Miracle-dz/UniFAR-FTUs huggingface dataset:
OP-SOCI210167 1..20

Meeting the multiple and often complex needs of families (children, young people and adults) within ‘Early Help’ support is dependent upon practitioners from different sectors sharing relevant and timely information, after gaining a family’s voluntary consent to share information. This article reports on qualitative one-to-one interviews with adults in families (n1⁄432), one mother/father dyad interview (n1⁄42) and focus groups with practitioners (n1⁄447) in five local authority areas in North East England receiving or providing Early Help support. We explored experiences of providing consent to share personal information and consider the usefulness of a digital health data system when providing Early Help support to families. Communication Privacy www.basw. co.uk # The Author(s) 2021. Published by Oxford University Press on behalf of The British Association of Social Workers. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/ 4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. British Journal of Social Work (2021) 00, 1–20 doi: 10.1093/bjsw/bcab167 D ow naded rom http/academ ic.p.com /jsw /advance-/doi/10.1093/bjsw /bcab7/6355301 by gest on 12 O cber 2021 Management theory was used as a framework to analyse the data. Key themes in participants’ accounts include the degree of need for help and support; the importance of trusting relationships; stronger and structured joint working practices; and understanding how information is shared. This work provides insights into current information sharing practices for some of the most vulnerable families and the wider social contexts. It has implications for the usefulness of a digital data system that shares GP health data with Early Help services and suggests the role this could have in the parent–practitioner relationship.
Benchmarking of Constant Power Generation Strategies for Single-Phase Grid-Connected Photovoltaic Systems

With a still increase of grid-connected photovoltaic (PV) systems, challenges have been imposed on the grid due to the continuous injection of a large amount of fluctuating PV power, like overloading the grid infrastructure (e.g., transformers) during peak power production periods. Hence, advanced active power control methods are required. As a cost-effective solution to avoid overloading, a constant power generation (CPG) control scheme by limiting the feed-in power has been introduced into the currently active grid regulations. In order to achieve a CPG operation, this paper presents three CPG strategies based on a power control method (P-CPG), a current limit method (I-CPG), and the perturb and observe algorithm (P&O-CPG). However, the operational mode changes (e.g., from the maximum power point tracking to a CPG operation) will affect the entire system performance. Thus, a benchmarking of the presented CPG strategies is also conducted on a 3-kW single-phase grid-connected PV system. Comparisons reveal that either the P-CPG or I-CPG strategies can achieve fast dynamics and satisfactory steady-state performance. In contrast, the P&O-CPG algorithm is the most suitable solution in terms of high robustness, but it presents poor dynamic performance.
Isolation and Characterization of Canthaxanthin Biosynthesis Genes from the Photosynthetic Bacterium Bradyrhizobium sp. Strain ORS278

