Signaling and Social Influence: The Impact of Corporate Volunteer Programs on Employee Work Behavior

Corporate volunteer programs serve the social agenda of the organizations that deploy them, and are important channels for delivering care and compassion to important causes and communities in need. However, the uptake of these programs by employees is surprisingly low. Little is known about the affective reactions of those who do not avail themselves of the programs offered. In this dissertation, I draw from research on work-life benefits, as well as theories of signaling and social influence, to examine the effects of corporate volunteer programs on the affect and behavior of both the employees who take part in the initiatives, as well as those who do not. In a pilot study, I find initial support for the positive synergies of multiple role engagement – specifically, that time spent on non-work-related activities has a significant positive effect on individuals’ perceptions of work-life enrichment, and this in turn relates positively to their engagement and personal initiative at work. This pre-test of measures and theoretical relationships provided a stepping stone for my primary dissertation project: a longitudinal field study at a large organization in the Northeast to examine the effects of its corporate volunteer program. Through surveys at two points in time, I find that even when employee participation in volunteering is low, such programs may nevertheless have a significant influence on employees’ work-related perceptions and behavior, as driven primarily by processes of social sharing. Workplace conversations around volunteering led to enhanced perceptions of organizational support for enrichment, increased interpersonal citizenship behaviors at work, and stronger future volunteer intentions, regardless of whether or not employees personally took part in the volunteer activity. These positive effects are most prominent when employees are in positions that afford the flexibility to join in such initiatives. Understanding the effects of social influence and the factors that moderate the impact of these corporate programs on employee outcomes is important as firms seek to provide a more enriching environment for their workforce

The expression profile analysis of NKX2-5 knock-out embryonic mice to explore the pathogenesis of congenital heart disease

AbstractBackgroundMutation of NKX2-5 could lead to the development of congenital heart disease (CHD) which is a common inherited disease. This study aimed to investigate the pathogenesis of CHD in NKX2-5 knock-out embryonic mice.MethodsThe expression profile in the NKX2-5 knock-out embryonic mice (GSE528) was downloaded from Gene Expression Omnibus. The heart tissues from the null/heterozygous embryonic day 12.5 mice were compared with wild-type mice to identify differentially expressed genes (DEGs), and then DEGs corresponding to the transcriptional factors were filtered out based on the information in the TRANSFAC database. In addition, a transcriptional regulatory network was constructed according to transcription factor binding site information from the University of California Santa Cruz database. A pathway interaction network was constructed by latent pathways identification analysis.ResultsThe 42 DEGs corresponding to transcriptional factors from the null and heterozygous embryos were identified. The transcriptional regulatory networks included five down-regulated DEGs (SP1, SRY, JUND, STAT6, and GATA6), and six up-regulated DEGs [POU2F1, NFY (NFYA/NFYB/NFYC), USF2 and MAX]. Latent pathways analysis demonstrated that ribosome, glycolysis/gluconeogenesis, and dilated cardiomyopathy pathways significantly interacted.ConclusionThe identified DEGs and latent pathways could provide new comprehensive view for understanding the pathogenesis of CHD

Generation of a Urine-Derived Ips Cell Line from a Patient with a Ventricular Septal Defect and Heart Failure and the Robust Differentiation of These Cells to Cardiomyocytes via Small Molecules

Background/Aims: Ventricular septal defects (VSDs) are one of the most common types of congenital heart malformations. Volume overload resulting from large VSDs can lead to heart failure (HF) and constitutes a major cause of pediatric HF with a series of often-fatal consequences. The etiology of VSD with HF is complex, and increasing evidence points toward a genetic basis. Indeed, we identified an L2483R mutation in the ryanodine receptor type 2 (RyR2) in a 2-month-old male patient with VSD with HF. Methods: We generated integration-free induced pluripotent stem cells from urine samples (UiPSCs) of this patient using Sendai virus containing the Yamanaka factors and characterized these cells based on alkaline phosphatase activity, pluripotency marker expression, and teratoma formation. Then, we induced the derived UiPSCs to rapidly and efficiently differentiate into functional cardiomyocytes through temporal modulation of canonical Wnt signaling with small molecules. Real-time PCR and immunofluorescence were used to verify the expression of myocardium-specific markers in the differentiated cardiomyocytes. The ultrastructure of the derived myocardial cells was further analyzed by using transmission electron microscopy. Results: The established UiPSC lines were positive for alkaline phosphatase activity, retained the RyR2 mutation, expressed pluripotency markers, and displayed differentiation potential to three germ layers in vivo. The UiPSC-derived cells showed hallmarks of cardiomyocytes, including spontaneous contraction and strong expression of cardiac-specific proteins and genes. However, compared with cardiomyocytes derived from H9 cells, they had a higher level of autophagy, implying that autophagy may play an important role in the development of VSD with HF. Conclusion: The protocol described here yields abundant myocardial cells and provides a solid platform for further investigation of the pathogenesis, pharmacotherapy, and gene therapy of VSD with HF

Schistosomiasis Japonica Control in Domestic Animals: Progress and Experiences in China

Schistosomiasis japonica, caused by Schistosoma japonicum, is an endemic, zoonotic parasitic disease. Domestic animals, particularly bovines, are thought to play an important role in transmission of the disease. Historically, China was the country mostly severely impacted by schistosomiasis japonica, but now prevalence and morbidity have been greatly reduced. Since the mid-1950s when China launched the National Schistosomiasis Control Program, the control of schistosomiasis in domestic animals has been carried out almost synchronously with that of human schistosomiasis, and this concept has been proven to be effective. Generally, the campaign of schistosomiasis japonica control in domestic animals in China went through four phases over the past six decades, namely, the large-scale epidemiological investigation phase, the case screening and small-scale chemotherapy phase, the mass chemotherapy phase, and the infection source control phase. These distinct phases were responsive to changing disease epidemiology, socioeconomic development, and technological advances, resulting in successful attainment of disease control goals

