Browse Articles

Coexisting maternal and child undernutrition in Ethiopia: Spatial modeling and multilevel analysis of consecutive EDHS data

Introduction Maternal and child undernutrition remains a major public health challenge globally, with the highest burdens observed in low- and middle-income countries. Coexisting maternal and child undernutrition has serious implications for survival, growth, and quality of life.Maternal and child undernutrition is a complex, multifactorial issue influenced by a web of interconnected determinants including health, socio-economic status, education and environmental conditions. Objectives To examine the spatial distribution and multilevel determinants of coexisting maternal and child undernutrition in Ethiopia using EDHS data from 2000–2016. Methods We analyzed a weighted sample of 33,445 participants from four consecutive EDHS surveys. Spatial autocorrelation, hotspot, and interpolation analyses were conducted using ArcMap 10.8. Multilevel logistic regression was performed in Stata 17. Cluster variability was assessed using ICC, MOR, and PCV. Variables with p < 0.05 were considered statistically significant. Result A total of 33,445 weighted sample was used for this study. The prevalence of coexisting maternal and child undernutrition was 22.87% (95% CI: 22.42, 23.32). Spatial analysis result showed that hot spot areas were concentrated in the northern regions especially Tigray, Amhara, and parts of Benishangul-Gumuz. Multilevel logistics regression analysis result revealed that maternal primary education (AOR = 0.88; 95% CI: 0.78, 0.98), secondary/higher education (AOR = 0.38; 95% CI: 0.29, 0.49), medium household wealth (AOR = 0.85; 95% CI: 0.75, 0.97), high household wealth (AOR = 0.78; 95% CI: 0.69, 0.89), child age 12–23 months (AOR = 2.77; 95% CI: 2.44, 3.16), ANC use (AOR = 0.83; 95% CI: 0.75, 0.92), improved toilet (AOR = 0.83; 95% CI: 0.71, 0.98) and regions. Conclusion and recommendations Coexisting maternal and child undernutrition shows marked geographic clustering in northern Ethiopia. Strengthening maternal education, improving household economic conditions, enhancing ANC use, and expanding sanitation services particularly in high-risk regions are essential to reduce the burden.

Energy efficient clustering protocol in wireless sensor networks using an adaptive hybrid optimization algorithm

A class of COPI cargo receptors regulates processing of transmembrane proteins by reinforcing their Golgi retention

Many transmembrane (TM) signaling receptors undergo essential posttranslational modification in the Golgi prior to their delivery to the plasma membrane (PM). Whether and how the passage and accompanied modification of these proteins across the Golgi is controlled remains unclear. Here, we show that leptin receptor overlapping transcript (LEPROT) and LEPROT-like 1 (LEPROTL1) regulate TM receptor activation by securing their sufficient Golgi retention. LEPROTs localize to cis and medial Golgi in a coat protein complex I (COPI)-dependent manner. LEPROTs interact directly with COPI coats and simultaneously engage a variety of integral membrane proteins with relatively long TM domains at acidic pH. Deletion of LEPROTs in cells causes expedited release of TM receptors transiting through the Golgi. Loss of LEPROTs dysregulates receptor signaling activity, including that of epidermal growth factor receptor (EGFR) and transferrin receptor (TFRC), due to defective modification. Collectively, LEPROTs serve as a class of COPI cargo receptors for TM receptors, ensuring adequate preparation, which is vital for subsequent action on the PM.

The socioeconomic impact of inherited retinal dystrophies (IRDs) in Belgium: A cost-of-illness study

