Humanities for the environment—A manifesto for research and action

Human preferences, practices and actions are the main drivers of global environmental change in the 21st century. It is crucial, therefore, to promote pro-environmental behavior. In order to accomplish this, we need to move beyond rational choice and behavioral decision theories, which do not capture the full range of commitments, assumptions, imaginaries, and belief systems that drive those preferences and actions. Humanities disciplines, such as philosophy, history, religious studies, gender studies, language and literary studies, psychology, and pedagogics do offer deep insights into human motivations, values, and choices. We believe that the expertise of such fields for transforming human preferences, practices and actions is ignored at society’s peril. We propose an agenda that focuses global humanities research on stepping up to the challenges of planetary environmental change. We have established Environmental Humanities Observatories through which to observe, explore and enact the crucial ways humanistic disciplines may help us understand and engage with global ecological problems by providing insight into human action, perceptions, and motivation. We present this Manifesto as an invitation for others to join the “Humanities for the Environment” open global consortium of humanities observatories as we continue to develop a shared research agenda

Splice-Modulating Oligonucleotide QR-110 Restores CEP290 mRNA and Function in Human c.2991+1655A>G LCA10 Models.

Leber congenital amaurosis type 10 (LCA10) is a severe inherited retinal dystrophy associated with mutations in CEP290. The deep intronic c.2991+1655A>G mutation in CEP290 is the most common mutation in LCA10 individuals and represents an ideal target for oligonucleotide therapeutics. Here, a panel of antisense oligonucleotides was designed to correct the splicing defect associated with the mutation and screened for efficacy and safety. This identified QR-110 as the best-performing molecule. QR-110 restored wild-type CEP290 mRNA and protein expression levels in CEP290 c.2991+1655A>G homozygous and compound heterozygous LCA10 primary fibroblasts. Furthermore, in homozygous three-dimensional iPSC-derived retinal organoids, QR-110 showed a dose-dependent restoration of mRNA and protein function, as measured by percentage and length of photoreceptor cilia, without off-target effects. Localization studies in wild-type mice and rabbits showed that QR-110 readily reached all retinal layers, with an estimated half-life of 58 days. It was well tolerated following intravitreal injection in monkeys. In conclusion, the pharmacodynamic, pharmacokinetic, and safety properties make QR-110 a promising candidate for treating LCA10, and clinical development is currently ongoing.This study was funded by ProQR. iPSC work in the Cheetham lab is also supported by the Wellcome Trust, Fight for Sight, RP Fighting Blindness, and Moorfields Eye Charity

High frequency of tumor cells with nuclear Egr-1 protein expression in human bladder cancer is associated with disease progression

<p>Abstract</p> <p>Background</p> <p>Egr-1 (early growth response-1 transcription factor) has been proposed to be involved in invasion and metastasis processes of human bladder cancer, but Egr-1 protein expression levels in human bladder cancer have not been investigated. In the present study we investigated the expression levels of Egr-1 protein in early stages of human bladder cancer and correlated it to later progression.</p> <p>Methods</p> <p>Expression of Egr-1 protein in human bladder cancer was examined by immunohistochemistry, on a tissue microarray constructed from tumors from 289 patients with non-muscle invasive urothelial bladder cancer.</p> <p>Results</p> <p>The frequency of tumor cells with nuclear Egr-1 immunolabelling correlated to bladder cancer stage, grade and to later progression to muscle-invasive bladder cancer (T2-4). Stage T1 tumors exhibited significantly higher frequencies of tumor cells with nuclear Egr-1 immunolabelling than Ta tumors (P = 0.001). Furthermore, Kaplan-Meier survival analysis showed that a high frequency of tumor cells with nuclear Egr-1 immunolabelling was significantly associated with a higher risk of progression to stage T2-4 (log-rank test, P = 0.035). Tumor cells with nuclear Egr-1 immunolabelling were found to localize at the tumor front in some of the tumor biopsies.</p> <p>Conclusion</p> <p>The results from this study support a potential involvement of Egr-1 in the progression from non-muscle invasive bladder cancers to muscle invasive bladder cancer.</p

