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Rotavirus vaccine performance varies between high and low income countries. One possible explanation is inherited histo-blood group antigens (HBGAs) the expression of which differs between populations. HBGAs are polymorphic glycans on mucosal surfaces. Their presence indicates the secretor phenotype, while their absence identifies a non-secretor status. HBGAs can act as rotavirus receptors and might influence live-attenuated rotavirus vaccine virus replication and shedding. Studies in low and middle income countries of the human rotavirus vaccine Rotarix (RV1), suggest HBGA secretor phenotype is important for vaccine immunogenicity. We investigated in a high income country the association between HBGA phenotype (secretor and Lewis) and the bovine-human reassortment vaccine RotaTeq (RV5) vaccine shedding in the stools of infants following each vaccine dose. Eighty-two infants from an Australian birth cohort provided saliva and weekly stool samples after RV5 vaccination doses. Lewis and secretor HBGA phenotyping was identified from saliva samples and confirmed by genotyping. Vaccine virus strains were detected by real-time polymerase chain reaction assays. No significant association between secretor status and vaccine virus shedding was identified. The proportion of infants who shed rotavirus following the first RV5 dose for secretor and non-secretor infants was 57/64 (89%) and 17/18 (94%), respectively, decreasing to 24/64 (33%) and 9/18 (50%) after the second dose and 26/64 (42%) and 8/18 (44%) following the third vaccine dose, respectively. Similarly, no significant differences were observed in vaccine virus shedding by Lewis, or combined Lewis and secretor status, after each vaccine dose. We found HBGAs were not associated with RV5 vaccine virus shedding in Australian infants.

Purpose This study aims to review the progress of research on artificial intelligence (AI) relating to the hospitality and tourism industry, focusing on the content, focal points, key terms and trends of AI research. Design/methodology/approach A total of 491 referred papers are selected from the Web of Science core collection database. These papers, published in the past 30 years (1991–2021), are analyzed by using Gephi and VOSviewer software. Findings AI research shows a growing trend since 1991, and the number of publications and citations increased significantly since 2018, indicating that AI became a focus for researchers. AI studies are grouped into four clusters, namely, AI technology, technology acceptance, customers’ perception and future trends. The research focus changed from AI technology in the early stage to customers’ attitudes toward and willingness to accept AI. Research limitations/implications The findings contribute to advance knowledge development, identify research gaps and shed light on future research. The results offer practical enlightenment for governments, tourism destinations and hospitality organization. Practical implications The results offer practical enlightenment for governments, tourism destinations and hospitality organization. Originality/value This study is the initial attempt to provide a systematic review of AI research relating to the tourism and hospitality fields.

Family navigator programs are becoming increasingly common among families of children with autism. Yet, it is unclear how family navigators are developed; by exploring the input of families of children with autism, such programs can be responsive to family needs. In this study, 12 parents of autistic children from low-resourced communities were interviewed to inform the development of a family navigator program. Findings demonstrated that programs need to prepare navigators to address barriers such as limited knowledge and difficulty accepting an autism diagnosis. Programs should teach navigators to use strategies with families including educating families about services and connecting families with peer support. Program content should reflect direct services, government services, and advocacy strategies. Implications are discussed.

Supplementary Figure 1 - PDF files 2472K, Expression of cell surface markers throughout CLL PBMC

Purpose: Despite advances in the treatment of chronic lymphocytic leukemia (CLL), the disease remains incurable with standard therapies and relapse is inevitable. A growing body of evidence indicates that alterations in the adhesion properties of neoplastic cells play a pivotal role in the development and progression of CLL.Experimental Design: The expression of 71 cell surface molecules was examined on CLL peripheral blood mononuclear cells (PBMCs) over 3 weeks in culture. The most highly upregulated marker, CD62L, was examined further for expression on CD5+/CD19+ CLL cells in vitro and in lymph node and bone marrow biopsies. The prosurvival role of CD62L was examined using a functional blocking antibody and therapeutic potential evaluated by comparison with current chemotherapy agents.Results: Blocking CD62L resulted in apoptosis of CLL cells but not PBMCs from healthy donors suggesting a novel role for CD62L in CLL cell survival. The beneficial effect of coculturing CLL cells with bone marrow stromal cells or endothelial cells does not protect CLL cells from anti-CD62L–related toxicity. Moreover, combining fludarabine or mafosfamide with the anti-CD62L in vitro produced an additive effect both with and without stromal cells.Conclusion: This is the first reported data showing that blocking the activation and homing marker, CD62L, regulates CLL cell survival in vitro. These data also suggest that therapeutic antibodies against CD62L may provide additional clinical benefit to patients with CLL receiving current standard chemotherapy protocols. Clin Cancer Res; 19(20); 5675–85. ©2013 AACR.

