Adapted motivational interviewing to improve the uptake of treatment for glaucoma in Nigeria: study protocol for a randomized controlled trial.

BACKGROUND: Glaucoma is a chronic eye disease associated with irreversible visual loss. In Africa, glaucoma patients often present late, with very advanced disease. One-off procedures, such as laser or surgery, are recommended in Africa because of lack of or poor adherence to medical treatment. However, acceptance of surgery is usually extremely low. To prevent blindness, adherence to treatment needs to improve, using acceptable, replicable and cost-effective interventions. After reviewing the literature and interviewing patients in Bauchi (Nigeria) motivational interviewing (MI) was selected as the intervention for this trial, with adaptation for glaucoma (MIG). MI is designed to strengthen personal motivation for, and commitment to a specific goal by eliciting and exploring a person's reasons for change within an atmosphere of acceptance and compassion. The aim of this study is to assess whether MIG increases the uptake of laser or surgery amongst glaucoma patients where this is the recommended treatment. The hypothesis is that MIG increases the uptake of treatment. This will be the first trial of MI in Africa. METHODS: This is a hospital based, single centre, randomized controlled trial of MIG plus an information sheet on glaucoma and its treatment (the latter being "standard care") compared with standard care alone for glaucoma patients where the treatment recommended is surgery or laser.Those eligible for the trial are adults aged 17 years and above who live within 200 km of Bauchi with advanced glaucoma where the examining ophthalmologist recommends surgery or laser. After obtaining written informed consent, participants will be randomly allocated to MIG plus standard care, or standard care alone. Motivational interviewing will be delivered in Hausa or English by one of two MIG trained personnel. One hundred and fifty participants will be recruited to each arm. The primary outcome is the proportion of participants undergoing laser or surgery within two months of the date given to re attend for the procedure. MIG quality will be assessed using the validated MI treatment integrity scale. DISCUSSION: Motivational interviewing may be an important tool to increase the acceptance of treatment for glaucoma. The approach is potentially scalable and may be useful for other chronic conditions in Africa. TRIAL REGISTRATION: ISRCTN79330571 (Controlled-Trials.com)

Optical response with threefold symmetry axis on oriented microdomains of opal photonic crystals

The paper deals with three-dimensional photonic crystals known as artificial opals, namely, fcc lattices of dielectric spheres: such systems have been the subject of numerous investigations. Opal photonic crystals viewed along the [111] direction of the fcc structure have a threefold symmetry axis; however this microscopic symmetry is difficult to observe in optical measurements performed on macroscopic areas containing microdomains with different orientations. In this work polarized transmittance measurements on [111]-stacked silica opals with single oriented microdomains, identified by field-emission scanning electron microscopy and laser-scanning confocal microscopy, demonstrate different optical response of twin structures with the two possible vertical stacking sequences. A detailed comparison with theory shows that microtransmittance experiments probe the photonic band structure along the Gamma-L-K and Gamma-L-U orientations of the Brillouin zone, respectively, thus giving conclusive evidence for macroscopic optical response related to the presence of a threefold (instead of a sixfold) symmetry axis in the photonic microstructure. The paper arises from a collaboration between the University of Pavia and the Politecnico di Torino

The Impact of International Remittance on Poverty, Household Consumption and Investment in Urban Ethiopia: Evidence from Cross-Sectional Measures

International remittance is an essential source of foreign exchange for Ethiopia, perhaps larger than the export earning of the country in its foreign exchange generation capacity. In the year 2013; total international remittance in Ethiopia reached 557 million USD from 387 million USD in 2010 according to World Bank Report. To assess the impact of international remittances on poverty, household consumption and investment in urban Ethiopia, this study used primary household survey data collected from four major urban areas of the country namely Addis Ababa, Gonder, Hawassa and Mekelle. The study applies both descriptive and empirical analysis; using Heckman two stage selection model the study finds that international remittances substantially reduce the level, depth and severity of poverty. For the sub sample of households which receive remittances poverty head count index, poverty gap and squared poverty gap declined by 64 percent, 67 percent and 70 percent respectively. Similarly the study found that all remittance receiving households spend part of their remittance income mainly on food and non durable goods. Yet, a good number of households are also used part of it for investment such as health, education and housing. Nevertheless; relatively insignificant number of households save part of remittance income and none of them used it to invest in entrepreneurial or other income generating activities.Keywords: International Remittance, Poverty and Household Consumption and Investmen