Monoamine related functional gene variants and relationships to monoamine metabolite concentrations in CSF of healthy volunteers

BACKGROUND: Concentrations of monoamine metabolites in human cerebrospinal fluid (CSF) have been used extensively as indirect estimates of monoamine turnover in the brain. CSF monoamine metabolite concentrations are partly determined by genetic influences. METHODS: We investigated possible relationships between DNA polymorphisms in the serotonin 2C receptor (HTR2C), the serotonin 3A receptor (HTR3A), the dopamine D(4 )receptor (DRD4), and the dopamine β-hydroxylase (DBH) genes and CSF concentrations of 5-hydroxyindolacetic acid (5-HIAA), homovanillic acid (HVA), and 3-methoxy-4-hydroxyphenylglycol (MHPG) in healthy volunteers (n = 90). RESULTS: The HTR3A 178 C/T variant was associated with 5-HIAA levels (p = 0.02). The DBH-1021 heterozygote genotype was associated with 5-HIAA (p = 0.0005) and HVA (p = 0.009) concentrations. Neither the HTR2C Cys23Ser variant, nor the DRD4 -521 C/T variant were significantly associated with any of the monoamine metabolites. CONCLUSIONS: The present results suggest that the HTR3A and DBH genes may participate in the regulation of dopamine and serotonin turnover rates in the central nervous system

Efficacy of dapagliflozin in heart failure with reduced ejection fraction according to body mass index

Background: In heart failure with reduced ejection fraction (HFrEF), there is an “obesity paradox”, where survival is better in patients with a higher body mass index (BMI) and weight loss is associated with worse outcomes. We examined the effect of a SGLT2 inhibitor according to baseline BMI in the Dapagliflozin And Prevention of Adverse-outcomes in Heart Failure trial (DAPA-HF). Methods and Results: BMI was examined using standard categories i.e. underweight (&lt;18.5 kg/m2); normal weight (18.5-24.9 Kg/m2); overweight (25.0-29.9 Kg/m2); obesity class I (30.0-34.9 Kg/m2); class II (35.0-39.9 Kg/m2) and class III (≥40 Kg/m2). The primary outcome in DAPA-HF was the composite of worsening heart failure or cardiovascular death. Overall, 1348 patients (28.4%) were under/normal-weight, 1722 (36.3%) overweight, 1013 (21.4%) obesity class I and 659 (13.9%) obesity class II/III. The unadjusted hazard ratio (95% CI) for the primary outcome with obesity category 1, the lowest risk group, as reference was: under-/normal-weight 1.41 (1.16-1.71), overweight 1.18 (0.97-1.42), obesity class II/III 1.37 (1.10-1.72). Patients with class I obesity were also at lowest risk of death. The effect of dapagliflozin on the primary outcome and other outcomes did not vary by baseline BMI e.g., HR for primary outcome: under-/normal-weight 0.74 (0.58-0.94), overweight 0.81 (0.65-1.02), obesity class I 0.68 (0.50-0.92), obesity class II/III 0.71 (0.51-1.00); P for interaction=0.79. The mean decrease in weight at 8 months with dapagliflozin was 0.9 (0.7-1.1) Kg (p&lt;0.001). Conclusion: We confirmed an “obesity survival paradox” in HFrEF. We showed that dapagliflozin was beneficial across the wide range of BMI studied. Clinical Trial Registration: ClinicalTrials.gov number NCT03036124 (https://clinicaltrials.gov/ct2/show/NCT03036124

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinson\u27s disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis.

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15–90. The effects of dementia, mild cognitive impairment, Parkinson’s disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p \u3c 0.001), while neither depression nor ADHD showed consistent associations with VLM scores (p \u3e 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis.

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinson's disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives