Intervention Delivery Matters: What Mothers at High Risk for Type 2 Diabetes Want in a Diabetes Prevention Program—Results from a Comparative Effectiveness Trial

Participants in the ENCOURAGE Healthy Families Study, a family-focused, modified Diabetes Prevention Program, reported challenges to and preferences for engaging in a diabetes prevention program. Challenges with flexible intervention delivery, accessibility, the traditional group-based format, and Coronavirus Disease 2019 (COVID-19) exposure risk can be mitigated by participant preferences for one-on-one, virtual/online intervention delivery.This work was supported by the JPB Foundation, New York, NY and the IUPUI Signature Center Initiative Fund. Sponsors did not contribute to the writing of this report or in the decision to submit the article for publication. The Journal’s Rapid Service Fee is funded by the University of Arizona Health Sciences Center for Border Health Disparities

Laboratory biomarkers associated with COVID-19 severity and management

The heterogeneous disease course of COVID-19 is unpredictable, ranging from mild self-limiting symptoms to cytokine storms, acute respiratory distress syndrome (ARDS), multi-organ failure and death. Identification of high-risk cases will enable appropriate intervention and escalation. This study investigates the routine laboratory tests and cytokines implicated in COVID-19 for their potential application as biomarkers of disease severity, respiratory failure and need of higher-level care. From analysis of 203 samples, CRP, IL-6, IL-10 and LDH were most strongly correlated with the WHO ordinal scale of illness severity, the fraction of inspired oxygen delivery, radiological evidence of ARDS and level of respiratory support (p ≤ 0.001). IL-6 levels of ≥3.27 pg/ml provide a sensitivity of 0.87 and specificity of 0.64 for a requirement of ventilation, and a CRP of ≥37 mg/l of 0.91 and 0.66. Reliable stratification of high-risk cases has significant implications on patient triage, resource management and potentially the initiation of novel therapies in severe patients

Trehalose induces autophagy via lysosomal-mediated TFEB activation in models of motoneuron degeneration

Macroautophagy/autophagy, a defense mechanism against aberrant stresses, in neurons counteracts aggregate-prone misfolded protein toxicity. Autophagy induction might be beneficial in neurodegenerative diseases (NDs). The natural compound trehalose promotes autophagy via TFEB (transcription factor EB), ameliorating disease phenotype in multiple ND models, but its mechanism is still obscure. We demonstrated that trehalose regulates autophagy by inducing rapid and transient lysosomal enlargement and membrane permeabilization (LMP). This effect correlated with the calcium-dependent phosphatase PPP3/calcineurin activation, TFEB dephosphorylation and nuclear translocation. Trehalose upregulated genes for the TFEB target and regulator Ppargc1a, lysosomal hydrolases and membrane proteins (Ctsb, Gla, Lamp2a, Mcoln1, Tpp1) and several autophagy-related components (Becn1, Atg10, Atg12, Sqstm1/p62, Map1lc3b, Hspb8 and Bag3) mostly in a PPP3- and TFEB-dependent manner. TFEB silencing counteracted the trehalose prodegradative activity on misfolded protein causative of motoneuron diseases. Similar effects were exerted by trehalase-resistant trehalose analogs, melibiose and lactulose. Thus, limited lysosomal damage might induce autophagy, perhaps as a compensatory mechanism, a process that is beneficial to counteract neurodegeneration

Defining Potential Therapeutic Targets in Coronavirus Disease 2019: A Cross-Sectional Analysis of a Single-Center Cohort

OBJECTIVES: Multiple mechanisms have been proposed to explain disease severity in coronavirus disease 2019. Therapeutic approaches need to be underpinned by sound biological rationale. We evaluated whether serum levels of a range of proposed coronavirus disease 2019 therapeutic targets discriminated between patients with mild or severe disease. DESIGN: A search of ClinicalTrials.gov identified coronavirus disease 2019 immunological drug targets. We subsequently conducted a retrospective observational cohort study investigating the association of serum biomarkers within the first 5 days of hospital admission relating to putative therapeutic biomarkers with illness severity and outcome. SETTING: University College London, a tertiary academic medical center in the United Kingdom. PATIENTS: Patients admitted to hospital with a diagnosis of coronavirus disease 2019. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Eighty-six patients were recruited, 44 (51%) with mild disease and 42 (49%) with severe disease. We measured levels of 10 cytokines/signaling proteins related to the most common therapeutic targets (granulocyte-macrophage colony-stimulating factor, interferon-α2a, interferon-β, interferon-γ, interleukin-1β, interleukin-1 receptor antagonist, interleukin-6, interleukin-7, interleukin-8, tumor necrosis factor-α), immunoglobulin G antibodies directed against either coronavirus disease 2019 spike protein or nucleocapsid protein, and neutralization titers of antibodies. Four-hundred seventy-seven randomized trials, including 168 different therapies against 83 different pathways, were identified. Six of the 10 markers (interleukin-6, interleukin-7, interleukin-8, interferon-α2a, interferon-β, interleukin-1 receptor antagonist) discriminated between patients with mild and severe disease, although most were similar or only modestly raised above that seen in healthy volunteers. A similar proportion of patients with mild or severe disease had detectable spike protein or nucleocapsid protein immunoglobulin G antibodies with equivalent levels between groups. Neutralization titers were higher among patients with severe disease. CONCLUSIONS: Some therapeutic and prognostic biomarkers may be useful in identifying coronavirus disease 2019 patients who may benefit from specific immunomodulatory therapies, particularly interleukin-6. However, biomarker absolute values often did not discriminate between patients with mild and severe disease or death, implying that these immunomodulatory treatments may be of limited benefit

