Effects of elevated CO2 on phytoplankton community biomass and species composition during a spring Phaeocystis spp. bloom in the western English Channel

A 21-year time series of phytoplankton community structure was analysed in relation to Phaeocystis spp. to elucidate its contribution to the annual carbon budget at station L4 in the western English Channel (WEC). Between 1993–2014 Phaeocystis spp. contributed ∼4.6% of the annual phytoplankton carbon and during the March − May spring bloom, the mean Phaeocystis spp. biomass constituted 17% with a maximal contribution of 47% in 2001. Upper maximal weekly values above the time series mean ranged from 63 to 82% of the total phytoplankton carbon (∼42–137 mg carbon (C) m −3 ) with significant inter-annual variability in Phaeocystis spp. Maximal biomass usually occurred by the end of April, although in some cases as early as mid-April (2007) and as late as late May (2013). The effects of elevated pCO 2 on the Phaeocystis spp. spring bloom were investigated during a fifteen-day semi-continuous microcosm experiment. The phytoplankton community biomass was estimated at ∼160 mg C m −3 and was dominated by nanophytoplankton (40%, excluding Phaeocystis spp.), Phaeocystis spp. (30%) and cryptophytes (12%). The smaller fraction of the community biomass comprised picophytoplankton (9%), coccolithophores (3%), Synechococcus (3%), dinoflagellates (1.5%), ciliates (1%) and diatoms (0.5%). Over the experimental period, total biomass increased significantly by 90% to ∼305 mg C m −3 in the high CO 2 treatment while the ambient pCO 2 control showed no net gains. Phaeocystis spp. exhibited the greatest response to the high CO 2 treatment, increasing by 330%, from ∼50 mg C m −3 to over 200 mg C m −3 and contributing ∼70% of the total biomass. Taken together, the results of our microcosm experiment and analysis of the time series suggest that a future high CO 2 scenario may favour dominance of Phaeocystis spp. during the spring bloom. This has significant implications for the formation of hypoxic zones and the alteration of food web structure including inhibitory feeding effects and lowered fecundity in many copepod species

Development and Psychometric Validation of the Pandemic-Related Traumatic Stress Scale for Children and Adults

To assess the public health impact of the COVID-19 pandemic on mental health, investigators from the National Institutes of Health Environmental influences on Child Health Outcomes (ECHO) research program developed the Pandemic-Related Traumatic Stress Scale (PTSS). Based on the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) acute stress disorder symptom criteria, the PTSS is designed for adolescent (13–21 years) and adult self-report and caregiver-report on 3–12-year-olds. To evaluate psychometric properties, we used PTSS data collected between April 2020 and August 2021 from non-pregnant adult caregivers (n = 11,483), pregnant/postpartum individuals (n = 1,656), adolescents (n = 1,795), and caregivers reporting on 3–12-year-olds (n = 2,896). We used Mokken scale analysis to examine unidimensionality and reliability, Pearson correlations to evaluate relationships with other relevant variables, and analyses of variance to identify regional, age, and sex differences. Mokken analysis resulted in a moderately strong, unidimensional scale that retained nine of the original 10 items. We detected small to moderate positive associations with depression, anxiety, and general stress, and negative associations with life satisfaction. Adult caregivers had the highest PTSS scores, followed by adolescents, pregnant/postpartum individuals, and children. Caregivers of younger children, females, and older youth had higher PTSS scores compared to caregivers of older children, males, and younger youth, respectively

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Childhood-onset autoimmune cytopenia as the presenting feature of biallelic ACP5 mutations