Bradyrhizobium strains isolated from Aeschynomene stem nodules are photosynthetic (4; see reference 6 for a review), which is a rare trait in Rhizobium bacteria. These strains exhibit a photoheterotrophic and strictly aerobic photosynthesis (6; A. Vermeglio, personal communication). In culture, most of these stem isolates show the same pink coloration, while a few strains produce orange pigmentation (12, 16). Pigment analyses showed that bacteriochlorophyll and spirilloxanthin, two pigments of the light harvesting system, are common to all of these photosynthetic Bradyrhizobium strains, whereas orange strains produce an additional bicyclic carotenoid, canthaxanthin (4,49-diketo-b-carotene) (12). This was the first report on the presence of this carotenoid in photosynthetic bacteria. Bradyrhizobium sp. strain ORS278 produces the highest quantity of canthaxanthin of all tested photosynthetic bacteria; canthaxanthin represents 85% of its total carotenoid content (12). Contrary to anaerobic purple phototrophic bacteria, aerobic phototrophic bacteria synthesize an unusually diverse variety of carotenoids, including photosynthetic carotenoids such as spirilloxanthin or spheroidenone, and often a large amount of bicyclic carotenoid (b-carotene and hydroxyl derivatives) (24; see reference 26 for a review). These carotenoids were shown to not be bound to the photosynthetic apparatus of these aerobic bacteria (17, 27) and their function is still unclear— they could have a protective role against photo-oxidative damage, as already observed for several carotenoids (19, 25). Synthetic canthaxanthin is applied for both direct and indirect food coloring (10, 23). In cosmetology and pharmacology, it is also combined with b-carotene for use as a dermal photoprotector (8). Canthaxanthin is, therefore, a pigment of high economic value, but its level in Bradyrhizobium sp. strain ORS278 (1.43 mg/g of dry cell weight) remains insufficient for this organism to be a realistic candidate for natural canthaxanthin production (12). However, it could be possible to enhance the production of canthaxanthin by cloning carotenoid biosynthesis genes of this strain. In this paper, we describe the cloning and characterization of the canthaxanthin gene cluster of Bradyrhizobium sp. strain ORS278. Isolation of a carotenoid gene cluster. The genes crtB and crtI, encoding, respectively, phytoene synthase and phytoene desaturase, two enzymes involved in the initial steps of carotenoid biosynthesis (Fig. 1), have been isolated and characterized in various microorganisms (1, 9, 11, 14, 15, 21). In all of these cases, these genes were found to be adjacent and oriented in the same direction. Comparison of the deduced amino
HIV_A_255549 271..282

Amon Exavery 1 John Charles Erica Kuhlik Asheri Barankena Godfrey Martin Mubyazi Levina Kikoyo Elizabeth Jere 1Pact, Dar es Salaam, Tanzania; 2Pact, Inc., Washington, DC 20036, USA; 3National Institute for Medical Research (NIMR), Dar es Salaam, Tanzania Background: Although Tanzania experiences a general decline in HIV prevalence, some populations such as caregivers of orphans may be at a higher risk than the general population, suggesting that infection pathways still need further exploration. This study examines how food insufficiency relates to HIV infection among caregivers of orphans and vulnerable children (OVC) in Tanzania. Data and Methods: Data are from a community-based, USAID-funded Kizazi Kipya project that aims at increasing the uptake of HIV services, as well as other health and social services by OVC and their caregivers in Tanzania. Caregivers who were enrolled in the project from January to July 2017 in seven regions of Tanzania, and had reported their HIV status to the project, were included in the analysis. While HIV status was the outcome, the main independent variable was food insufficiency which was assessed using the Household Hunger Scale (HHS). Using Stata (version 14.0; StataCorp LP, College Station, TX, USA), data analysis involved multilevel mixed-effects logistic regression. Results: Of the 47,617 caregivers analyzed (73.7% females), 61.8% and 4.6% were experiencing moderate and severe hunger, respectively. The overall HIV prevalence among the caregivers was 28.3%. Nevertheless, the prevalence was as high as 34.2% among caregivers in severe hunger households. Multivariate analysis revealed an increasing likelihood of being HIV positive as hunger increased (moderate hunger: OR=1.10, 95%CI: 1.03–1.18; severe hunger: OR=1.51, 95%CI: 1.32–1.74). These observations were adjusted for marital status, age, sex, education, place of residence, family size, disability status, and health insurance. Conclusion: Food insufficiency is associated with a higher likelihood of HIV infection among OVC caregivers in Tanzania, suggesting that improving access to adequate food has a potential to reduce HIV risks among them. Furthermore, food insufficiency could be considered an important criterion for targeting HIV testing and treatment services to expand coverage.
(2008) Cancer profiles by affinity propagation. In: Seventh International Conference on Machine Learning and Applications, 2008.

The affinity propagation algorithm is applied to a problem of breast cancer subtyping using traditional biologic markers. The algorithm provides a procedure to determine the number of profiles to be considered. A well know breast cancer case series was used to compare the results of the affinity propagation with the results obtained with standard algorithms and indexes for the optimal choice of the number of clusters. Results from affinity propagation are consistent with the results already obtained having the advantage of providing an indication about the number of clusters.
Smoking and Parkinson disease: Evidence for gene-by-smoking interactions.

Objective To investigate whether cigarette smoking interacts with genes involved in individual susceptibility to xenobiotics for the risk of Parkinson disease (PD). Methods Two French population-based case-control studies (513 patients, 1,147 controls) were included as a discovery sample to examine gene-smoking interactions based on 3,179 single nucleotide polymorphisms (SNPs) in 289 genes involved in individual susceptibility to xenobiotics. SNP – by – cigarette smoking interactions were tested in the discovery sample through an empirical Bayes (EB) approach. Nine SNPs were selected for replication in a population-based case-control study from California (410 patients, 845 controls) with standard logistic regression and the EB approach. For SNPs that replicated, we performed pooled analyses including the discovery and replication datasets and computed pooled odds ratios and con ﬁ dence intervals (CIs) using random-e ﬀ ects meta-analysis. discovery dataset
Modeling Contextual Agreement in Preferences

Personalization, or customizing the experience of each individual user, is seen as a useful way to navigate the huge variety of choices on the Web today. A key tenet of personalization is the capacity to model user preferences. The paradigm has shifted from that of individual preferences, whereby we look at a user’s past activities alone, to that of shared preferences, whereby we model the similarities in preferences between pairs of users (e.g., friends, people with similar interests). However, shared preferences are still too granular, because it assumes that a pair of users would share preferences across all items. We therefore postulate the need to pay attention to “context”, which refers to the specific item on which the preferences between two users are to be estimated. In this paper, we propose a generative model for contextual agreement in preferences. For every triplet consisting of two users and an item, the model estimates both the prior probability of agreement between the two users, as well as the posterior probability of agreement with respect to the item at hand. The model parameters are estimated from ratings data. To extend the model to unseen ratings, we further propose several matrix factorization techniques focused on predicting agreement, rather than ratings. Experiments on real-life data show that our model yields context-specific similarity values that perform better on a prediction task than models relying on shared preferences.
Bidirectional Associations Between TCRs and Social Status

This four-wave longitudinal study examined bidirectional associations among pupils’ social status (preference and popularity) and teacher–child relationship characteristics (quality, support, satisfaction, and conflict) in special education. Participants included 586 pupils (86% boys) initially attending Grades 4 and 5 (M age Wave 1 = 10.82 years, SD = 0.86) and their teachers. Reports of teacher–child relationships were collected from teachers and pupils through questionnaires. Peer nominations were used to assess preference and popularity. Autoregressive cross-lagged models indicated that preference predicted changes in satisfaction between school years. Conflict in the teacher–child relationship predicted preference, and preference and popularity predicted conflict within and between school years. Bidirectionality of the associations depended on the aspect of the teacher–child relationship and the dimension of social status. Conflict was more robustly related to social status than satisfaction, support, and pupil-reported relationship quality. The associations within school years were not more robust than associations between school years.
Summary of the Mechanical Performances of the 1.5 m Long Models of the Nb3Sn Low-β Quadrupole MQXF

The Nb3Sn quadrupole MQXF is being developed as a part of the LHC High Luminosity upgrade. The magnet design was tested on 1.5m long short models, sharing the same cross-section with the full-length magnets. Various azimuthal and longitudinal preloads were applied, studying the impact on the magnet training and on its mechanical performances. The experiments demonstrated the possibility to control the magnet prestress. However, various factors, coil size among the others, may affect the stress variation between and within each winding. This variation could prevent the magnet to reach the desired performances, for example as result of critical current degradation of the Nb3Sn strands. This paper analyzes the mechanical performances of the short models, studying in particular the stress variation on different coils. The measured coil size was used as input in the numerical simulations, and results were then compared with the strain gauge measurements. Finally, the short models experience was used to evaluate the feasibility of a loading operation that does not rely on the strain measurements.
Prediction of adolescent suicide attempt by integrating clinical, neurocognitive and geocoded neighborhood environment data

Objective- The authors used multimodal data collected during pre/early-adolescence in research settings to predict self-report of past suicide attempt (SA) by mid-late adolescence in pediatric care settings. The study further aimed to determine types of data that contribute to the prediction; and to test generalizability of the prediction in an independent sample. Methods- The authors applied machine learning methods on clinical, neurocognitive and geocoded neighborhood environmental data from the Philadelphia Neurodevelopmental Cohort study (PNC, Mean age 11.1, SD=2.2, 52.3% female and 51.4% Black participants) to predict SA reported ~5 years later in a community pediatric clinic (n=922, 5.3% SA) or emergency department (n=497, 8.2% SA). The authors compared prediction performance when using all data versus individual data types, then used feature selection algorithms (Lasso, Relief and Random Forest) to identify important predictors and compared performance of models relying on feature subsets. Results- In the training dataset, SA prediction was good, reaching AUC=0.75, sensitivity/specificity 0.76/0.77 when relying on feature subsets identified using feature selection pipelines. Use of highest-ranking feature subsets from the training dataset yielded similar prediction in the testing dataset with AUC=0.74, sensitivity/specificity 0.66/0.70. Different algorithms showed different high-ranking features, but overall multiple data domains were represented among the highest-ranking predictors selected by each algorithm. Conclusions- These findings provide evidence for feasibility of predicting youth SA using data collected at a single timepoint early in life in a diverse cohort. Results encourage incorporation of multiple data types including neurocognitive and geocoded environmental measures in machine learning SA prediction pipelines.
Contribution of prenatal exposure to ambient temperature extremes and severe maternal morbidity: A retrospective Southern birth cohort

BACKGROUND: Health disparities have persisted in severe maternal morbidity (SMM), an event in which a woman nearly dies from a complication during pregnancy, with limited data on environmental risk factors. OBJECTIVE: To examine the association between prenatal exposure to high and low ambient temperatures and SMM during critical windows of pregnancy for a birth cohort in the Southeastern United States. METHODS: This retrospective, population-based birth cohort included hospital deliveries from 1999 to 2017 (570,660 women, 921,444 deliveries). Daily average temperatures at the county-scale were merged with delivery discharge records and days of exposure to very hot and very cold were estimated over the following critical windows: preconception, and first, second, and third trimesters (T1-T3). Generalized estimating equations with multivariable Poisson models examined the association between temperature extremes and SMM for each critical window. RESULTS: Women exposed to a low compared to a high number of cold days during the first and third trimesters were 1.11 (CI: 1.03, 1.20) and 1.30 (CI: 1.20, 1.42) times more likely to experience SMM, respectively. Compared to the no exposure group, women exposed to a high number of very hot temperatures during preconception were 1.09 (95%CI:1.02,1.18) more likely to experience SMM. Sustained exposure to a high or moderate-intensity heat wave during the summer months was associated with a 45% or 39% increase in SMM risk during T2, respectively. Pregnant populations residing in rural locations were more sensitive to cold exposure in T3. Women exposed to a high number of very hot days in T2 compared to no exposure were 20% more likely to experience preterm SMM. SIGNIFICANCE: Findings suggest that maternal exposure to hot or cold temperature extremes around the time or during pregnancy may be a contributing environmental risk factor for SMM. More attention should be focused on prenatal counseling in pregnant populations around the risk of thermal extremes.
Mitochondrial MICOS complex genes, implicated in hypoplastic left heart syndrome, maintain cardiac contractility and actomyosin integrity