A RAB5/RAB4 recycling circuitry induces a proteolytic invasive program and promotes tumor dissemination

The mechanisms by which tumor cells metastasize and the role of endocytic proteins in this process are not well understood. We report that overexpression of the GTPase RAB5A, a master regulator of endocytosis, is predictive of aggressive behavior and metastatic ability in human breast cancers. RAB5A is necessary and sufficient to promote local invasion and distant dissemination of various mammary and nonmammary tumor cell lines, and this prometastatic behavior is associated with increased intratumoral cell motility. Specifically, RAB5A is necessary for the formation of invadosomes, membrane protrusions specialized in extracellular matrix (ECM) degradation. RAB5A promotes RAB4- and RABENOSYN-5-dependent endo/exocytic cycles (EECs) of critical cargos (membrane-type 1 matrix metalloprotease [MT1-MMP] and \u3b23 integrin) required for invadosome formation in response to motogenic stimuli. This trafficking circuitry is necessary for spatially localized hepatocyte growth factor (HGF)/MET signaling that drives invasive, proteolysis-dependent chemotaxis in vitro and for conversion of ductal carcinoma in situ to invasive ductal carcinoma in vivo. Thus, RAB5A/RAB4 EECs promote tumor dissemination by controlling a proteolytic, mesenchymal invasive program

STEM education in the twenty-first century: learning at work-an exploration of design and technology teacher perceptions and practices

Teachers’ knowledge of STEM education, their understanding, and pedagogical application of that knowledge is intrinsically linked to the subsequent effectiveness of STEM delivery within their own practice; where a teacher’s knowledge and understanding is deficient, the potential for pupil learning is ineffective and limited. Set within the context of secondary age phase education in England and Wales (11–16 years old), this paper explores how teachers working within the field of design and technology education acquire new knowledge in STEM; how understanding is developed and subsequently embedded within their practice to support the creation of a diverse STEM-literate society. The purpose being to determine mechanisms by which knowledge acquisition occurs, to reconnoitre potential implications for education and learning at work, including consideration of the role which new technologies play in the development of STEM knowledge within and across contributory STEM subject disciplines. Underpinned by an interpretivist ontology, work presented here builds upon the premise that design and technology is an interdisciplinary educational construct and not viewed as being of equal status to other STEM disciplines including maths and science. Drawing upon the philosophical field of symbolic interactionism and constructivist grounded theory, work embraces an abductive methodology where participants are encouraged to relate design and technology within the context of STEM education. Emergent findings are discussed in relation to their potential to support teachers’ educational development for the advancement of STEM literacy, and help secure design and technology’s place as a subject of value within a twenty-first Century curriculum

Stochastic Model of the Still Water Bending Moment of Oil Tankers

In this paper a predictive model is adopted for quantifying the stochastic variability of the global static bending load acting on a tanker ship in sagging. The purpose of the investigation is to provide quantitative information on the uncertainties affecting the prediction of still water load effect to be possibly utilised in a reliability evaluation of the hull girder strength. The various sources of variability in bending loads are reviewed, then the attention is focussed on the influence of the uncertainties affecting the cargo weight distribution on board. Loading modes corresponding to uniform filling levels are analysed in particular, based on the note that such conditions are both the most frequent and those inducing the highest sagging moments. The loading process is simulated by a stochastic variation of the filling levels in the various tanks around the nominal values. The characteristics of the probability distributions for filling levels are derived from a specific analysis carried out on the detailed reports of two sister ships, compiled at the end of the loading process. These data reflect also geometrical and operational constraints of the specific ships. The fluctuation of filling levels represents a disturbance in input to the loading process that is partially controlled by means of a feed-back based on trim checks. The corresponding variations in the still water bending moment (SWBM) are identified, with retro-actions triggered by different levels of deviation from the predicted trim conditions. The advantages of the predictive procedure are seen in a direct modelling of physical quantities subjected to uncertainties and of the control process put in place by the crew, allowing a better understanding of the reasons for the variability of the bending loads. Further, the model allows to focus on a specific loading condition that can be adopted as reference situation for the structural checks. The results in terms of mean values and coefficients of variation are compared with those provided by other procedures proposed in literature and considerations are made on a possible improvement in the stochastic model of SWBM in reliability evaluations