A large-scale CRISPR screen reveals context-specific genetic regulation of retinal ganglion cell regeneration.

Many genes are known to regulate retinal regeneration after widespread tissue damage. Conversely, genes controlling regeneration after limited cell loss, as per degenerative diseases, are undefined. As stem/progenitor cell responses scale to injury levels, understanding how the extent and specificity of cell loss impact regenerative processes is important. Here, transgenic zebrafish enabling selective retinal ganglion cell (RGC) ablation were used to identify genes that regulate RGC regeneration. A single cell multiomics-informed screen of 100 genes identified seven knockouts that inhibited and 11 that promoted RGC regeneration. Surprisingly, 35 out of 36 genes known and/or implicated as being required for regeneration after widespread retinal damage were not required for RGC regeneration. The loss of seven even enhanced regeneration kinetics, including the proneural factors neurog1, olig2 and ascl1a. Mechanistic analyses revealed that ascl1a disruption increased the propensity of progenitor cells to produce RGCs, i.e. increased 'fate bias'. These data demonstrate plasticity in the mechanism through which Müller glia convert to a stem-like state and context specificity in how genes function during regeneration. Increased understanding of how the regeneration of disease-relevant cell types is specifically controlled will support the development of disease-tailored regenerative therapeutics.

Fatty acid-binding proteins and fatty acid synthase influence glial reactivity and promote the formation of Müller glia-derived progenitor cells in the chick retina.

A recent comparative transcriptomic study of Müller glia (MG) in vertebrate retinas revealed that fatty acid binding proteins (FABPs) are among the most highly expressed genes in chick ( Hoang et al., 2020). Here, we investigate how FABPs and fatty acid synthase (FASN) influence glial cells in the chick retina. During development, FABP7 is highly expressed by retinal progenitor cells and maturing MG, whereas FABP5 is upregulated in maturing MG. PMP2 (FABP8) is expressed by oligodendrocytes and FABP5 is expressed by non-astrocytic inner retinal glial cells, and both of these FABPs are upregulated by activated MG. In addition to suppressing the formation of Müller glia-derived progenitor cells (MGPCs), we find that FABP-inhibition suppresses the proliferation of microglia. FABP-inhibition induces distinct changes in single cell transcriptomic profiles, indicating transitions of MG from resting to reactive states and suppressed MGPC formation, with upregulation of gene modules for gliogenesis and decreases in neurogenesis. FASN-inhibition increases the proliferation of microglia and suppresses the formation of MGPCs. We conclude that fatty acid metabolism and cell signaling involving fatty acids are important in regulating the reactivity and dedifferentiation of MG, and the proliferation of microglia and MGPCs.

AutoPeptideML: a study on how to build more trustworthy peptide bioactivity predictors.

MOTIVATION: Automated machine learning (AutoML) solutions can bridge the gap between new computational advances and their real-world applications by enabling experimental scientists to build their own custom models. We examine different steps in the development life-cycle of peptide bioactivity binary predictors and identify key steps where automation cannot only result in a more accessible method, but also more robust and interpretable evaluation leading to more trustworthy models. RESULTS: We present a new automated method for drawing negative peptides that achieves better balance between specificity and generalization than current alternatives. We study the effect of homology-based partitioning for generating the training and testing data subsets and demonstrate that model performance is overestimated when no such homology correction is used, which indicates that prior studies may have overestimated their performance when applied to new peptide sequences. We also conduct a systematic analysis of different protein language models as peptide representation methods and find that they can serve as better descriptors than a naive alternative, but that there is no significant difference across models with different sizes or algorithms. Finally, we demonstrate that an ensemble of optimized traditional machine learning algorithms can compete with more complex neural network models, while being more computationally efficient. We integrate these findings into AutoPeptideML, an easy-to-use AutoML tool to allow researchers without a computational background to build new predictive models for peptide bioactivity in a matter of minutes. AVAILABILITY AND IMPLEMENTATION: Source code, documentation, and data are available at https://github.com/IBM/AutoPeptideML and a dedicated web-server at http://peptide.ucd.ie/AutoPeptideML. A static version of the software to ensure the reproduction of the results is available at https://zenodo.org/records/13363975.