Introduction Inherited retinal diseases (IRDs) are a diverse group of vision-threatening conditions caused by genetic mutations, affecting over 5.5 million people globally. These diseases have profound impact on patients, families and society. However, there is a lack of comprehensive data on their prevalence, economic burden, and societal costs. This information gap hinders effective decision-making, and the allocation of resources needed for research, treatment, and patient support, ultimately compromising care and outcomes. Objective To quantify the societal burden of IRDs in Belgium in 2023 Methods This cost-of-illness study estimated the total costs of the 11 most prevalent IRDs in Belgium. A survey of Belgian IRD patients collected primary data on disease burden, health resource utilization, productivity, and care-related expenses. Additionally, data on prevalence and health system costs were based on a literature review from PubMed and the Cochrane Library. Results Patients reported a substantial impact on daily activities (96%), mental health (81%), and 78% reported having received genetic testing. IRDs impose a significant economic burden in Belgium, with an average annual cost of €37,228 per patient and a total cumulative burden of €129.4 million. Indirect non-healthcare costs represented the largest proportion (84%), followed by direct healthcare costs (12%), mainly from rehabilitation, and direct non-healthcare costs (4%). Indirect costs included significant productivity losses of €77.7 million and an informal care burden of €31.3 million. Government support programmes accounted for €4.9 million annually. Conclusion This study highlights the substantial clinical and economic burden of IRDs on Belgian society. Therefore, it is important to continue investing in research and development, as well as to consider the substantial societal impact of these conditions in decision-making and shaping policy changes for Belgium. Future investments informed by these findings can contribute to decreasing the burden on society and enhance the well-being, inclusion and productivity of patients and caregivers.

UV-C irradiation enhances the antimicrobial and Anti-Inflammatory bioactivity of ginseng oil

Application of FT-NIR spectroscopy to the prediction of Chromium contamination in soil by evolutionary chemometrics

Fourier-transform near-Infrared (FT-NIR) technology offers a promising alternative to traditional methods for detecting soil Chromium (Cr) contamination. However, the relationship between soil Cr content and the spectra may involve complex non-linear dynamics and data redundancy. Therefore, selecting spectral feature variables and constructing parametric scaling models for rapid estimation has become a focal point in current research. In this study, the parametric scaling support vector machine (PSSVM) method is proposed for optimizing the modeling parameters, the binary modified differential evolution (BDE) algorithm is designed for selecting the feature variables. In combination, a novel combined optimization system is established by embedding the PSSVM model into the BDE iterative process. The system (BDE-PSSVM) is validated by estimating the soil Cr content based on the FT-NIR spectral data. The soil samples are collected from the area around a centralized waste treatment base, serving as the research subject. The original spectral data underwent preprocessing using Savitzky-Golay smoothing. Subsequently, the samples were divided into the training and testing sets by the SPXY algorithm, where the testing samples are strictly excluded from the model training process. Feature selection and the parametric scaling model optimization are simultaneously performed by applying the BDE-PSSVM model. The most optimal model observes the minimal root mean square error of 8.114, which only carries 56 discrete variables. In comparison to some other counterpart modeling methods, the BDE-PSSVM uses less feature variables and yields the better prediction results. This finding indicates that the proposed BDE-PSSVM modeling system provides an efficient way for rapid estimation of soil Cr content in cooperation with the FT-NIR technology. The proposed system is expected to undergo testing for its application in detecting additional analytes.

Characteristics of motor polyneuropathy in Fabry disease: a case-control study

Force-dependent structural dynamics of the giant nesprin-2

The nesprin protein family serves as a critical physical bridge between the cytoskeleton–a fundamental structural scaffold and mechanotransduction hub of the cell, and the nucleus–an intriguing and emerging mechanoresponsive element. Due to the external mechanical cues and the nucleo-cytoskeletal dynamics, the nesprins are physiologically under forces. However, the dynamics of nesprins within physiological forces and loading rates remain largely unexplored. In this study, we employ magnetic-tweezers-based single-molecule manipulation alongside molecular dynamic simulations and AlphaFold structural predictions to comprehensively investigate the dynamics of force-bearing spectrin repeat (SR) domains of the giant nesprin-2 protein. Through direct quantification, we unveil that the numerous SRs undergo mechanical unfolding and refolding dynamics with distinct transition rates within several pN scale. Furthermore, we show that the giant nesprin-2 could act as an effective molecular absorber adeptly maintaining forces on the nucleoskeleton and cytoskeleton linkage within a few pN across displacement spans exceeding one μm. Notably, our findings imply that subtle pN-level mechanical forces intricately modulate nesprin–protein interactions via the dynamics of domain folding and unfolding. Collectively, our study offers a comprehensive understanding of the mechanical characteristics of nesprin-2 giant, shedding light on its pivotal role in nucleoskeleton–cytoskeleton mechanotransduction.

