Contraceptive experience and factors associated with desire for postpartum family planning among pregnant women of the nkongsamba health district, Littoral Region, Cameroon

Background: The postpartum period remains a very important period during which contraceptive needs can be met and a significant reduction of maternal and foetal morbi-mortality achieved. This study aimed to evaluate past contraceptive experience and identify factors associated with the desire for postpartum family planning among women in late pregnancy. Methods: We conducted a cross-sectional survey from September 2020 to December 2021 in four major health facilities of the Nkongsamba Health District, Cameroon, and consecutively included all pregnant women in late pregnancy, who came for antenatal follow-up in these health facilities. Data were collected using a semi-structured interviewer-administered questionnaire. Multivariable logistic regression was used to estimate adjusted odds ratios (AORs) for the factors associated with desire for postpartum family planning. Two-tailed p-values < 0.05 were considered statistically significant. Results: Among the 1074 participants, 41.71% [95% CI: 38.78–44.70] reported a future desire for modern postpartum contraception. The self-reported prevalence of use of modern contraception in the past in the study population was 48.87% [95%CI: 45.86–51.88]. Only 17.64% [95%CI: 14.59–21.16] of women had adopted a modern contraceptive method other than the barrier methods in the past. Among pregnant women who had used modern contraception in the past, 11.50% [95%CI: 9.02–14.55] reported to have had their modern contraceptive experience with long-acting reversible contraceptives (LARCs). The prevalence of unintended pregnancy (current pregnancy) was 40.04% [37.15-43.00], with 11.55% being unwanted, and 28.49% mistimed. Compared to their respective counterparts, participants ≤ 30 years old (AOR = 0.71[0.52–0.99]), with monthly revenue below 100 thousand FCFA (AOR = 0.45[0.32–0.62]), who were single (AOR = 0.38[0.27–0.54]), had lower odds for desire of postpartum family planning. In contrast, women who were Christians (AOR = 2.13[1.27–3.58]), with a history of use of modern contraception before conception (AOR = 2.80[2.02–3.90]), and had a current unintended term pregnancy had higher odds of desiring postpartum contraception (AOR = 2.91[2.13–3.99]). Conclusion: The desire for postpartum family planning is still low among pregnant women. This desire for postpartum family planning depends on sociodemographic factors and past contraceptive practices

Migration of magnetic microparticles through a liquid–liquid interface under an external magnetic field

Liquid–liquid interfaces play a pivotal role in various microfluidic processes involving microparticles, including coating, dissolution, controlled release of polyelectrolytes or drugs, and self-assembly processes. In all of these cases, non-invasive techniques to manipulate the microparticle transport are essential. Magnetic manipulation offers an accessible and straightforward means of controlling the motion of magnetic particles within microfluidic devices. Magnetic microparticles are commonly used for conformal polyelectrolyte coating and drug encapsulation by passing them through a liquid–liquid interface, due to their high saturation magnetization, stability, and low toxicity. In this work, we draw inspiration from the lack of studies on the behaviour of magnetic particles near a liquid–liquid interface under conditions of low Reynolds numbers and high capillary action, despite its engineering relevance in microfluidic systems. We consider a canonical flow configuration in which particle motion is driven by the stagnation-point flow that is generated when two different liquids flow towards one another. We show how the operating conditions dictate whether the particle will pierce the interface and become coated or not and illustrate this via parameter-space plots. We use the results of this analysis to understand how the operating conditions influence the fraction of particles that pass through the liquid–liquid interface and are conformally coated, which may be used to guide a variety of industrial processes

Bright and stable anti-counterfeiting devices with independent stochastic processes covering multiple length scales

Physical unclonable functions (PUFs) are considered the most promising approach to address the global issue of counterfeiting. Current PUF devices are often based on a single stochastic process, which can be broken, especially since their practical encoding capacities can be significantly lower than the theoretical value. Here we present stochastic PUF devices with features across multiple length scales, which incorporate semiconducting polymer nanoparticles (SPNs) as fluorescent taggants. The SPNs exhibit high brightness, photostability and size tunability when compared to the current state-of-the-art taggants. As a result, they are easily detectable and highly resilient to UV radiation. By embedding SPNs in photoresists, we generate PUFs consisting of nanoscale (distribution of SPNs within microspots), microscale (fractal edges on microspots), and macroscale (random microspot array) designs. With the assistance of a deep-learning model, the resulting PUFs show both near-ideal performance and accessibility for general end users, offering a strategy for next-generation security devices