Hypoplastic left heart syndrome (HLHS) is a severe congenital heart disease (CHD) with a likely oligogenic etiology, but our understanding of the genetic complexities and pathogenic mechanisms leading to HLHS is limited. We therefore performed whole genome sequencing (WGS) on a large cohort of HLHS patients and their families to identify candidate genes that were then tested in Drosophila heart model for functional and structural requirements. Bioinformatic analysis of WGS data from an index family comprised of a HLHS proband born to consanguineous parents and postulated to have a homozygous recessive disease etiology, prioritized 9 candidate genes with rare, predicted damaging homozygous variants. Of the candidate HLHS gene homologs tested, cardiac-specific knockdown (KD) of mitochondrial MICOS complex subunit dCHCHD3/6 resulted in drastically compromised heart contractility, diminished levels of sarcomeric actin and myosin, reduced cardiac ATP levels, and mitochondrial fission-fusion defects. Interestingly, these heart defects were similar to those inflicted by cardiac KD of ATP synthase subunits of the electron transport chain (ETC), consistent with the MICOS complex's role in maintaining cristae morphology and ETC complex assembly. Analysis of 183 genomes of HLHS patient-parent trios revealed five additional HLHS probands with rare, predicted damaging variants in CHCHD3 or CHCHD6. Hypothesizing an oligogenic basis for HLHS, we tested 60 additional prioritized candidate genes in these cases for genetic interactions with CHCHD3/6 in sensitized fly hearts. Moderate KD of CHCHD3/6 in combination with Cdk12 (activator of RNA polymerase II), RNF149 (E3 ubiquitin ligase), or SPTBN1 (scaffolding protein) caused synergistic heart defects, suggesting the potential involvement of a diverse set of pathways in HLHS. Further elucidation of novel candidate genes and genetic interactions of potentially disease-contributing pathways is expected to lead to a better understanding of HLHS and other CHDs.
Managing the evidence infodemic: Automation approaches used for developing NICE COVID-19 living guidelines

Background and Objectives The National Institute for Health and Care Excellence (NICE) produces evidence-based guidance and advice for health, public health and social care practitioners in England and Wales. Between March 2020 and March 2022, NICE produced 24 COVID-19 guidelines to support healthcare workers during the COVID-19 pandemic. This article outlines three automation strategies NICE utilised to facilitate faster processing of evidence on COVID-19 and describes the value of those approaches when there is an increasing volume of evidence and demand on resources. Study Design and Setting Text classification using machine learning, and regular expression-based pattern matching were used to automate screening of literature search results. Relevant clinical trials were tracked by automated monitoring of clinical trial databases and Pubmed. Results The strategies discussed here brought considerable efficiencies in the processing time without impacting on quality compared to equivalent manual efforts. Additionally, the paper illustrates how to incorporate automation into established processes of the evidence management pipeline. Conclusions We have demonstrated through testing and use in live guideline development and surveillance that these are effective and low risk approaches at managing high volumes of evidence.
Genetic risk, parental history, and suicide attempts in a diverse sample of US adolescents

Background Adolescent suicide is a major health problem in the US marked by a recent increase in risk of suicidal behavior among Black/African American youth. While genetic factors partly account for familial transmission of suicidal behavior, it is not clear whether polygenic risk scores of suicide attempt can contribute to suicide risk classification. Objectives To evaluate the contribution of a polygenic risk score for suicide attempt (PRS-SA) in explaining variance in suicide attempt by early adolescence. Methods We studied N = 5,214 non-related youth of African and European genetic ancestry from the Adolescent Brain Cognitive Development (ABCD) Study (ages 8.9–13.8 years) who were evaluated between 2016 and 2021. Regression models tested associations between PRS-SA and parental history of suicide attempt/death with youth-reported suicide attempt. Covariates included age and sex. Results Over three waves of assessments, 182 youth (3.5%) reported a past suicide attempt, with Black youth reporting significantly more suicide attempts than their White counterparts (6.1 vs. 2.8%, p < 0.001). PRS-SA was associated with suicide attempt [odds ratio (OR) = 1.3, 95% confidence interval (CI) 1.1–1.5, p = 0.001]. Parental history of suicide attempt/death was also associated with youth suicide attempt (OR = 3.1, 95% CI, 2.0–4.7, p < 0.001). PRS-SA remained significantly associated with suicide attempt even when accounting for parental history (OR = 1.29, 95% CI = 1.1–1.5, p = 0.002). In European ancestry youth (n = 4,128), inclusion of PRS-SA in models containing parental history explained more variance in suicide attempt compared to models that included only parental history (ΔR2 = 0.7%, p = 0.009). Conclusions Findings suggest that PRS-SA may be useful for youth suicide risk classification in addition to established risk factors.