To contain the COVID-19 pandemic, India imposed a national lockdown at the end of March 2020, a decision that resulted in a massive reverse migration as many workers across economic sectors returned ...to their home regions. Migrants provide the foundations of the agricultural workforce in the ‘breadbasket’ states of Punjab and Haryana in Northwest India.There are mounting concerns that near and potentially longer-term reductions in labor availability may jeopardize agricultural production and consequently national food security. The timing of rice transplanting at the beginning of the summer monsoon season has a cascading influence on productivity of the entire rice-wheat cropping system. To assess the potential for COVID-related reductions in the agriculture workforce to disrupt production of the dominant rice-wheat cropping pattern in these states, we use a spatial ex ante modelling framework to evaluate four scenarios representing a range of plausible labor constraints on the timing of rice transplanting. Averaged over both states, results suggest that rice productivity losses under all delay scenarios would be low as compare to those for wheat, with total system productivity loss estimates ranging from 9%, to 21%, equivalent to economic losses of USD $674 m to $1.48 billion. Late rice transplanting and harvesting can also aggravate winter air pollution with concomitant health risks. Technological options such as direct seeded rice, staggered nursery transplanting, and crop diversification away from rice can help address these challenges but require new approaches to policy and incentives for change.
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•An ex-ante analysis was done using geospatial tools on potential effect of labour shortage on rice-wheat system.•Food grain production loss due to labor shortage can be 23% from current levels of production.•Residue burning will exacerbate air pollution in winter and could coincide with an anticipated COVID resurgence in the fall.•India needs new strategies to use available technological and management innovations to address emerging constraints.
We apply an online optimization process based on machine learning to the production of Bose-Einstein condensates (BEC). BEC is typically created with an exponential evaporation ramp that is optimal ...for ergodic dynamics with two-body s-wave interactions and no other loss rates, but likely sub-optimal for real experiments. Through repeated machine-controlled scientific experimentation and observations our 'learner' discovers an optimal evaporation ramp for BEC production. In contrast to previous work, our learner uses a Gaussian process to develop a statistical model of the relationship between the parameters it controls and the quality of the BEC produced. We demonstrate that the Gaussian process machine learner is able to discover a ramp that produces high quality BECs in 10 times fewer iterations than a previously used online optimization technique. Furthermore, we show the internal model developed can be used to determine which parameters are essential in BEC creation and which are unimportant, providing insight into the optimization process of the system.
Background
About half of twin pregnancies deliver preterm, and it is unclear whether any intervention reduces this risk.
Objectives
To assess the evidence for the effectiveness of progesterone, ...cerclage, and pessary in twin pregnancies.
Search strategy
We searched Medline, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials, and ISI Web of Science, without language restrictions, up to 25 January 2016.
Selection criteria
Randomised controlled trials of progesterone, cerclage, or pessary for preventing preterm birth in women with twin pregnancies, without symptoms of threatened preterm labour.
Data collection and analysis
Two independent reviewers extracted data using a piloted form. Study quality was appraised with the Cochrane Risk of Bias tool. We performed pairwise inverse variance random‐effects meta‐analyses.
Main results
We included 23 trials (all but three were considered to have a low risk of bias) comprising 6626 women with twin pregnancies. None of the interventions significantly reduced the risk of preterm birth overall at <34 or <37 weeks of gestation, or neonatal death, our primary outcomes, compared to a control group. In women receiving vaginal progesterone, the relative risk (RR) of preterm birth <34 weeks of gestation was 0.82 (95% CI 0.64–1.05, seven studies, I2 36%), with a significant reduction in some key secondary outcomes, including very low birthweight (<1500 g, RR 0.71, 95% CI 0.52–0.98, four studies, I2 46%) and mechanical ventilation (RR 0.61, 95% CI 0.45–0.82, four studies, I2 22%).
Conclusion
In twin gestations, although no overarching intervention was beneficial for the prevention of preterm birth and its sequelae, vaginal progesterone improved some important secondary outcomes.
Tweetable
Vaginal progesterone may be beneficial in twin pregnancies, but not 17‐OHPC, cerclage, or pessary.
Tweetable
Vaginal progesterone may be beneficial in twin pregnancies, but not 17‐OHPC, cerclage, or pessary.
Objective
Post‐traumatic stress disorder (PTSD) is common in Veterans. Symptoms can perpetuate into late life, negatively impacting physical and mental health. Exercise and social support are ...beneficial in treating anxiety disorders such as PTSD in the general population, although less is known about the impact on Veterans who have lived with PTSD for decades. This study assessed associations between social connectedness, physical function and self‐reported change in PTSD symptoms among older Veterans specifically participating in Gerofit.
Design
Prospective clinical intervention.
Setting
Twelve sites of Veterans Affairs (VA) Gerofit exercise program across the United States.
Participants
Three hundred and twenty one older Veteran Gerofit participants (mean age = 74) completed physical assessments and questionnaires regarding physical and emotional symptoms and their experience.
Measurements
Measures of physical function, including 30‐second chair stands, 10‐m and 6‐min walk were assessed at baseline and 3 months; change in PTSD symptoms based on the Diagnostic Statistical Manual—5 (DSM‐5) assessed by a self‐report questionnaire; and social connection measured by the Relatedness Subscale of the Psychological Need Satisfaction in Exercise scale (PNSE) were evaluated after 3 months of participation in Gerofit.
