Effects of selective serotonin reuptake inhibitor treatment on plasma oxytocin and cortisol in major depressive disorder

Background: Oxytocin is known for its capacity to facilitate social bonding, reduce anxiety and for its actions on the stress hypothalamopituitary adrenal (HPA) axis. Since oxytocin can physiologically suppress activity of the HPA axis, clinical applications of this neuropeptide have been proposed in conditions where the function of the HPA axis is dysregulated. One such condition is major depressive disorder (MDD). Dysregulation of the HPA system is the most prominent endocrine change seen with MDD, and normalizing the HPA axis is one of the major targets of recent treatments. The potential clinical application of oxytocin in MDD requires improved understanding of its relationship to the symptoms and underlying pathophysiology of MDD. Previous research has investigated potential correlations between oxytocin and symptoms of MDD, including a link between oxytocin and treatment related symptom reduction. The outcomes of studies investigating whether antidepressive treatment (pharmacological and non-pharmacological) influences oxytocin concentrations in MDD, have produced conflicting outcomes. These outcomes suggest the need for an investigation of the influence of a single treatment class on oxytocin concentrations, to determine whether there is a relationship between oxytocin, the HPA axis (e.g., oxytocin and cortisol) and MDD. Our objective was to measure oxytocin and cortisol in patients with MDD before and following treatment with selective serotonin reuptake inhibitors, SSRI. Method: We sampled blood from arterial plasma. Patients with MDD were studied at the same time twice; pre- and post- 12 weeks treatment, in an unblinded sequential design (clinicaltrials.govNCT00168493). Results: Results did not reveal differences in oxytocin or cortisol concentrations before relative to following SSRI treatment, and there were no significant relationships between oxytocin and cortisol, or these two physiological variables and psychological symptom scores, before or after treatment. Conclusions: These outcomes demonstrate that symptoms of MDD were reduced following effective treatment with an SSRI, and further, stress physiology was unlikely to be a key factor in this outcome. Further research is required to discriminate potential differences in underlying stress physiology for individuals with MDD who respond to antidepressant treatment, relative to those who experience treatment resistance.Charlotte Keating, Tye Dawood, David A Barton, Gavin W Lambert and Alan J Tilbroo

Using Light to Improve Commercial Value

The plasticity of plant morphology has evolved to maximize reproductive fitness in response to prevailing environmental conditions. Leaf architecture elaborates to maximize light harvesting, while the transition to flowering can either be accelerated or delayed to improve an individual's fitness. One of the most important environmental signals is light, with plants using light for both photosynthesis and as an environmental signal. Plants perceive different wavelengths of light using distinct photoreceptors. Recent advances in LED technology now enable light quality to be manipulated at a commercial scale, and as such opportunities now exist to take advantage of plants' developmental plasticity to enhance crop yield and quality through precise manipulation of a crops' lighting regime. This review will discuss how plants perceive and respond to light, and consider how these specific signaling pathways can be manipulated to improve crop yield and quality

GLODAPv2.2022: the latest version of the global interior ocean biogeochemical data product

The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface-to-bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2022 is an update of the previous version, GLODAPv2.2021 (Lauvset et al., 2021). The major changes are as follows: data from 96 new cruises were added, data coverage was extended until 2021, and for the first time we performed secondary quality control on all sulphur hexafluoride (SF6) data. In addition, a number of changes were made to data included in GLODAPv2.2021. These changes affect specifically the SF6 data, which are now subjected to secondary quality control, and carbon data measured onboard the RV Knorr in the Indian Ocean in 1994–1995 which are now adjusted using CRM measurements made at the time. GLODAPv2.2022 includes measurements from almost 1.4 million water samples from the global oceans collected on 1085 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but converted to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For the present annual update, adjustments for the 96 new cruises were derived by comparing those data with the data from the 989 quality controlled cruises in the GLODAPv2.2021 data product using crossover analysis. SF6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO2) chemistry comparisons to estimates based on empirical algorithms provided additional context for adjustment decisions. The adjustments that we applied are intended to remove potential biases from errors related to measurement, calibration, and data handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 μmol kg-1 in dissolved inorganic carbon, 4 μmol kg-1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments

