3,387 research outputs found

    Cariology Clinical Trials:What Are We-and What Should We Be-Looking At?

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    Randomized control trial (RCT) methodology has compared interventions for the prevention and management of dental caries since the late 1960s. Despite almost 50 years and evidence of significant wastage within the wider biomedical research field, there has been little investigation into what works well and where weaknesses lie. This paper aims to draw attention to areas for improvement within cariology clinical trial methodology by summarizing systematic reviews on interventions and outcomes, and using examples to illustrate some challenges with intervention delivery fidelity, outcome analyses, and intervention co-production. Trial design stage choices are critical to ensure that optimum information is obtained when testing interventions. Intervention choice, outcome choice, and analyses are particularly important, and cariology trials have specific issues associated with them. A systematic search and review of cariology RCTs found 650 RCT reports. Social Network Analysis of interventions revealed a high degree of separation between prevention and management trials, gaps in clinically important comparisons, and a tendency for there to be comparisons within groups; e.g., comparison of interventions within the same, rather than different, levels of invasiveness. Outcomes measured for the same trial reports show: a focus on restoration performance and individual/population caries burden; the growing use of carious lesion activity and economic-related outcomes; and sparse, although an increase in the use of, patient-reported/patient-centered outcomes. Fidelity of adherence to complex interventions can be challenging to measure but is important in interpreting trial findings. Involving target populations in intervention design, delivery, and relating it to the planned rollout, are opportunities to ensure intervention relevance and improved uptake. Outcomes analyses should consider the minimum clinically important differences and outcome relevance measures for the target population. Factors underlying trialistsā€™ comparator and outcome choices need to be identified, and there is a need to ensure that a minimum dataset of outcomes allow for combination and comparisons of trial data for systematic review

    Planning and control for microassembly of structures composed of stress-engineered MEMS microrobots

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    We present control strategies that implement planar microassembly using groups of stress-engineered MEMS microrobots (MicroStressBots) controlled through a single global control signal. The global control signal couples the motion of the devices, causing the system to be highly underactuated. In order for the robots to assemble into arbitrary planar shapes despite the high degree of underactuation, it is desirable that each robot be independently maneuverable (independently controllable). To achieve independent control, we fabricated robots that behave (move) differently from one another in response to the same global control signal. We harnessed this differentiation to develop assembly control strategies, where the assembly goal is a desired geometric shape that can be obtained by connecting the chassis of individual robots. We derived and experimentally tested assembly plans that command some of the robots to make progress toward the goal, while other robots are constrained to remain in small circular trajectories (orbits) until it is their turn to move into the goal shape. Our control strategies were tested on systems of fabricated MicroStressBots. The robots are 240ā€“280 Āµm Ɨ 60 Āµm Ɨ 7ā€“20 Āµm in size and move simultaneously within a single operating environment. We demonstrated the feasibility of our control scheme by accurately assembling five different types of planar microstructures

    Precision medicine for suicidality: from universality to subtypes and personalization

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    Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a ā€˜liquid biopsyā€™ approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator

    Leibniz, Acosmism, and Incompossibility

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    Leibniz claims that God acts in the best possible way, and that this includes creating exactly one world. But worlds are aggregates, and aggregates have a low degree of reality or metaphysical perfection, perhaps none at all. This is Leibnizā€™s tendency toward acosmism, or the view that there this no such thing as creation-as-a-whole. Many interpreters reconcile Leibnizā€™s acosmist tendency with the high value of worlds by proposing that God sums the value of each substance created, so that the best world is just the world with the most substances. I call this way of determining the value of a world the Additive Theory of Value (ATV), and argue that it leads to the current and insoluble form of the problem of incompossibility. To avoid the problem, I read ā€œpossible worldsā€ in ā€œGod chooses the best of all possible worldsā€ as referring to Godā€™s ideas of worlds. These ideas, though built up from essences, are themselves unities and so well suited to be the value bearers that Leibnizā€™s theodicy requires. They have their own value, thanks to their unity, and that unity is not preserved when more essences are added

    Investigation of sidewall cracking in PMMA LIGA structures

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    During x-ray exposure in the LIGA process, the polymethylmethacrylate (PMMA) photoresist undergoes chain scission, which reduces the molecular weight of the exposed materials. Under some exposure and development conditions, sidewall cracking is observed on the PMMA sidewall, creating surface texture that is undesirable. In this research, exposed and developed PMMA sidewalls were examined for evidence of crack formation using optical profilometry. PMMA thickness, exposure dose and delay time between the end of exposure and beginning of development were varied. Our analysis of samples, with three different radiation doses and four different delay times from the end of exposure to the beginning of development, indicate that the first occurrence of cracking and the extent of cracking are affected by both the dose and the development delay time. This work includes the examination of the depth of cracks into the PMMA, distance between cracks, the width of cracks and the relationship between crack occurrence and dose profile. An empirical predictive model to correlate the delay time to the observance of sidewall cracking based on the deposited dose is presented. This information has direct implication for predicting processing conditions and logistics for LIGA fabricated parts.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/49050/2/jmm6_7_010.pd
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