Supplementary Figure Legends - PDF files 57K, Figure Legends

Supplementary Table 2 - PDF files 77K, CD markers used in phenotype screen

Supplementary Figure 3 - PDF files 1469K, Correlation of CD62L antibody toxicity and clinical parameters

Supplementary Table 1 - PDF files 69K, Patient Data

Supplementary Table 1 from Induction of Human Arylamine N-Acetyltransferase Type I by Androgens in Human Prostate Cancer Cells

This study analyzes the rapid development of mobile payment in the fast-food restaurant industry and the effect it has on consumer behavior. Moreover, this work examines the influence of mobile payment users' motivation on satisfaction and the effects of motivation and satisfaction on continuance intention. A total of 547 questionnaires were collected in Shenzhen China prior to the late 2019 COVID-19 pandemic outbreak. The findings indicate that motivation and satisfaction each has a significant positive, direct effect on the continuance intention of mobile payment usage. The results show that intrinsic motivation, notably the Perceived Enjoyment factor, has a greater impact than satisfaction on continuance intention. Respondents are less satisfied with Perceived Privacy and Perceived Security but show greater satisfaction with Perceived Service Quality. Perceived Enjoyment and Perceived Service Quality can evoke the intention to continue to use mobile payment. The results of this research provide useful information for mobile payment providers and fast-food restaurant owners to further improve their services. The proposed consumer behavior framework of the continuance intention of mobile payment service usage can be used as a basis for hospitality researchers to refine research on mobile payment technology and service management.

The purpose was to investigate long-term health impacts of trauma and the aim was to describe the functional outcome and health status up to 7 years after trauma. We conducted a prospective, multi-centre cohort study of adult trauma patients admitted to three regional trauma centres with moderate or major trauma (ISS ≥ 9) in Hong Kong (HK). Patients were followed up at regular time points (1, 6 months and 1, 2, 3, 4, 5, 6, and 7 years) by telephone using extended Glasgow Outcome Scale (GOSE) and the Short-Form 36 (SF36). Observed annual mortality rate was compared with the expected mortality rate estimated using the HK population cohort. Linear mixed model (LMM) analyses examined the changes in SF36 with subgroups of age ≥ 65 years, ISS > 15, and GOSE ≥ 5 over time. At 7 years, 115 patients had died and 48% (138/285) of the survivors responded. The annual mortality rate (AMR) of the trauma cohort was consistently higher than the expected mortality rate from the general population. Forty-one percent of respondents had upper good recovery (GOSE = 8) at 7 years. Seven-year mean PCS and MCS were 45.06 and 52.06, respectively. LMM showed PCS improved over time in patients aged

Sodium-Glucose Co-Transporter 2 (SGLT2) inhibitors have demonstrated kidney, cardiovascular and mortality benefits in the general population; however, the evidence is limited in solid organ transplant recipients. The aim of this systematic review was to evaluate the current efficacy and safety data of SGLT2 inhibitors in adult kidney, heart, lung, and liver transplant recipients with pre-existing type 2 or post-transplantation diabetes mellitus.We searched MEDLINE, MEDLINE Epub, CENTRAL, CDSR, EMBASE, CINAHL, and sources of unpublished literature. All primary interventional and observational studies on SGLT2 inhibitors in transplant recipients were included. Clinical outcomes included mortality, cardiovascular and kidney events, and adverse events such as graft rejection. Surrogate markers including hemoglobin A1c (HbA1c) and weight reduction were also evaluated.Of the 17 studies that were included in this systematic review, there were 15 studies on kidney transplant recipients (n = 2417 patients) and two studies on heart transplant recipients (n = 122 patients). There was only one randomized controlled trial which evaluated 49 kidney transplant patients over 24 weeks. Overall, studies were heterogeneous in study design, sample size, duration of diabetes, time to SGLT2 inhibitor initiation post-transplantation (ranging from 0.88 to 11 years post kidney transplant; five to 5.7 years post heart transplant) and follow-up (ranging from 0.4 to 5.25 years in kidney transplant patients; 0.75 to one year in heart transplant patients). Only one retrospective study evaluated mortality as a part of a composite outcome in kidney transplant patients; however, study limitations restrict generalizability of results. Overall, studies could not confirm clinical cardiovascular and kidney benefits in the transplant population. Findings suggested that SGLT2 inhibitors may improve glycemic control; however, they are associated with urinary tract infection. Diabetic ketoacidosis and acute kidney injury also occurred in these studies, with precipitating factors such as infection and acute heart failure exacerbation.While SGLT2 inhibitors are promising agents with expanding indications in the non-transplant population, these agents may not be suitable for all solid organ transplant recipients, and close monitoring (e.g. for urinary tract infections) and patient education (e.g. sick day management) are essential if these agents are initiated. Evidence is based on short-term findings and suggests an association with hemoglobin A1c reduction and increased adverse events. Further long-term randomized controlled trials are needed to evaluate the effect of SGLT2 inhibitors on clinically important outcomes, including mortality reduction, in solid organ transplant recipients.

