Perceptions of Treatment Plan Goals of People in Psychiatric Rehabilitation

Collaborative treatment planning is a process by which providers and consumers work together to set goals for treatment, choose between alternative services, and establish a plan. Research has not examined consumers’ views of their treatment plan goals. The present study examined ways in which consumers react to their treatment plan goals. Twenty-one interviews with Veterans engaged in psychiatric rehabilitation regarding goals listed in their treatment plan were analyzed using inductive content analysis. Reactions to treatment plan goals are reported. Analyses indicate people do not vary in a linear degree regarding agreement with treatment plan goals. Clinicians and researchers should examine the extent to which treatment plan goals are consistent with the consumer’s personal goals and self-concept

Maternal and perinatal factors associated with the human milk microbiome

Microbes are present in human milk regardless of the mother's health. The origins of the milk microbiota likely include the mother's skin, infant's mouth, and transfer from the maternal gastrointestinal (GI) tract. Prominent bacterial taxa in human milk are Staphylococcus and Streptococcus, but many other genera are also found including anaerobic Lactobacillus, Bifidobacterium, and Bacteroides. The milk microbiome is highly variable and potentially influenced by geographic location, delivery mode, time postpartum, feeding mode, social networks, environment, maternal diet, and milk composition. Mastitis alters the milk microbiome, and the intake of Lactobacilli has shown potential for mastitis treatment and prevention. Although milk and infant fecal microbiomes are different, their variations appear to be related – suggesting that milk is an important contributor of early GI colonization. Nonetheless, nothing is known regarding whether the milk microbiome influences infant health. Further research and clinical interventions are needed to determine if changes in the microbiomes of human milk and infant formula/food impact health.</p

Rising arterial stiffness with accumulating comorbidities associates with heart failure with preserved ejection fraction

Aims: Comorbidities play a significant role towards the pathophysiology of heart failure with preserved ejection fraction (HFpEF), characterized by abnormal macrovascular function and altered ventricular–vascular coupling. However, our understanding of the role of comorbidities and arterial stiffness in HFpEF remains incomplete. We hypothesized that HFpEF is preceded by a cumulative rise in arterial stiffness as cardiovascular comorbidities accumulate, beyond that associated with ageing. Methods and results: Arterial stiffness was assessed using pulse wave velocity (PWV) in five groups: Group A, healthy volunteers (n = 21); Group B, patients with hypertension (n = 21); Group C, hypertension and diabetes mellitus (n = 20); Group D, HFpEF (n = 21); and Group E, HF with reduced ejection fraction (HFrEF) (n = 11). All patients were aged 70 and above. Mean PWV increased from Groups A to D (PWV 10.2, 12.2, 13.0, and 13.7 m/s, respectively) as vascular comorbidities accumulated independent of age, renal function, haemoglobin, obesity (body mass index), smoking status, and hypercholesterolaemia. HFpEF exhibited the highest PWV and HFrEF displayed near‐normal levels (13.7 vs. 10 m/s, P = 0.003). PWV was inversely related to peak oxygen consumption (r = −0.304, P = 0.03) and positively correlated with left ventricular filling pressures (E/e′) on echocardiography (r = −0.307, P = 0.014). Conclusions: This study adds further support to the concept of HFpEF as a disease of the vasculature, underlined by an increasing arterial stiffness that is driven by vascular ageing and accumulating vascular comorbidities, for example, hypertension and diabetes. Reflecting a pulsatile arterial afterload associated with diastolic dysfunction and exercise capacity, PWV may provide a clinically relevant tool to identify at‐risk intermediate phenotypes (e.g. pre‐HFpEF) before overt HFpEF occurs

Ecologies, synergies, and biological systems shaping human milk composition—a report from “Breastmilk Ecology: Genesis of Infant Nutrition (BEGIN)” Working Group 2