The Ability of a 3-Gene Host Signature in Blood to Distinguish Tuberculous Meningitis From Other Brain Infections.

BACKGROUND: Tuberculous meningitis (TBM) is difficult to diagnose. We investigated whether a 3-gene host response signature in blood can distinguish TBM from other brain infections. METHODS: The expression of 3 genes (dual specificity phosphatase 3 [DUSP3], guanylate-binding protein [GBP5], krupple-like factor 2 [KLF2]) was analyzed by RNA sequencing of archived whole blood from 4 cohorts of Vietnamese adults: 281 with TBM, 279 with pulmonary tuberculosis, 50 with other brain infections, and 30 healthy controls. Tuberculosis scores (combined 3-gene expression) were calculated following published methodology and discriminatory performance compared using area under a receiver operator characteristic curve (AUC). RESULTS: GBP5 was upregulated in TBM compared to other brain infections (P < .001), with no difference in DUSP3 and KLF2 expression. The diagnostic performance of GBP5 alone (AUC, 0.74; 95% confidence interval [CI], .67-.81) was slightly better than the 3-gene tuberculosis score (AUC, 0.66; 95% CI, .58-.73) in TBM. Both GBP5 expression and tuberculosis score were higher in participants with human immunodeficiency virus (HIV; P < .001), with good diagnostic performance of GBP5 alone (AUC, 0.86; 95% CI, .80-.93). CONCLUSIONS: The 3-gene host signature in whole blood has the ability to discriminate TBM from other brain infections, including in individuals with HIV. Validation in large prospective diagnostic study is now required.

Residential proximity to oil and gas developments and childhood cancer survival.

BACKGROUND: Environmental toxicants may impact survival in children with cancer, but the literature investigating these associations remains limited. Because oil and gas developments emit several hazardous air pollutants, the authors evaluated the relationship between residential proximity to oil or gas development and survival across 21 different pediatric cancers. METHODS: The Texas Cancer Registry had 29,730 children (≤19 years old) diagnosed with a primary cancer between 1995 to 2017. Geocoded data were available for 285,266 active oil or gas wells and 109,965 horizontal wells. The authors calculated whether each case lived within 1000 m (yes/no) from each type of oil or gas development. Survival analyses were conducted using Cox regression, adjusting for potential confounders. RESULTS: A total of 14.2% of cases lived within 1000 m of an oil or gas well or horizontal well. Living within 1000 m of an oil or gas well was associated with risk of mortality in cases with acute myeloid leukemia (AML) (adjusted hazard ratio [aHR], 1.36; 95% confidence interval [CI], 1.01-1.84) and hepatoblastoma (aHR, 2.13; 95% CI, 1.03-4.39). An inverse association was observed with Ewing sarcoma (aHR, 0.35; 95% CI, 0.13-0.95). No associations were observed with horizontal well. There was evidence of a dose-response effect in children with AML or hepatoblastoma and residential proximity to oil or gas wells. In general, the magnitude of association increased with decreasing distance and with higher number of wells across the three distances. CONCLUSIONS: Residential proximity to oil or gas wells at diagnosis is associated with the risk of mortality in children with AML or hepatoblastoma.

Photonic Flatband Resonances in Multiple Light Scattering.

We introduce the concept of photonic flatband resonances and demonstrate it for an array of high-index dielectric particles. We employ the multiple Mie scattering theory and demonstrate that both short- and long-range interactions between the resonators are crucial for the emerging collective resonances and their associated photonic flatbands. By examining both near- and far-field characteristics, we uncover how the flatbands emerge due to a fine tuning of resonators' radiation fields, and predict that hybridization of a flatband resonance with an electric hot spot can lead to giant values of the Purcell factor for the electric dipolar emitters.

Maternal educational attainment in pregnancy and epigenome-wide DNA methylation changes in the offspring from birth until adolescence.