Vertex model with internal dissipation enables sustained flows

Complex tissue flows in epithelia are driven by intra- and inter-cellular processes that generate, maintain, and coordinate mechanical forces. There has been growing evidence that cell shape anisotropy, manifested as nematic order, plays an important role in this process. Here we extend an active nematic vertex model by replacing substrate friction with internal viscous dissipation, dominant in epithelia not supported by a substrate or the extracellular matrix, which are found in many early-stage embryos. When coupled to cell shape anisotropy, the internal viscous dissipation allows for long-range velocity correlations and thus enables the spontaneous emergence of flows with a large degree of spatiotemporal organisation. We demonstrate sustained flow in epithelial sheets confined to a channel, providing a link between the cell-level vertex model of tissue dynamics and continuum active nematics, whose behaviour in a channel is theoretically understood and experimentally realisable. Our findings also show a simple mechanism that could account for collective cell migration correlated over distances large compared to the cell size, as observed during morphogenesis

Forty years of the Ellis–Baldwin test

Modern cosmology is built on the assumption that the Universe is homogeneous and isotropic on large scales — but this is challenged by results of the Ellis–Baldwin test that show an unexplained anomaly in the distribution of distant galaxies and quasars

Lipid-mediated resolution of inflammation and survival in amyotrophic lateral sclerosis

Neuroinflammation impacts on the progression of amyotrophic lateral sclerosis (ALS), a fatal neurodegenerative disorder. Specialized pro-resolving mediators trigger the resolution of inflammation. We investigate the specialized pro-resolving mediator blood profile and their receptors’ expression in peripheral blood mononuclear cells in relation to survival in ALS. People living with ALS (pwALS) were stratified based on bulbar versus limb onset and on key progression metrics using a latent class model, to separate faster progressing from slower progressing ALS. Specialized pro-resolving mediator blood concentrations were measured at baseline and in one additional visit in 20 pwALS and 10 non-neurological controls (Cohort 1). Flow cytometry was used to study the GPR32 and GPR18 resolvin receptors’ expression in peripheral blood mononuclear cells from 40 pwALS and 20 non-neurological controls (Cohort 2) at baseline and in two additional visits in 17 pwALS. Survival analysis was performed using Cox proportional hazards models, including known clinical predictors and GPR32 and GPR18 mononuclear cell expression. Differential expression and linear discriminant analyses showed that plasma resolvins were able to distinguish phenotypic variants of ALS from non-neurological controls. RvE3 was elevated in blood from pwALS, whilst RvD1, RvE3, RvT4 and RvD1n-3 DPA were upregulated in A-S and RvD2 in A-F. Compared to non-neurological controls, GPR32 was upregulated in monocytes expressing the active inflammation-suppressing CD11b+ integrin from fast-progressing pwALS, including those with bulbar onset disease (P < 0.0024), whilst GPR32 and GPR18 were downregulated in most B and T cell subtypes. Only GPR18 was upregulated in naïve double positive Tregs, memory cytotoxic Tregs, senescent late memory B cells and late senescent CD8+ T cells from pwALS compared to non-neurological controls (P < 0.0431). Higher GPR32 and GPR18 median expression in blood mononuclear cells was associated with longer survival, with GPR32 expression in classical monocytes (hazard ratio: 0.11, P = 0.003) and unswitched memory B cells (hazard ratio: 0.44, P = 0.008) showing the most significant association, along with known clinical predictors. Low levels of resolvins and downregulation of their membrane receptors in blood mononuclear cells are linked to a faster progression of ALS. Higher mononuclear cell expression of resolvin receptors is a predictor of longer survival. These findings suggest a lipid-mediated neuroprotective response that could be harnessed to develop novel therapeutic strategies and biomarkers for ALS

Nonlinear evolution and acceleration of unstable fuel-lean hydrogen/air flame at normal and cryogenic temperatures