Air pollution exposure during pregnancy and childhood autistic traits in four European population-based cohort studies : the ESCAPE project

Background: Prenatal exposure to air pollutants has been suggested as a possible etiologic factor for the occurrence of autism spectrum disorder. Objectives: We aimed to assess whether prenatal air pollution exposure is associated with childhood autistic traits in the general population. Methods: Ours was a collaborative study of four European population-based birth/child cohorts— CATSS (Sweden), Generation R (the Netherlands), GASPII (Italy), and INMA (Spain). Nitrogen oxides (NO2, NOx) and particulate matter (PM) with diameters of ≤ 2.5 μm (PM2.5), ≤ 10 μm (PM10), and between 2.5 and 10 μm (PMcoarse), and PM2.5 absorbance were estimated for birth addresses by land-use regression models based on monitoring campaigns performed between 2008 and 2011. Levels were extrapolated back in time to exact pregnancy periods. We quantitatively assessed autistic traits when the child was between 4 and 10 years of age. Children were classified with autistic traits within the borderline/clinical range and within the clinical range using validated cut-offs. Adjusted cohort-specific effect estimates were combined using random-effects meta-analysis. Results: A total of 8,079 children were included. Prenatal air pollution exposure was not associated with autistic traits within the borderline/clinical range (odds ratio = 0.94; 95% CI: 0.81, 1.10 per each 10‑μg/m3 increase in NO2 pregnancy levels). Similar results were observed in the different cohorts, for the other pollutants, and in assessments of children with autistic traits within the clinical range or children with autistic traits as a quantitative score. Conclusions: Prenatal exposure to NO2 and PM was not associated with autistic traits in children from 4 to 10 years of age in four European population-based birth/child cohort studies.NonePublishe

Large Language Models meet moral values: A comprehensive assessment of moral abilities

Automatic moral classification in textual data is crucial for various fields including Natural Language Processing (NLP), social sciences, and ethical AI development. Despite advancements in supervised models, their performance often suffers when faced with real-world scenarios due to overfitting to specific data distributions. To address these limitations, we propose leveraging state-of-the-art Large Language Models (LLMs) trained on extensive common-sense data for unsupervised moral classification. We introduce an innovative evaluation framework that directly compares model outputs with human annotations, ensuring an assessment of model performance. Our methodology explores the effectiveness of different LLM sizes and prompt designs in moral value detection tasks, considering both multi-label and binary classification scenarios. We present experimental results using the Moral Foundation Reddit Corpus (MFRC) and discuss implications for future research in ethical AI development and human–computer interaction. Experimental results demonstrate that GPT-4 achieves superior performance, followed by GPT-3.5, Llama-70B, Mixtral-8x7B, Mistral-7B and Llama-7B. Additionally, the study reveals significant variations in model performance across different moral domains, particularly between everyday morality and political contexts. Our work provides meaningful insights into the use of zero-shot and few-shot models for moral value detection and discusses the potential and limitations of current technology in this task

Untargeted UPLC-MS Profiling Pipeline to Expand Tissue Metabolome Coverage: Application to Cardiovascular Disease.

Metabolic profiling studies aim to achieve broad metabolome coverage in specific biological samples. However, wide metabolome coverage has proven difficult to achieve, mostly because of the diverse physicochemical properties of small molecules, obligating analysts to seek multiplatform and multimethod approaches. Challenges are even greater when it comes to applications to tissue samples, where tissue lysis and metabolite extraction can induce significant systematic variation in composition. We have developed a pipeline for obtaining the aqueous and organic compounds from diseased arterial tissue using two consecutive extractions, followed by a different untargeted UPLC-MS analysis method for each extract. Methods were rationally chosen and optimized to address the different physicochemical properties of each extract: hydrophilic interaction liquid chromatography (HILIC) for the aqueous extract and reversed-phase chromatography for the organic. This pipeline can be generic for tissue analysis as demonstrated by applications to different tissue types. The experimental setup and fast turnaround time of the two methods contributed toward obtaining highly reproducible features with exceptional chromatographic performance (CV % < 0.5%), making this pipeline suitable for metabolic profiling applications. We structurally assigned 226 metabolites from a range of chemical classes (e.g., carnitines, α-amino acids, purines, pyrimidines, phospholipids, sphingolipids, free fatty acids, and glycerolipids) which were mapped to their corresponding pathways, biological functions and known disease mechanisms. The combination of the two untargeted UPLC-MS methods showed high metabolite complementarity. We demonstrate the application of this pipeline to cardiovascular disease, where we show that the analyzed diseased groups (<i>n </i>= 120) of arterial tissue could be distinguished based on their metabolic profiles

