interface, the crack is either blocked or deflected. Once deflected, the crack propagates along the interface and causes the complete debonding of the fibre.Le comportement sous chargement monotone des composites renforcés par des fibres naturelles commence à être assez bien connu aujourd'hui. Cependant, le comportement à la rupture est encore mal maîtrisé. Le présent travail décrit une approche numérique développée pour simuler le mécanisme de propagation d'une fissure matricielle à l'interface fibre végétale alfa / résine époxy dans les composites à matrice polymère. A cette fin, le comportement à la rupture d'un VER constitué d'une fibre unitaire d'alfa, de comportement linéaire anisotrope, entourée d'une matrice de comportement non linéaire viscoélastique, a été étudié à l'aide d'un modèle éléments finis. L'analyse du comportement à la rupture du composite fibre alfa/résine époxy montre que sous l'action d'un chargement uniaxial, longitudinal ou transversal par rapport à la fibre, une fissure initiée dans la matrice se propage perpendiculairement au sens de la sollicitation. Au voisinage de l'interface, le taux de restitution d'énergie diminue et ce taux est plus élevé en présence de zones de non adhésion générées par des problèmes de mouillages. Arrivée à l'interface, la fissure est soit bloquée soit déviée. Une fois déviée, la fissure se propage le long de l'interface et entraîne la décohésion de la fibre

Cobalt-doped porous carbon nanosheets derived from 2D hypercrosslinked polymer with CoN₄ for high performance electrochemical capacitors

Cobalt-doped graphene-coupled hypercrosslinked polymers (Co-GHCP) have been successfully prepared on a large scale, using an efficient RAFT (Reversible Addition-Fragmentation Chain Transfer Polymerization) emulsion polymerization and nucleophilic substitution reaction with Co (II) porphyrin. The Co-GHCP could be transformed into cobalt-doped porous carbon nanosheets (Co-GPC) through direct pyrolysis treatment. Such a Co-GPC possesses a typical 2D morphology with a high specific surface area of 257.8 m2 g−1. These intriguing properties of transition metal-doping, high conductivity, and porous structure endow the Co-GPC with great potential applications in energy storage and conversion. Utilized as an electrode material in a supercapacitor, the Co-GPC exhibited a high electrochemical capacitance of 455 F g−1 at a specific current of 0.5 A g−1. After 2000 charge/discharge cycles, at a current density of 1 A g−1, the specific capacitance increased by almost 6.45%, indicating the excellent capacitance and durability of Co-GPC. These results demonstrated that incorporation of metal porphyrin into the framework of a hypercrosslinked polymer is a facile strategy to prepare transition metal-doped porous carbon for energy storage applications

Application of Weighted Gene Co-expression Network Analysis for Data from Paired Design

Investigating how genes jointly affect complex human diseases is important, yet challenging. The network approach (e.g., weighted gene co-expression network analysis (WGCNA)) is a powerful tool. However, genomic data usually contain substantial batch effects, which could mask true genomic signals. Paired design is a powerful tool that can reduce batch effects. However, it is currently unclear how to appropriately apply WGCNA to genomic data from paired design. In this paper, we modified the current WGCNA pipeline to analyse high-throughput genomic data from paired design. We illustrated the modified WGCNA pipeline by analysing the miRNA dataset provided by Shiah et al. (2014), which contains forty oral squamous cell carcinoma (OSCC) specimens and their matched non-tumourous epithelial counterparts. OSCC is the sixth most common cancer worldwide. The modified WGCNA pipeline identified two sets of novel miRNAs associated with OSCC, in addition to the existing miRNAs reported by Shiah et al. (2014). Thus, this work will be of great interest to readers of various scientific disciplines, in particular, genetic and genomic scientists as well as medical scientists working on cancer

Incidence and influencing factors of fertility concerns in breast cancer in young women: a systematic review and meta-analysis

ObjectiveThis systematic review and meta-analysis aimed to evaluate the prevalence and influencing factors of fertility concerns in breast cancer in young women.MethodsA literature search on PubMed, Embase, Web of Science, and Cochrane Library databases was conducted up to February 2023 and was analyzed (Revman 5.4 software) in this study. The papers were chosen based on inclusion standards, and two researchers independently extracted the data. The included studies’ quality was evaluated using criteria set out by the Agency for Healthcare Research and Quality. To identify significant variations among the risk factors, odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) were utilized.ResultsA total of 7 studies that included 1579 breast cancer in young women were enrolled in the study. The results showed that for breast cancer in young women, the incidence of fertility concerns 53%(95%CI [0.45,0.58]). The results showed that education (2.65, 95% CI 1.65–5.63), full-time work (0.12, 95% CI 1.03–1.93), fertility intentions (7.84, 95% CI 1.50–37.4), depression level (1.25, 95% CI 1.03–1.5), and endocrine therapy (1.32, 95% CI 1.08–1.62) were risk factors for fertility concerns in young women with BC. Having a partner (0.41, 95% CI 0.33–0.5), ≥1 child (0.3, 95% CI 0.22–0.4) were identified as protective factors against fertility concerns in young women with BC.ConclusionsThe incidence of fertility concerns in breast cancer in young women is at a moderately high level. We should pay more attention to the risk factors of fertility concerns to help breast cancer in young women cope with their fertility concerns and promote their psychological well-being

Gut microbiota-derived metabolite Trimethylamine-N-oxide (TMAO) and multiple health outcomes:an umbrella review and updated meta-analysis

BACKGROUND: Trimethylamine-N-oxide (TMAO) is a gut microbiota-derived metabolite produced from dietary nutrients. Many studies have discovered that circulating TMAO levels are linked to a wide range of health outcomes. OBJECTIVES: This study aimed to summarize health outcomes related to circulating TMAO levels. METHODS: We searched Embase, Medline, Web of Science and Scopus databases from inception to 15 February 2022 to identify and update meta-analyses examining the associations between TMAO and multiple health outcomes. For each health outcome, we estimated the summary effect size, 95% prediction confidence interval (CI), between-study heterogeneity, evidence of small-study effects, and evidence of excess-significance bias. These metrics were used to evaluate the evidence credibility of the identified associations. RESULTS: This umbrella review identified 24 meta-analyses that investigated the association between circulating TMAO levels and health outcomes including all-cause mortality, cardiovascular diseases, diabetes mellitus, cancer, and renal function. We updated these meta-analyses by including a total of 82 individual studies in 18 unique health outcomes. Among them, 14 associations were nominally significant. After evidence credibility assessment, we found six (33%) associations (i.e., all-cause mortality, cardiovascular disease mortality, major adverse cardiovascular events, hypertension, diabetes mellitus, and glomerular filtration rate) to present highly suggestive evidence. CONCLUSIONS: TMAO might be a novel biomarker related to human health conditions including all-cause mortality, hypertension, cardiovascular disease, diabetes, cancer and kidney function. Further studies are needed to investigate whether circulating TMAO levels could be an intervention target for chronic disease

Growth differentiation factor-15/adiponectin ratio as a potential biomarker for metabolic syndrome in Han Chinese

AimsGrowth differentiation factor-15 (GDF-15) and adiponectin are adipokines that regulate metabolism. This study aimed to evaluate the roles of GDF-15, adiponectin, and GDF-15/adiponectin ratio (G/A ratio) as biomarkers for detecting metabolic syndrome (MS).Materials and methodsThis cross-sectional study included 676 participants aged 20–70 years in Jurong, China. The participants were divided into four groups based on sex and age (<40 and ≥40 years). MS was defined according to the modified National Cholesterol Education Program Adult Treatment Panel III criteria. Receiver operating characteristic curves were used to evaluate the performance of GDF-15, adiponectin, and the G/A ratio in predicting MS.ResultsThe prevalence of MS was 22.0% (149/676). Logistic regression analysis indicated that the G/A ratio and adiponectin levels, but not GDF-15 levels, were correlated with MS [odds ratio; 95% CI 1.010 (1.006–1.013) and 0.798 (0.735–0.865), respectively] after adjusting for confounding factors. The G/A ratio displayed a significant relationship with MS in each subgroup and with each MS component in both men and women; however, adiponectin concentrations were significantly associated with MS and all its components only in men (all P <0.05). The area under the curve (AUC) of the G/A ratio and the adiponectin level for MS was 0.758 and 0.748, respectively. The highest AUC was 0.757 for the adiponectin level in men and 0.724 for the G/A ratio in women.ConclusionsThis study suggests that the G/A ratio and adiponectin are potential biomarkers for detecting MS in women and men, respectively

Distinct miRNAs associated with various clinical presentations of SARS-CoV-2 infection.

MicroRNAs (miRNAs) have been shown to play important roles in viral infections, but their associations with SARS-CoV-2 infection remain poorly understood. Here, we detected 85 differentially expressed miRNAs (DE-miRNAs) from 2,336 known and 361 novel miRNAs that were identified in 233 plasma samples from 61 healthy controls and 116 patients with COVID-19 using the high-throughput sequencing and computational analysis. These DE-miRNAs were associated with SASR-CoV-2 infection, disease severity, and viral persistence in the patients with COVID-19, respectively. Gene ontology and KEGG pathway analyses of the DE-miRNAs revealed their connections to viral infections, immune responses, and lung diseases. Finally, we established a machine learning model using the DE-miRNAs between various groups for classification of COVID-19 cases with different clinical presentations. Our findings may help understand the contribution of miRNAs to the pathogenesis of COVID-19 and identify potential biomarkers and molecular targets for diagnosis and treatment of SARS-CoV-2 infection