Integrating physiological threshold experiments with climate modeling to project mangrove species’ range expansion

Predictions of climate-related shifts in species ranges have largely been based on correlative models. Due to limitations of these models, there is a need for more integration of experimental approaches when studying impacts of climate change on species distributions. Here, we used controlled experiments to identify physiological thresholds that control poleward range limits of three species of mangroves found in North America. We found that all three species exhibited a threshold response to extreme cold, but freeze tolerance thresholds varied among species. From these experiments, we developed a climate metric, freeze degree days (FDD), which incorporates both the intensity and the frequency of freezes. When included in distribution models, FDD accurately predicted mangrove presence/absence. Using 28 years of satellite imagery, we linked FDD to observed changes in mangrove abundance in Florida, further exemplifying the importance of extreme cold. We then used downscaled climate projections of FDD to project that these range limits will move northward by 2.2–3.2 km yr⁻¹ over the next 50 years

Identification of blood-based molecular signatures for prediction of response and relapse in schizophrenia patients

The current inability of psychiatric medicine to objectively select the most appropriate treatment or to predict imminent relapse are major factors contributing to the severity and clinical burden of schizophrenia. We have previously used multiplexed immunoassays to show that schizophrenia patients have a distinctive molecular signature in serum compared with healthy control subjects. In the present study, we used the same approach to measure biomarkers in a population of 77 schizophrenia patients who were followed up over 25 months with four aims: (1) to identify molecules associated with symptom severity in antipsychotic naive and unmedicated patients, (2) to determine biomarker signatures that could predict response over a 6-week treatment period, (3) to identify molecular panels that could predict the time to relapse in a cross-sectional population of patients in remission and (4) to investigate how the biological relapse signature changed throughout the treatment course. This led to identification of molecular signatures that could predict symptom improvement over the first 6 weeks of treatment as well as predict time to relapse in a subset of 18 patients who experienced recurrence of symptoms. This study provides the groundwork for the development of novel objective clinical tests that can help psychiatrists in the clinical management of schizophrenia

Genetic Background Can Result in a Marked or Minimal Effect of Gene Knockout (GPR55 and CB2 Receptor) in Experimental Autoimmune Encephalomyelitis Models of Multiple Sclerosis

PMCID: PMC379391

LHC and lepton flavour violation phenomenology of a left-right extension of the MSSM

We study the phenomenology of a supersymmetric left-right model, assuming minimal supergravity boundary conditions. Both left-right and (B-L) symmetries are broken at an energy scale close to, but significantly below the GUT scale. Neutrino data is explained via a seesaw mechanism. We calculate the RGEs for superpotential and soft parameters complete at 2-loop order. At low energies lepton flavour violation (LFV) and small, but potentially measurable mass splittings in the charged scalar lepton sector appear, due to the RGE running. Different from the supersymmetric 'pure seesaw' models, both, LFV and slepton mass splittings, occur not only in the left- but also in the right slepton sector. Especially, ratios of LFV slepton decays, such as Br(${\tilde\tau}_R \to \mu \chi^0_1$)/Br(${\tilde\tau}_L \to \mu \chi^0_1$) are sensitive to the ratio of (B-L) and left-right symmetry breaking scales. Also the model predicts a polarization asymmetry of the outgoing positrons in the decay $\mu^+ \to e^+ \gamma$, A ~ [0,1], which differs from the pure seesaw 'prediction' A=1$. Observation of any of these signals allows to distinguish this model from any of the three standard, pure (mSugra) seesaw setups.Comment: 43 pages, 17 figure

Breast imaging technology: Application of magnetic resonance imaging to angiogenesis in breast cancer

Magnetic resonance imaging (MRI) techniques enable vascular function to be mapped with high spatial resolution. Current methods for imaging in breast cancer are described, and a review of recent studies that compared dynamic contrast-enhanced MRI with histopathological indicators of tumour vascular status is provided. These studies show correlation between in vivo dynamic contrast measurements and in vitro histopathology. Dynamic contrast enhanced MRI is also being applied to assessment of the response of breast tumours to treatment

Methods for specifying the target difference in a randomised controlled trial : the Difference ELicitation in TriAls (DELTA) systematic review

Peer reviewedPublisher PD

Study of the reaction e^{+}e^{-} -->J/psi\pi^{+}\pi^{-} via initial-state radiation at BaBar

We study the process $e^+e^-\to J/\psi\pi^{+}\pi^{-}$ with initial-state-radiation events produced at the PEP-II asymmetric-energy collider. The data were recorded with the BaBar detector at center-of-mass energies 10.58 and 10.54 GeV, and correspond to an integrated luminosity of 454 $\mathrm{fb^{-1}}$. We investigate the $J/\psi \pi^{+}\pi^{-}$ mass distribution in the region from 3.5 to 5.5 $\mathrm{GeV/c^{2}}$. Below 3.7 $\mathrm{GeV/c^{2}}$ the $\psi(2S)$ signal dominates, and above 4 $\mathrm{GeV/c^{2}}$ there is a significant peak due to the Y(4260). A fit to the data in the range 3.74 -- 5.50 $\mathrm{GeV/c^{2}}$ yields a mass value $4244 \pm 5$ (stat) $\pm 4$ (syst)$\mathrm{MeV/c^{2}}$ and a width value $114 ^{+16}_{-15}$ (stat)$\pm 7$(syst)$\mathrm{MeV}$ for this state. We do not confirm the report from the Belle collaboration of a broad structure at 4.01 $\mathrm{GeV/c^{2}}$. In addition, we investigate the $\pi^{+}\pi^{-}$ system which results from Y(4260) decay

Semi-automated non-target processing in GC × GC–MS metabolomics analysis: applicability for biomedical studies

Due to the complexity of typical metabolomics samples and the many steps required to obtain quantitative data in GC × GC–MS consisting of deconvolution, peak picking, peak merging, and integration, the unbiased non-target quantification of GC × GC–MS data still poses a major challenge in metabolomics analysis. The feasibility of using commercially available software for non-target processing of GC × GC–MS data was assessed. For this purpose a set of mouse liver samples (24 study samples and five quality control (QC) samples prepared from the study samples) were measured with GC × GC–MS and GC–MS to study the development and progression of insulin resistance, a primary characteristic of diabetes type 2. A total of 170 and 691 peaks were quantified in, respectively, the GC–MS and GC × GC–MS data for all study and QC samples. The quantitative results for the QC samples were compared to assess the quality of semi-automated GC × GC–MS processing compared to targeted GC–MS processing which involved time-consuming manual correction of all wrongly integrated metabolites and was considered as golden standard. The relative standard deviations (RSDs) obtained with GC × GC–MS were somewhat higher than with GC–MS, due to less accurate processing. Still, the biological information in the study samples was preserved and the added value of GC × GC–MS was demonstrated; many additional candidate biomarkers were found with GC × GC–MS compared to GC–MS

Novel n-3 Docosapentaneoic Acid-Derived Pro-resolving Mediators Are Vasculoprotective and Mediate the Actions of Statins in Controlling Inflammation

“This is a post-peer-review, pre-copyedit version of a chapter published in Advances in Experimental Medicine and Biology book series (AEMB, volume 1161). The final publication is available athttps://doi.org/10.1007/978-3-030-21735-8_7