Childhood-onset chronic and refractory cytopenias are rare and may be genetic in etiology. We report three pediatric cases of severe autoimmune thrombocytopenia or anemia associated with growth retardation and spastic diplegia with intracranial calcification. The identification of platyspondyly and metaphyseal lesions suggested a potential diagnosis of spondyloenchondrodysplasia (SPENCD), which was confirmed with the identification of biallelic ACP5 mutations. Two patients demonstrated elevated serum interferon alpha levels. Our report highlights ACP5-associated disease as a cause of childhood-onset autoimmune cytopenia, particularly combined with growth retardation and/or spasticity. Furthermore, a role for type I interferon in the pathogenesis of autoimmune cytopenias is supported

The pressure–temperature–time path of migmatites from the Sikkim Himalaya

A combined metamorphic and isotopic study of lit-par-lit migmatites exposed in the hanging wall of the Main Central Thrust (MCT) from Sikkim has provided a unique insight into the pressure–temperature–time path of the High Himalayan Crystalline Series of the eastern Himalaya. The petrology and geochemistry of one such migmatite indicates that the leucosome comprises a crystallized peraluminous granite coexisting with sillimanite and alkali feldspar. Large garnet crystals (2–3 mm across) are strongly zoned and grew initially within the kyanite stability field. The melanosome is a biotite–garnet pelitic gneiss, with fibrolitic sillimanite resulting from polymorphic inversion of kyanite. By combining garnet zoning profiles with the NaCaMnKFMASHTO pseudosection appropriate to the bulk composition of a migmatite retrieved from c. 1 km above the thrust zone, it has been established that early garnet formed at pressures of 10–12 kbar, and that subsequent decompression caused the rock to enter the melt field at c. 8 kbar and c. 750 °C, generating peritectic sillimanite and alkali feldspar by the incongruent melting of muscovite. Continuing exhumation resulted in resorption of garnet. Sm–Nd growth ages of garnet cores and rim, indicate pre-decompression garnet growth at 23 ± 3 Ma and near-peak temperatures during melting at 16 ± 2 Ma. This provides a decompression rate of 2 ± 1 mm yr-1 that is consistent with exhumation rates inferred from mineral cooling ages from the eastern Himalaya. Simple 1D thermal modelling confirms that exhumation at this rate would result in a near-isothermal decompression path, a result that is supported by the phase relations in both the melanosome and leucosome components of the migmatite. Results from this study suggest that anatexis of Miocene granite protoliths from the Himalaya was a consequence of rapid decompression, probably in response to movement on the MCT and on the South Tibetan detachment to the north

Exposure to Contemporary and Emerging Chemicals in Commerce among Pregnant Women in the United States: The Environmental influences on Child Health Outcome (ECHO) Program.

Prenatal chemical exposures can influence maternal and child health; however, few industrial chemicals are routinely biomonitored. We assessed an extensive panel of contemporary and emerging chemicals in 171 pregnant women across the United States (U.S.) and Puerto Rico in the Environmental influences on Child Health Outcomes (ECHO) Program. We simultaneously measured urinary concentrations of 89 analytes (103 total chemicals representing 73 parent compounds) in nine chemical groups: bactericides, benzophenones, bisphenols, fungicides and herbicides, insecticides, organophosphate esters (OPEs), parabens, phthalates/alternative plasticizers, and polycyclic aromatic hydrocarbons (PAHs). We estimated associations of creatinine-adjusted concentrations with sociodemographic and specimen characteristics. Among our diverse prenatal population (60% non-Hispanic Black or Hispanic), we detected 73 of 89 analytes in ≥1 participant and 36 in >50% of participants. Five analytes not currently included in the U.S. biomonitoring were detected in ≥90% of samples: benzophenone-1, thiamethoxam, mono-2-(propyl-6-carboxy-hexyl) phthalate, monocarboxy isooctyl phthalate, and monohydroxy-iso-decyl phthalate. Many analyte concentrations were higher among women of Hispanic ethnicity compared to those of non-Hispanic White women. Concentrations of certain chemicals decreased with the calendar year, whereas concentrations of their replacements increased. Our largest study to date identified widespread exposures to prevalent and understudied chemicals in a diverse sample of pregnant women in the U.S