Connection and disconnection as predictors of mental health and wellbeing

Despite the established literature on connection to others, and burgeoning research on self-connection, researchers have paid little attention to the equivalent experiences of disconnection that people can experience in their everyday lives. The current research examined connection and disconnection from oneself and others. Specifically, across two studies, participants listed up to twenty words or phrases that they experienced related to each form of (dis)connection. Study 1 focused on how these affected participants’ mental health (i.e. anxiety and depression), while study 2 examined positive forms of wellbeing (i.e., flourishing and life satisfaction). Results suggested that increased mental health was most strongly related to a greater experience of connection to others. Flourishing also increased as one’s experience of other-connection increased. By contrast, poorer wellbeing was related to a greater experience of disconnection from others. Finally, life satisfaction decreased when participants experienced greater self-disconnection. In all, these findings provide an initial test of and support for the continued examination of various forms of both connection and disconnection

Low energy supersymmetry from R-symmetries

In a generic setting of Wess-Zumino models, we prove that the existence of a supersymmetric vacuum with a vanishing superpotential can be a consequence of a continuous or discrete R-symmetry when invariant fields are not less than fields transforming in the same way as the superpotential under the R-symmetry. The realization in string theory is discussed. We show that a rich landscape of low energy supersymmetric vacua can be found in the Type IIB flux compactification setup ready for the KKLT construction of de Sitter vacua in string theory.Comment: 5 pages; v2: typos, add references; v3: major revision, add WCP4 hypersurface example, add references, published versio

An image-based modeling framework for predicting spatiotemporal brain cancer biology within individual patients

Imaging is central to the clinical surveillance of brain tumors yet it provides limited insight into a tumor\u27s underlying biology. Machine learning and other mathematical modeling approaches can leverage paired magnetic resonance images and image-localized tissue samples to predict almost any characteristic of a tumor. Image-based modeling takes advantage of the spatial resolution of routine clinical scans and can be applied to measure biological differences within a tumor, changes over time, as well as the variance between patients. This approach is non-invasive and circumvents the intrinsic challenges of inter- and intratumoral heterogeneity that have historically hindered the complete assessment of tumor biology and treatment responsiveness. It can also reveal tumor characteristics that may guide both surgical and medical decision-making in real-time. Here we describe a general framework for the acquisition of image-localized biopsies and the construction of spatiotemporal radiomics models, as well as case examples of how this approach may be used to address clinically relevant questions

The effect of bisphosphonate treatment on the biochemical and cellular events during bone remodelling in response to microinjury stimulation.

Osteoporosis is one of the most prevalent bone diseases worldwide and is characterised by high levels of bone turnover, a marked loss in bone mass and accumulation of microdamage, which leads to an increased fracture incidence that places a huge burden on global health care systems. Bisphosphonates have been used to treat osteoporosis and have shown great success in conserving bone mass and reducing fracture incidence. In spite of the existing knowledge of the in vivo responses of bone to bisphosphonates, the cellular responses to these drugs have yet to be fully elucidated. In vitro model systems that allow the decoupling of complex highly integrated events, such as bone remodelling, provide a tool whereby these biological processes may be studied in a more simplified context. This study firstly utilised an in vitro model system of bone remodelling and comprising all three major cell types of the bone (osteocytes, osteoclasts and osteoblasts), which was representative of the bone\u27s capacity to sense microdamage and subsequently initiate a basic multicellular unit response. Secondly, this system was used to study the effect of two commonly utilised aminobisphosphonate treatments for osteoporosis, alendronate and zoledronate. We demonstrated that microinjury to osteocyte networks being treated with bisphosphonates modulates receptor activator of nuclear factor kappa-B ligand and osteoprotegerin activity, and subsequently osteoclastogenesis. Furthermore, bisphosphonates increased the osteogenic potential following microinjury. Thus, we have shown for the first time that bisphosphonates act at all three stages of bone remodelling, from microinjury to osteoclastogenesis and ultimately osteogenesis