Human milk is universally recognized as the preferred food for infants during the first 6 mo of life because it provides not only essential and conditionally essential nutrients in necessary amounts but also other biologically active components that are instrumental in protecting, communicating important information to support, and promoting optimal development and growth in infants. Despite decades of research, however, the multifaceted impacts of human milk consumption on infant health are far from understood on a biological or physiological basis. Reasons for this lack of comprehensive knowledge of human milk functions are numerous, including the fact that milk components tend to be studied in isolation, although there is reason to believe that they interact. In addition, milk composition can vary greatly within an individual as well as within and among populations. The objective of this working group within the Breastmilk Ecology: Genesis of Infant Nutrition (BEGIN) Project was to provide an overview of human milk composition, factors impacting its variation, and how its components may function to coordinately nourish, protect, and communicate complex information to the recipient infant. Moreover, we discuss the ways whereby milk components might interact such that the benefits of an intact milk matrix are greater than the sum of its parts. We then apply several examples to illustrate how milk is better thought of as a biological system rather than a more simplistic “mixture” of independent components to synergistically support optimal infant health

Respiratory plasticity in response to changes in oxygen supply and demand

Aerobic organisms maintain O2 homeostasis by responding to changes in O2 supply and demand in both short and long time domains. In this review, we introduce several specific examples of respiratory plasticity induced by chronic changes in O2 supply (environmental hypoxia or hyperoxia) and demand (exercise-induced and temperature-induced changes in aerobic metabolism). These studies reveal that plasticity occurs throughout the respiratory system, including modifications to the gas exchanger, respiratory pigments, respiratory muscles, and the neural control systems responsible for ventilating the gas exchanger. While some of these responses appear appropriate (e.g., increases in lung surface area, blood O2 capacity, and pulmonary ventilation in hypoxia), other responses are potentially harmful (e.g., increased muscle fatigability). Thus, it may be difficult to predict whole-animal performance based on the plasticity of a single system. Moreover, plastic responses may differ quantitatively and qualitatively at different developmental stages. Much of the current research in this field is focused on identifying the cellular and molecular mechanisms underlying respiratory plasticity. These studies suggest that a few key molecules, such as hypoxia inducible factor (HIF) and erythropoietin, may be involved in the expression of diverse forms of plasticity within and across species. Studying the various ways in which animals respond to respiratory challenges will enable a better understanding of the integrative response to chronic changes in O2 supply and deman

What's normal? Oligosaccharide concentrations and profiles in milk produced by healthy women vary geographically.

Background: Human milk is a complex fluid comprised of myriad substances, with one of the most abundant substances being a group of complex carbohydrates referred to as human milk oligosaccharides (HMOs). There has been some evidence that HMO profiles differ in populations, but few studies have rigorously explored this variability.Objectives: We tested the hypothesis that HMO profiles differ in diverse populations of healthy women. Next, we examined relations between HMO and maternal anthropometric and reproductive indexes and indirectly examined whether differences were likely related to genetic or environmental variations.Design: In this cross-sectional, observational study, milk was collected from a total of 410 healthy, breastfeeding women in 11 international cohorts and analyzed for HMOs by using high-performance liquid chromatography.Results: There was an effect of the cohort (P 4 times higher in milk collected in Sweden than in milk collected in rural Gambia (mean ± SEM: 473 ± 55 compared with 103 ± 16 nmol/mL, respectively; P < 0.05), and disialyllacto-N-tetraose (DSLNT) concentrations ranged from 216 ± 14 nmol/mL (in Sweden) to 870 ± 68 nmol/mL (in rural Gambia) (P < 0.05). Maternal age, time postpartum, weight, and body mass index were all correlated with several HMOs, and multiple differences in HMOs [e.g., lacto-N-neotetrose and DSLNT] were shown between ethnically similar (and likely genetically similar) populations who were living in different locations, which suggests that the environment may play a role in regulating the synthesis of HMOs.Conclusions: The results of this study support our hypothesis that normal HMO concentrations and profiles vary geographically, even in healthy women. Targeted genomic analyses are required to determine whether these differences are due at least in part to genetic variation. A careful examination of sociocultural, behavioral, and environmental factors is needed to determine their roles in this regard. This study was registered at clinicaltrials.gov as NCT02670278