Maternal educational attainment (MEA) shapes offspring health through multiple potential pathways. Differential DNA methylation may provide a mechanistic understanding of these long-term associations. We aimed to quantify the associations of MEA with offspring DNA methylation levels at birth, in childhood and in adolescence. Using 37 studies from high-income countries, we performed meta-analysis of epigenome-wide association studies (EWAS) to quantify the associations of completed years of MEA at the time of pregnancy with offspring DNA methylation levels at birth (n = 9 881), in childhood (n = 2 017), and adolescence (n = 2 740), adjusting for relevant covariates. MEA was found to be associated with DNA methylation at 473 cytosine-phosphate-guanine sites at birth, one in childhood, and four in adolescence. We observed enrichment for findings from previous EWAS on maternal folate, vitamin-B12 concentrations, maternal smoking, and pre-pregnancy BMI. The associations were directionally consistent with MEA being inversely associated with behaviours including smoking and BMI. Our findings form a bridge between socio-economic factors and biology and highlight potential pathways underlying effects of maternal education. The results broaden our understanding of bio-social associations linked to differential DNA methylation in multiple early stages of life. The data generated also offers an important resource to help a more precise understanding of the social determinants of health.

Epigenome-wide meta-analysis of prenatal maternal stressful life events and newborn DNA methylation.

Prenatal maternal stressful life events are associated with adverse neurodevelopmental outcomes in offspring. Biological mechanisms underlying these associations are largely unknown, but DNA methylation likely plays a role. This meta-analysis included twelve non-overlapping cohorts from ten independent longitudinal studies (N = 5,496) within the international Pregnancy and Childhood Epigenetics consortium to examine maternal stressful life events during pregnancy and DNA methylation in cord blood. Children whose mothers reported higher levels of cumulative maternal stressful life events during pregnancy exhibited differential methylation of cg26579032 in ALKBH3. Stressor-specific domains of conflict with family/friends, abuse (physical, sexual, and emotional), and death of a close friend/relative were also associated with differential methylation of CpGs in APTX, MyD88, and both UHRF1 and SDCCAG8, respectively; these genes are implicated in neurodegeneration, immune and cellular functions, regulation of global methylation levels, metabolism, and schizophrenia risk. Thus, differences in DNA methylation at these loci may provide novel insights into potential mechanisms of neurodevelopment in offspring.

Factors Influencing Tobacco Smoking and Cessation Among People Living with HIV: A Systematic Review and Meta-analysis.

Tobacco smoking is highly prevalent among people living with HIV (PLWH), yet there is a lack of data on smoking behaviours and effective treatments in this population. Understanding factors influencing tobacco smoking and cessation is crucial to guide the design of effective interventions. This systematic review and meta-analysis of studies conducted in both high-income (HICs) and low- and middle-income countries (LMICs) synthesised existing evidence on associated factors of smoking and cessation behaviour among PLWH. Male gender, substance use, and loneliness were positively associated with current smoking and negatively associated with smoking abstinence. The association of depression with current smoking and lower abstinence rates were observed only in HICs. The review did not identify randomised controlled trials conducted in LMICs. Findings indicate the need to integrate smoking cessation interventions with mental health and substance use services, provide greater social support, and address other comorbid conditions as part of a comprehensive approach to treating tobacco use in this population. Consistent support from health providers trained to provide advice and treatment options is also an important component of treatment for PLWH engaged in care, especially in LMICs.

Reaching High Accuracy for Energetic Properties at Second-Order Perturbation Cost by Merging Self-Consistency and Spin-Opposite Scaling.

Quantum chemical methods dealing with challenging systems while retaining low computational costs have attracted attention. In particular, many efforts have been devoted to developing new methods based on second-order perturbation that may be the simplest correlated method beyond Hartree-Fock. We have recently developed a self-consistent perturbation theory named one-body Møller-Plesset second-order perturbation theory (OBMP2) and shown that it can resolve issues caused by the noniterative nature of standard perturbation theory. In this work, we extend the method by introducing spin-opposite scaling to the double-excitation amplitudes, resulting in the O2BMP2 method. We assess the O2BMP2 performance on the triple-bond N2 dissociation, singlet-triplet gaps, and ionization potentials. O2BMP2 performs much better than standard MP2 and reaches the accuracy of coupled-cluster methods in all cases considered in this work.