Real-Time Service Composition Algorithm based on Semantic Web

Abstract: Real-time service composition needs to meet the time constraints precisely and enhanced the speed of combination computing quickly. To improve the accuracy of service selection, we establish a time ontology model and a set of inference rules, the search strategies through logic reasoning combined with the extended UDDI improve the search efficiency by 129 % and accuracy by 161%. In the process of service composition, the improved simulated annealing algorithm (WSC-ISA) is proposed to implement the NP-hard problem of web service composition with QoS properties, which optimizes the solution by time priority and accepting deterioration solution in probability. Experiment results show that the efficiency of WSC-ISA is improved by more than 6 % and the time is reduced by more than 12.3%, which shows the algorithm reduces the computation time while maintains the high efficiency

Preparation of Fe₃O₄@PDA@Au@GO Composite as SERS Substrate and Its Application in the Enrichment and Detection for Phenanthrene

In this study, highly active Fe3O4@PDA@Au@GO surface-enhanced Raman spectroscopy (SERS) active substrate was synthesized for application in the enrichment and detection of trace polycyclic aromatic hydrocarbons (PAHs) in the environment. The morphology and structure were characterized by transmission electron microscopy (TEM), energy-dispersive spectroscopy (EDS), X-ray diffraction (XRD) and UV–visible absorption spectrum (UV–vis spectra). The effect of each component of Fe3O4@PDA@Au@GO nanocomposites on SERS was explored, and it was found that gold nanoparticles (Au NPs) are crucial to enhance the Raman signal based on the electromagnetic enhancement mechanism, and apart from enriching the PAHs through π–π interaction, graphene oxide (GO) also generates strong chemical enhancement of Raman signals, and polydopamine (PDA) can prevent Au from shedding and agglomeration. The existence of Fe3O4 aided the quick separation of substrate from the solutions, which greatly simplified the detection procedure and facilitated the reuse of the substrate. The SERS active substrate was used to detect phenanthrene in aqueous solution with a detection limit of 10−7 g/L (5.6 × 10−10 mol/L), which is much lower than that of ordinary Raman, it is promising for application in the enrichment and detection of trace PAHs

The Efficacy and Safety of Mainstream Medications for Patients With cDMARD-Naïve Rheumatoid Arthritis: A Network Meta-Analysis

Background: The mainstream medications for rheumatoid arthritis (RA) include conventional disease-modifying antirheumatic drugs (cDMARDs), which mostly are methotrexate (MTX), and biologic agents such as adalimumab (ADA), certolizumab (CZP), etanercept (ETN), golimumab (GOL), infliximab (IFX), and tocilizumab (TCZ). This network meta-analysis was aimed at evaluating the efficacy and safety of the medications above and interventions combining cDMARDs and biologic agents for patients with RA.Methods: PubMed, EMBASE, Cochrane Library, and ClinicalTrials.gov were searched systematically for eligible randomized controlled trials (RCTs). Outcomes concerning efficacy and safety were evaluated utilizing odds ratios (ORs) and 95% credible intervals (CrI). The outcomes of efficacy would be evaluated through remission and American College of Rheumatology (ACR) scores. The surface under the cumulative ranking curve (SUCRA) was calculated to rank each treatment on each index.Results: A total of 20 RCTs with 9,047 patients were included, and the efficacy and safety of the concerning interventions for RA were evaluated. Compared with cDMARDs alone, TCZ+MTX, ETN+MTX, IFX+MTX, TCZ, and ADA+MTX showed significant statistical advantage on ACR20, ACR50, and ACR70. Apart from that, as for remission, TCZ+MTX, IFX+MTX, TCZ, and CZP+MTX performed better compared to cDMARDs alone. The SUCRA ranking also indicated that TCZ+MTX was the intervention with best ranking in the entire four efficacy indexes followed by ETX+MTX and IFX+MTX. However, there was no obvious difference among these medications compared with cDMARDs when it comes to safety, which need more specific studies on that.Conclusion: TCZ+MTX was potentially the most recommended combination of medications for RA due to its good performance in all outcomes of efficacy. ETX+MTX and IFX+MTX, which also performed well, could be introduced as alternative treatments. However, considering the adverse events, the treatments concerning should be introduced with caution

Comparison of an Artificial Neural Network and a Response Surface Model during the Extraction of Selenium-Containing Protein from Selenium-Enriched <i>Brassica napus</i> L.

In this study, the extraction conditions for selenium-enriched rape protein (SEP) were optimized by applying a response surface methodology (RSM) and artificial neural network (ANN) model, and then, the optimal conditions were obtained using a genetic algorithm (GA). Then, the antioxidant power of the SEP was examined by using the DPPH, ABTS, and CCK-8 (Cell Counting Kit-8), and its anticancer activities were explored by conducting a cell migration test. The results showed that compared with the RSM model, the ANN model was more accurate with a higher determination coefficient and fewer errors when it was applied to optimize the extraction method. The data obtained for SEP using a GA were as follows: the extraction temperature was 59.4 °C, the extraction time was 3.0 h, the alkaline concentration was 0.24 mol/L, the liquid-to-material ratio was 65.2 mL/g, and the predicted content of protein was 58.04 mg/g. The protein was extracted under the conditions obtained by the GA; the real content of protein was 57.69 mg/g, and the protein yield was 61.71%. Finally, as the concentration of the selenium-containing protein increased, it showed increased ability in scavenging free radicals and was influential in inhibiting the proliferation and migration of HepG2 cells