Genetic stability of Brucella abortus S19 and RB51 vaccine strains by multiple locus variable number tandem repeat analysis (MLVA16)

The aims of the present study were (i) to assess the in vitro genetic stability of S19 and RB51 Brucella abortus vaccines strains and (ii) to evaluate the ability of multiple-locus variable-number tandem repeat (VNTR) analysis (MLVA) as a tool to be used in the quality control of live vaccines against brucellosis. Sixty-three batches of commercial S19 (n = 53) and RB51 (n = 10) vaccines, produced between 2006 and 2009, were used in this study. S19 and RB51 vaccines were obtained from, respectively, seven and two different manufacturers. Ten in vitro serial passages were performed on reference strains and on selected batches of commercial vaccines. All batches, reference strains and strains of serial passages were typed by the MLVA16. The results demonstrated that B. abortus S19 and RB51 vaccine strains are genetically stable and very homogeneous in their respective groups. Anyway, batches of S19 from one manufacturer and batches of RB51 from another presented genotypes distincts from the reference vaccine strains. In both cases, differences were found on locus Bruce07, which had addition of one repeat unit in the case of S19 batches and the deletion of one repeat unit in the case of RB51 batches. In summary, MLVA16 proved to be a molecular tool capable of discriminating small genomic variations and should be included in in vitro official tests.     

Are computational applications the “crystal ball” in the IVF laboratory? The evolution from mathematics to artificial intelligence

Mathematics rules the world of science. Innovative technologies based on mathematics have paved the way for implementation of novel strategies in assisted reproduction. Ascertaining efficient embryo selection in order to secure optimal pregnancy rates remains the focus of the in vitro fertilization scientific community and the strongest driver behind innovative approaches. This scoping review aims to describe and analyze complex models based on mathematics for embryo selection, devices, and software most widely employed in the IVF laboratory and algorithms in the service of the cutting-edge technology of artificial intelligence. Despite their promising nature, the practicing embryologist is the one ultimately responsible for the success of the IVF laboratory and thus the one to approve embracing pioneering technologies in routine practice. Applied mathematics and computational biology have already provided significant insight into the selection of the most competent preimplantation embryo. This review describes the leap of evolution from basic mathematics to bioinformatics and investigates the possibility that computational applications may be the means to foretell a promising future for the IVF clinical practice.     

The Spoke-Hub-and-Node Model of Integrated Heart Failure Care

Heart failure (HF) is a significant public health concern. Specialized HF clinics provide the optimal environment to address the complex needs of these patients and improve outcomes. The current and growing population of patients with HF outstrips the ability of these clinics to deliver care. Integrated care is defined as health services that are managed and delivered so that people receive a seamless continuum of health promotion, disease prevention, diagnosis, treatment, disease management, rehabilitation, and palliative care services. This approach requires coordination across different levels and sites of care within and beyond the health sector, according to changing patient needs throughout their lives. The spoke-hub-and-node (SHN) model represents an organization of care that works collaboratively with the primary care sector and is highly integrated with community-based multidisciplinary teams of health care professionals and specialty care. The purpose of this article is to analyze the requirements for successful implementation of SHN models. We consider the respective roles of HF clinics, HF nurse specialists, pharmacists, palliative care teams, telemonitoring, and solo practitioners. We also discuss levels of care delivery and the importance of patient stratification and patient flow. The SHN approach has the potential to build on and improve the chronic care model (CCM) to deliver centralized services to preserve high-quality patient-centred care at affordable costs.     

The heavy price of conversion from laparoscopic to open procedures for emergent cholecystectomies

Background

Laparoscopic cholecystectomy (LC) is the standard operative intervention for gallbladder disease. Complications may necessitate conversion to an open cholecystectomy (OC). This study aims to determine the cost-consequences of laparoscopic-to-open conversion using a nationally-representative sample.

Addressing Methodologic Challenges and Minimizing Threats to Validity in Synthesizing Findings from Individual-Level Data Across Longitudinal Randomized Trials

Integrative Data Analysis (IDA) encompasses a collection of methods for data synthesis that pools participant-level data across multiple studies. Compared with single-study analyses, IDA provides larger sample sizes, better representation of participant characteristics, and often increased statistical power. Many of the methods currently available for IDA have focused on examining developmental changes using longitudinal observational studies employing different measures across time and study. However, IDA can also be useful in synthesizing across multiple randomized clinical trials to improve our understanding of the comprehensive effectiveness of interventions, as well as mediators and moderators of those effects. The pooling of data from randomized clinical trials presents a number of methodological challenges, and we discuss ways to examine potential threats to internal and external validity. Using as an illustration a synthesis of 19 randomized clinical trials on the prevention of adolescent depression, we articulate IDA methods that can be used to minimize threats to internal validity, including (1) heterogeneity in the outcome measures across trials, (2) heterogeneity in the follow-up assessments across trials, (3) heterogeneity in the sample characteristics across trials, (4) heterogeneity in the comparison conditions across trials, and (5) heterogeneity in the impact trajectories. We also demonstrate a technique for minimizing threats to external validity in synthesis analysis that may result from non-availability of some trial datasets. The proposed methods rely heavily on latent variable modeling extensions of the latent growth curve model, as well as missing data procedures. The goal is to provide strategies for researchers considering IDA.