Preschoolers and kindergarteners demonstrate rapid growth and change in motor skills, socio-emotional (SE) skills, and academic performance. Data on 250 children with disabilities (CWD) and 250 typically developing children (TDC) from the Early Childhood Longitudinal Study-Birth Cohort (ECLS-B) data set were analyzed to explore the relation between motor skills, SE skills and academic performance for children with and without disabilities. The ECLS-B data set is the first study to follow children from birth through kindergarten entry, collecting data on thier early development. The current study utilized descriptive and regression analyses (survey frequency, mean, and regression) were conducted using Statistical Analysis Software (SAS) version 9.2 (SAS Institute, 2008). Results indicated that both fine and gross motor skills make significant contributions to SE skills in CWD at both preschool and kindergarten and in TDC at preschool only. A significant correlation between fine and gross motor skills and academic performance was found for CWD and TDC in preschool and kindergarten. These findings indicated that an increased emphasis on the development of fine and gross motor skills during the preschool years may benefit the development of SE skills and academic performance for CWD. Results sheds light on the importance of including motor interventions as part of early childhood education programs delivered to CWD to narrow the achievement gap and ideally result in early learning success.

This study aims to explore the psychological needs and satisfaction of Chinese, Japanese, and Korean tourists across three phases (i.e. before, during and perceived aftermath) of the COVID-19 pande...

The high dropout rate from Massive Open Online Courses (MOOCs) has been a major concern of researchers and educators over the years. Although academic papers on MOOCs have mushroomed over the past ...

The purpose of this study is to develop an in-depth understanding of cultural diversity in China’s hotels by examining hotel employees’ Intercultural Communication Competency (ICC) practices. Follo...

Preschoolers demonstrate rapid growth in motor, cognitive, and socioemotional (SE) skills. The Early Childhood Longitude Study–Birth Cohort was used to investigate the discrepancy in fine motor, gross motor, cognitive, and SE skills between children with and without disabilities. Findings indicated that, compared with typically developing children (TDC), children with disabilities (CWD) have (a) significant discrepancies in preschool and kindergarten among these skills, (b) an increased discrepancy in fine motor and cognitive skills from preschool to kindergarten, (c) the largest gaps in gross motor skills at preschool and kindergarten, and (d) no significant change in SE gaps from preschool to kindergarten. The findings provide evidence to support the discrepancies in motor, cognitive, and SE skills between CWD and TDC that occur as early as preschool, and that these discrepancies are not getting smaller as children enter kindergarten.

This study examines the impacts of frontline hotel employees’ emotional intelligence (EI) and cultural intelligence (CQ) on guests’ satisfaction, and uniquely captures guests’ perceptions of staff ...

International audience; Outcomes reported in randomized controlled trials in peritoneal dialysis (PD) are diverse, are measured inconsistently, and may not be important to patients, families, and clinicians. The Standardized Outcomes in Nephrology-Peritoneal Dialysis (SONG-PD) initiative aims to establish a core outcome set for trials in PD based on the shared priorities of all stakeholders. We convened an international SONG-PD stakeholder consensus workshop in May 2018 in Vancouver, Canada. Nineteen patients/caregivers and 51 health professionals attended. Participants discussed core outcome domains and implementation in trials in PD. Four themes relating to the formation of core outcome domains were identified: life participation as a main goal of PD, impact of fatigue, empowerment for preparation and planning, and separation of contributing factors from core factors. Considerations for implementation were identified: standardizing patient-reported outcomes, requiring a validated and feasible measure, simplicity of binary outcomes, responsiveness to interventions, and using positive terminology. All stakeholders supported inclusion of PD-related infection, cardiovascular disease, mortality, technique survival, and life participation as the core outcome domains for PD.

Rapid developments in sensor technology, data processing tools and data storage capability have helped fuel an increased appetite for equipment health monitoring in mechanical systems. As a result, the number of sensors and amount of data collected for health monitoring has grown tremendously. It is hoped that by collecting large quantities of operational data, predictive tools can be developed that will provide operational, maintenance and safety benefits. Data mining and machine learning techniques are important tools in addressing the ensuing challenge of extracting useful results from the data collected. In this work, the sensor data from a gas turbine system was analyzed with the objective of failure modeling and prediction. Previous efforts had used a two-class approach for this problem, to distinguish healthy and failed states of the system. In this work, a third class labelled as deteriorated data is added prior to each failure event to explore the ability of machine learning models to provide early warning of upcoming incidents. Several maintenance incidents were recorded by the sensor system in two separate vehicles. Three approaches to selecting training data were used. The first followed a traditional method of randomly selecting data points from all data according to a desired percentage of failed data to include in training, target ratios between failed and healthy data in each data set, as well as target ratios between training and testing data. The second data selection strategy was to consider data related to failure incidents as a whole and select certain incidents to include in training, and the remaining ones to be unseen in testing. The third approach was cross-validation which is typically used as a technique to evaluate how a classifier will perform on unseen data while still using the entirety of the data to train the final classifier. In addition to investigating training and data selection strategies, the effect of hyperparameter optimization was explored as well as the effect of varying the time period of the deteriorated class. Using the gas turbine data, which included 7 failure incidents and 76 predictor variables, a variety of classifier models of the system were developed in a three-class problem to differentiate healthy, deteriorated and failed system states. The classifier methods included support vector machines, Gaussian Naïve Bayes, random forest, adaboost, multilayer perceptron, k-nearest neighbor, and XG boost. Ensemble models were also created to leverage all the individual classifier models that were developed. This paper will describe the comprehensive results that were obtained using the various approaches and combinations, highlighting the respective benefits and limitations.