Enabling Space Exploration Medical System Development Using a Tool Ecosystem

The NASA Human Research Program's (HRP) Exploration Medical Capability (ExMC) Element is utilizing a Model Based Systems Engineering (MBSE) approach to enhance the development of systems engineering products that will be used to advance medical system designs for exploration missions beyond Low Earth Orbit. In support of future missions, the team is capturing content such as system behaviors, functional decompositions, architecture, system requirements and interfaces, and recommendations for clinical capabilities and resources in Systems Modeling Language (SysML) models. As these products mature, SysML models provide a way for ExMC to capture relationships among the various products, which includes supporting more integrated and multi-faceted views of future medical systems. In addition to using SysML models, HRP and ExMC are developing supplementary tools to support two key functions: 1) prioritizing current and future research activities for exploration missions in an objective manner; and 2) enabling risk-informed and evidence-based trade space analysis for future space vehicles, missions, and systems. This paper will discuss the long-term HRP and ExMC vision for the larger ecosystem of tools, which include dynamic Probabilistic Risk Assessment (PRA) capabilities, additional SysML models, a database of system component options, and data visualizations. It also includes a review of an initial Pilot Project focused on enabling medical system trade studies utilizing data that is coordinated across tools for consistent outputs (e.g., mission risk metrics that are associated with medical system mass values and medical conditions addressed). This first Pilot Project demonstrated successful operating procedures and integration across tools. Finally, the paper will also cover a second Pilot Project that utilizes tool enhancements such as medical system optimization capabilities, post-processing, and visualization of generated data for subject matter expert review, and increased integration amongst the tools themselves

High Throughput Interrogation of Somatic Mutations in High Grade Serous Cancer of the Ovary

BACKGROUND:Epithelial ovarian cancer is the most lethal of all gynecologic malignancies, and high grade serous ovarian cancer (HGSC) is the most common subtype of ovarian cancer. The objective of this study was to determine the frequency and types of point somatic mutations in HGSC using a mutation detection protocol called OncoMap that employs mass spectrometric-based genotyping technology. METHODOLOGY/PRINCIPAL FINDINGS:The Center for Cancer Genome Discovery (CCGD) Program at the Dana-Farber Cancer Institute (DFCI) has adapted a high-throughput genotyping platform to determine the mutation status of a large panel of known cancer genes. The mutation detection protocol, termed OncoMap has been expanded to detect more than 1000 mutations in 112 oncogenes in formalin-fixed paraffin-embedded (FFPE) tissue samples. We performed OncoMap on a set of 203 FFPE advanced staged HGSC specimens. We isolated genomic DNA from these samples, and after a battery of quality assurance tests, ran each of these samples on the OncoMap v3 platform. 56% (113/203) tumor samples harbored candidate mutations. Sixty-five samples had single mutations (32%) while the remaining samples had ≥ 2 mutations (24%). 196 candidate mutation calls were made in 50 genes. The most common somatic oncogene mutations were found in EGFR, KRAS, PDGRFα, KIT, and PIK3CA. Other mutations found in additional genes were found at lower frequencies (<3%). CONCLUSIONS/SIGNIFICANCE:Sequenom analysis using OncoMap on DNA extracted from FFPE ovarian cancer samples is feasible and leads to the detection of potentially druggable mutations. Screening HGSC for somatic mutations in oncogenes may lead to additional therapies for this patient population

Comparison of Two Approaches for the Metataxonomic Analysis of the Human Milk Microbiome.

Recent work has demonstrated the existence of large inter-individual and inter-population variability in the microbiota of human milk from healthy women living across variable geographical and socio-cultural settings. However, no studies have evaluated the impact that variable sequencing approaches targeting different 16S rRNA variable regions may have on the human milk microbiota profiling results. This hampers our ability to make meaningful comparisons across studies. In this context, the main purpose of the present study was to re-process and re-sequence the microbiome in a large set of human milk samples (n = 412) collected from healthy women living at diverse international sites (Spain, Sweden, Peru, United States, Ethiopia, Gambia, Ghana and Kenya), by targeting a different 16S rRNA variable region and reaching a larger sequencing depth. Despite some differences between the results obtained from both sequencing approaches were notable (especially regarding alpha and beta diversities and Proteobacteria representation), results indicate that both sequencing approaches revealed a relatively consistent microbiota configurations in the studied cohorts. Our data expand upon the milk microbiota results we previously reported from the INSPIRE cohort and provide, for the first time across globally diverse populations, evidence of the impact that different DNA processing and sequencing approaches have on the microbiota profiles obtained for human milk samples. Overall, our results corroborate some similarities regarding the microbial communities previously reported for the INSPIRE cohort, but some differences were also detected. Understanding the impact of different sequencing approaches on human milk microbiota profiles is essential to enable meaningful comparisons across studies. Clinical Trial Registration: www.clinicaltrials.gov, identifier NCT02670278