Hydrogen is a promising alternative fuel due to its zero-carbon nature. However, safety issues associated with hydrogen storage at cryogenic conditions are a key constrain to its industrial use. Understanding hydrogen flame propagation at cryogenic conditions is essential for ensuring safe hydrogen utilization. Since cryogenic hydrogen flame is prone to both Darrieus-Landau instability (DLI) and diffusional-thermal instability (DTI), it is necessary to evaluate the effects of cryogenic temperature on unstable hydrogen flame propagation and acceleration. In this study, two-dimensional numerical simulations are performed to assess the effects of cryogenic temperature on the nonlinear evolution and acceleration of fuel-lean hydrogen flames. By changing the equivalence ratio, initial temperature and channel size, the intensity of DLI and DTI varies, resulting in various regimes of flame evolution. It is found that cryogenic flames are more unstable than normal flames. For fuel-lean hydrogen flames, DTI leads to chaotic evolution of cellular flame front. In contrast, for stoichiometric or fuel-rich flames without DTI, flames propagate in a steady single-cusp regime. Analyses show that long-term dynamics for fuel-lean flames including cell splitting, merging and lateral movement are caused by flow-flame-chemistry interaction. Moreover, cryogenic temperature leads to profound increase in the local reaction rate for fuel-lean flame, while it shows minimal impact for stoichiometric flame, demonstrating the strong influence of DTI on cryogenic flame structure and acceleration. Accelerative propagation of fuel-lean flames is caused by the combined effects of flame surface area increase and local reaction rate enhancement. Enhancement of flame consumption speed is primarily caused by strong DTI at cryogenic temperature, with a secondary contribution from DLI. Furthermore, results show that in narrow channels flame front evolution and acceleration are sensitive to the domain size. Flame consumption speed changes non-monotonically with channel width and evolves in an oscillatory manner. Results also show that the domain size affects the flame acceleration primarily by constraining the flame surface area increase rather altering the local reaction rate. The present study provides insights to cryogenic hydrogen flame propagation as well as hydrogen safety control

Deep neural networks have an inbuilt Occam’s razor

The remarkable performance of overparameterized deep neural networks (DNNs) must arise from an interplay between network architecture, training algorithms, and structure in the data. To disentangle these three components for supervised learning, we apply a Bayesian picture based on the functions expressed by a DNN. The prior over functions is determined by the network architecture, which we vary by exploiting a transition between ordered and chaotic regimes. For Boolean function classification, we approximate the likelihood using the error spectrum of functions on data. Combining this with the prior yields an accurate prediction for the posterior, measured for DNNs trained with stochastic gradient descent. This analysis shows that structured data, together with a specific Occam’s razor-like inductive bias towards (Kolmogorov) simple functions that exactly counteracts the exponential growth of the number of functions with complexity, is a key to the success of DNNs

On a conjecture of Marton

We prove a conjecture of K. Marton, widely known as the polynomial Freiman–Ruzsa conjecture, in characteristic 2. The argument extends to odd characteristic, with details to follow in a subsequent paper

De novo transcriptome assembly and discovery of drought-responsive genes in white spruce ( Picea glauca )

Forests face an escalating threat from the increasing frequency of extreme drought events driven by climate change. To address this challenge, it is crucial to understand how widely distributed species of economic or ecological importance may respond to drought stress. In this study, we examined the transcriptome of white spruce (Picea glauca (Moench) Voss) to identify key genes and metabolic pathways involved in the species’ response to water stress. We assembled a de novo transcriptome, performed differential gene expression analyses at four time points over 22 days during a controlled drought stress experiment involving 2-year-old plants and three genetically distinct clones, and conducted gene enrichment analyses. The transcriptome assembly and gene expression analysis identified a total of 33,287 transcripts corresponding to 18,934 annotated unique genes, including 4,425 genes that are uniquely responsive to drought. Many transcripts that had predicted functions associated with photosynthesis, cell wall organization, and water transport were down-regulated under drought conditions, while transcripts linked to abscisic acid response and defense response were up-regulated. Our study highlights a previously uncharacterized effect of drought stress on lipid metabolism genes in conifers and significant changes in the expression of several transcription factors, suggesting a regulatory response potentially linked to drought response or acclimation. Our research represents a fundamental step in unraveling the molecular mechanisms underlying short-term drought responses in white spruce seedlings. In addition, it provides a valuable source of new genetic data that could contribute to genetic selection strategies aimed at enhancing the drought resistance and resilience of white spruce to changing climates