Results
Ninety five (29.6%) Veterans reported PTSD. Significant improvement was noted in self‐rated PTSD symptoms at 3 months (P < .05). Moderate correlation (r = .44) was found between social connectedness with other participants in Gerofit and PTSD symptom improvement for those Veterans who endorsed improvement (n = 59). All participants improved on measures of physical function. In Veterans who endorsed PTSD there were no significant associations between physical function improvement and PTSD symptoms.
Conclusion
Veterans with PTSD that participated in Gerofit group exercise reported symptom improvement, and social connectedness was significantly associated with this improvement. In addition to physical health benefits, the social context of Gerofit may offer a potential resource for improving PTSD symptoms in older Veterans that warrants further study.
Little is known about how leukemia cells alter the bone marrow (BM) niche to facilitate their own growth and evade chemotherapy. Here, we provide evidence that acute myeloid leukemia (AML) blasts ...remodel the BM niche into a leukemia growth-permissive and normal hematopoiesis-suppressive microenvironment through exosome secretion. Either engrafted AML cells or AML-derived exosomes increased mesenchymal stromal progenitors and blocked osteolineage development and bone formation in vivo. Preconditioning with AML-derived exosomes 'primed' the animals for accelerated AML growth. Conversely, disruption of exosome secretion in AML cells through targeting Rab27a, an important regulator involved in exosome release, significantly delayed leukemia development. In BM stromal cells, AML-derived exosomes induced the expression of DKK1, a suppressor of normal hematopoiesis and osteogenesis, thereby contributing to osteoblast loss. Conversely, treatment with a DKK1 inhibitor delayed AML progression and prolonged survival in AML-engrafted mice. In addition, AML-derived exosomes induced a broad downregulation of hematopoietic stem cell-supporting factors (for example, CXCL12, KITL and IGF1) in BM stromal cells and reduced their ability to support normal hematopoiesis. Altogether, this study uncovers novel features of AML pathogenesis and unveils how AML cells create a self-strengthening leukemic niche that promotes leukemic cell proliferation and survival, while suppressing normal hematopoiesis through exosome secretion.
Bayesian Belief Networks (BBNs) are being increasingly used to develop a range of predictive models and risk assessments for ecological systems. Ecological BBNs can be applied to complex catchment ...and water quality issues, integrating multiple spatial and temporal variables within social, economic and environmental decision making processes. This paper reviews the essential components required for ecologists to design a best-practice predictive BBN in an ecological risk assessment (ERA) framework for aquatic ecosystems, outlining: (1) how to create a BBN for an aquatic ERA?; (2) what are the challenges for aquatic ecologists in adopting the best-practice applications of BBNs to ERAs?; and (3) how can BBNs in ERAs influence the science/management interface into the future? The aims of this paper are achieved using three approaches. The first is to demonstrate the best-practice development of BBNs in aquatic sciences using a simple nutrient model. The second is to discuss the limitations and challenges aquatic ecologists encounter when applying BBNs to ERAs. The third is to provide a framework for integrating best-practice BBNs into ERAs and the management of aquatic ecosystems. A quantitative review of the application and development of BBNs in aquatic science from 2002 to 2014 was conducted to identify areas where continued best-practice development is required. We outline a best-practice framework for the integration of BBNs into ERAs and study of complex aquatic systems.
•An overview for creating a Bayesian Belief Network (BBN) is presented.•Potential solutions for challenges using Bayesian Belief Networks are reported.•A meta-analysis of Bayesian Belief Networks published in aquatic science presented.•The best-practice principles underpinning Bayesian Belief Networks are discussed.•A framework is proposed to advance the management of ecosystems using networks.
ONC201 is a first-in-class imipridone molecule currently in clinical trials for the treatment of multiple cancers. Despite enormous clinical potential, the mechanism of action is controversial. To ...investigate the mechanism of ONC201 and identify compounds with improved potency, we tested a series of novel ONC201 analogues (TR compounds) for effects on cell viability and stress responses in breast and other cancer models. The TR compounds were found to be ∼50–100 times more potent at inhibiting cell proliferation and inducing the integrated stress response protein ATF4 than ONC201. Using immobilized TR compounds, we identified the human mitochondrial caseinolytic protease P (ClpP) as a specific binding protein by mass spectrometry. Affinity chromatography/drug competition assays showed that the TR compounds bound ClpP with ∼10-fold higher affinity compared to ONC201. Importantly, we found that the peptidase activity of recombinant ClpP was strongly activated by ONC201 and the TR compounds in a dose- and time-dependent manner with the TR compounds displaying a ∼10–100 fold increase in potency over ONC201. Finally, siRNA knockdown of ClpP in SUM159 cells reduced the response to ONC201 and the TR compounds, including induction of CHOP, loss of the mitochondrial proteins (TFAM, TUFM), and the cytostatic effects of these compounds. Thus, we report that ClpP directly binds ONC201 and the related TR compounds and is an important biological target for this class of molecules. Moreover, these studies provide, for the first time, a biochemical basis for the difference in efficacy between ONC201 and the TR compounds.
Auger processes involving the filling of holes in the valence band are thought to make important contributions to the low-energy photoelectron and secondary electron spectrum from many solids. ...However, measurements of the energy spectrum and the efficiency with which electrons are emitted in this process remain elusive due to a large unrelated background resulting from primary beam-induced secondary electrons. Here, we report the direct measurement of the energy spectra of electrons emitted from single layer graphene as a result of the decay of deep holes in the valence band. These measurements were made possible by eliminating competing backgrounds by employing low-energy positrons (<1.25 eV) to create valence-band holes by annihilation. Our experimental results, supported by theoretical calculations, indicate that between 80 and 100% of the deep valence-band holes in graphene are filled via an Auger transition.
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