Uncovering Values: Detecting Latent Moral Content from Natural Language with Explainable and Non-Trained Methods

Moral values as commonsense norms shape our everyday individual and community behavior. The possibility to extract moral attitude rapidly from natural language is an appealing perspective that would enable a deeper understanding of social interaction dynamics and the individual cognitive and behavioral dimension. In this work we focus on detecting moral content from natural language and we test our methods on a corpus of tweets previously labeled as containing moral values or violations, according to Moral Foundation Theory. We develop and compare two different approaches: (i) a frame-based symbolic value detector based on knowledge graphs and (ii) a zero-shot machine learning model fine-tuned on a task of Natural Language Inference (NLI) and a task of emotion detection. Our approaches achieve considerable performances without the need for prior training

Incidence and phenotypes of childhood-onset genetic epilepsies:a prospective population-based national cohort

Epilepsy is common in early childhood. In this age group it is associated with high rates of therapy-resistance, and with cognitive, motor, and behavioural comorbidity. A large number of genes, with wide ranging functions, are implicated in its aetiology, especially in those with therapy-resistant seizures. Identifying the more common single-gene epilepsies will aid in targeting resources, the prioritization of diagnostic testing and development of precision therapy. Previous studies of genetic testing in epilepsy have not been prospective and population-based. Therefore, the population-incidence of common genetic epilepsies remains unknown. The objective of this study was to describe the incidence and phenotypic spectrum of the most common single-gene epilepsies in young children, and to calculate what proportion are amenable to precision therapy. This was a prospective national epidemiological cohort study. All children presenting with epilepsy before 36 months of age were eligible. Children presenting with recurrent prolonged (&gt;10 min) febrile seizures; febrile or afebrile status epilepticus (&gt;30 min); or with clusters of two or more febrile or afebrile seizures within a 24-h period were also eligible. Participants were recruited from all 20 regional paediatric departments and four tertiary children’s hospitals in Scotland over a 3-year period. DNA samples were tested on a custom-designed 104-gene epilepsy panel. Detailed clinical information was systematically gathered at initial presentation and during follow-up. Clinical and genetic data were reviewed by a multidisciplinary team of clinicians and genetic scientists. The pathogenic significance of the genetic variants was assessed in accordance with the guidelines of UK Association of Clinical Genetic Science (ACGS). Of the 343 patients who met inclusion criteria, 333 completed genetic testing, and 80/333 (24%) had a diagnostic genetic finding. The overall estimated annual incidence of single-gene epilepsies in this well-defined population was 1 per 2120 live births (47.2/100 000; 95% confidence interval 36.9–57.5). PRRT2 was the most common single-gene epilepsy with an incidence of 1 per 9970 live births (10.0/100 000; 95% confidence interval 5.26–14.8) followed by SCN1A: 1 per 12 200 (8.26/100 000; 95% confidence interval 3.93–12.6); KCNQ2: 1 per 17 000 (5.89/100 000; 95% confidence interval 2.24–9.56) and SLC2A1: 1 per 24 300 (4.13/100 000; 95% confidence interval 1.07–7.19). Presentation before the age of 6 months, and presentation with afebrile focal seizures were significantly associated with genetic diagnosis. Single-gene disorders accounted for a quarter of the seizure disorders in this cohort. Genetic testing is recommended to identify children who may benefit from precision treatment and should be mainstream practice in early childhood onset epilepsy