GLODAPv2.2022: the latest version of the global interior ocean biogeochemical data product

The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface-to-bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2022 is an update of the previous version, GLODAPv2.2021 (Lauvset et al., 2021). The major changes are as follows: data from 96 new cruises were added, data coverage was extended until 2021, and for the first time we performed secondary quality control on all sulfur hexafluoride (SF6) data. In addition, a number of changes were made to data included in GLODAPv2.2021. These changes affect specifically the SF6 data, which are now subjected to secondary quality control, and carbon data measured on board the RV Knorr in the Indian Ocean in 1994–1995 which are now adjusted using certified reference material (CRM) measurements made at the time. GLODAPv2.2022 includes measurements from almost 1.4 million water samples from the global oceans collected on 1085 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, chlorofluorocarbon-11 (CFC-11), CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but converted to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For the present annual update, adjustments for the 96 new cruises were derived by comparing those data with the data from the 989 quality-controlled cruises in the GLODAPv2.2021 data product using crossover analysis. SF6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO2) chemistry comparisons to estimates based on empirical algorithms provided additional context for adjustment decisions. The adjustments that we applied are intended to remove potential biases from errors related to measurement, calibration, and data handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments. The original data, their documentation, and DOI codes are available at the Ocean Carbon and Acidification Data System of NOAA NCEI (https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/oceans/GLODAPv2_2022/, last access: 15 August 2022). This site also provides access to the merged data product, which is provided as a single global file and as four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under https://doi.org/10.25921/1f4w-0t92 (Lauvset et al., 2022). These bias-adjusted product files also include significant ancillary and approximated data, which were obtained by interpolation of, or calculation from, measured data. This living data update documents the GLODAPv2.2022 methods and provides a broad overview of the secondary quality control procedures and results.</p

Examining the preparation and characterization of coatings based on linear aromatic terpoly(methoxy-cyanurate-thiocyanurate)s

Two series of terpoly(methoxy-cyanurate-thiocyanurate)s based on thiodiphenol and dithiodiphenyl sulphide, and dihydroxydiphenylether and dithiodiphenyl ether, are prepared in good yield and purity, and fully characterised. Most of the resulting polymers, formed at room temperature using phase transfer catalysis, can be cast into films with good resilience and thermal stability. Two series of terpoly(methoxy-cyanurate-thiocyanurate)s based on thiodiphenol and dithiodiphenyl sulfide and on dihydroxydiphenyl ether and dithiodiphenyl ether, were prepared in good yield and purity and fully characterized. Most of the resulting polymers, formed at room temperature using phase transfer catalysis, can be cast into films with good resilience and thermal stability (some examples suffer practically no mass loss when held isothermally at 190 °C and only display appreciable losses when held continuously at 225 °C). Char yields of 53%-61% are achieved in nitrogen depending on backbone structure. Some problems were encountered with solubility, particularly with copolymers, which limited molecular weight analysis, but values of Mn = 8000-13000 g mol-1 were obtained for the polymers based on thiodiphenol and dithiodiphenyl sulfide, and Mn = 5000-13000 g mol-1 for the polymers based on dihydroxydiphenyl ether and dithiodiphenyl ether. DSC reveals polymerization exotherms with maxima at 184-207 °C (ΔHp = 43-59 kJ mol-1), which are believed to be due to isomerization of the cyanurate to the isocyanurate (activation energies span 159-195 kJ mol-1). Molecular simulation shows that diphenylether and diphenylsulfide display very similar conformational energy surfaces and would therefore be expected to adopt similar conformations, but the diphenylsulfide offers less resistance to deformations that increase the proximity of the two phenyl rings and results in more resilient films. © 2013 Society of Chemical Industry