Tritium in vegetation at various types of radioactive contamination sites under arid climate conditions

This article presents research findings on tritium ( 3 H) in plants at the Semipalatinsk Test Site (STS), including the perimeter of the ‘Degelen’ site, the riverside zone of the Shagan River, and a conditionally ‘background’ area—the southeastern part of the STS (SEP). The 3 H content in plants was determined in tritiated free water (TFWT) and organically bound 3 H (OBT). Plant samples were measured using an ultra-low-level liquid scintillation spectrometer. Maximum 3 H concentrations in plants were detected at the ‘Degelen’ site (TFWT up to 51 ± 5 kBq/kg, ОBТ up to 15 ± 1 kBq/kg) and Shagan River (TFWT up to 39 ± 4 kBq/kg, ОBТ up to 13 ± 1 kBq/kg). The presence of 3 H was recorded not only at underground nuclear sites but also in the conditionally ‘background’ area (TFWT up to 0.18 ± 0.02 kBq/kg, ОBТ up to 0.088 ± 0.028 kBq/kg). Research suggests that water plays a key role in 3 H migration processes in the natural system of interest. The OBT/TFWT values for the study area varied on average from 0.3 to 0.7. The dose rate of internal irradiation of the studied plants varied from 6.3 × 10 −6 (SEP) to 1.2 × 10 −2 µGy/day (at the boundary of the ‘Degelen’ site), which is significantly lower than the safe exposure level for biota.

Flow cytometry helps differentiate between mucous membrane pemphigoid and erosive oral lichen planus

Protein language models trained on biophysical dynamics inform mutation effects

Structural dynamics are fundamental to protein functions and mutation effects. Current protein deep learning models are predominantly trained on sequence and/or static structure data, which often fail to capture the dynamic nature of proteins. To address this, we introduce SeqDance and ESMDance, two protein language models trained on dynamic biophysical properties derived from molecular dynamics simulations and normal mode analyses of over 64,000 proteins. Both models can be directly applied to predict dynamic properties of unseen ordered and disordered proteins. SeqDance, trained from scratch, has attentions that capture dynamic interaction and comovement between residues, and its embeddings encode rich representations of protein dynamics that can be further utilized to predict conformational properties beyond the training tasks via transfer learning. SeqDance predicted dynamic property changes reflect mutation effect on protein folding stability. ESMDance, built upon ESM2 (Evolutionary Scale Model II) outputs, substantially outperforms ESM2 in zero-shot prediction of mutation effects for designed and viral proteins which lack evolutionary information. Together, SeqDance and ESMDance offer a framework for integrating protein dynamics into language models, enabling more generalizable predictions of protein behavior and mutation effects.

Exploration of a workflow for the classification and identification of co-purified protein complexes yields new structures and multiple MSP assembly states

Native protein complexes have garnered interest as targets for structural dissemination. Cryogenic electron microscopy (cryo-EM) with its ability to image protein mixtures is the most promising tool to enable structural proteomics. Additionally, image processing has evolved and can deal with conformational and compositional heterogeneity. Integrative approaches, namely mass spectrometry in conjunction with cryo-EM, have made it possible to characterize and identify complex mixtures. However, this comes at a cost of generating models and interpreting mass spectra. Here we present a modified approach that builds on publicly available software. By generating maps around 4 Å and unsupervised model building we were able to identify the most abundant proteins in our sample. This sample consisted of co-purified membrane proteins in nanodiscs. We found a novel structure and unexpected nanodisc assemblies. Our maps imply a direct interaction between membrane proteins and membrane scaffolding proteins.

A semi-analytical approach for solving a fractional-order mathematical model of skin cell damage and repair driven by environmental pollutants

Generalizations of the quadratic bound optimization principle

The quadratic bound (QB) principle proposed by Böhning and Lindsay in 1988 is an important special case of the majorization–minimization or minorization-maximization optimization principle. The quadratic upper-bound (QUB) principle is pertinent to minimization; the analogous quadratic lower-bound principle is pertinent to maximization. Unfortunately, in minimizing a loss f ( θ ) , the QUB principle is limited by the difficulty of finding a constant positive definite matrix B such that B − d 2 f ( θ ) is positive semidefinite for all θ . This paper proposes a generalization of the QB principle that avoids this limitation. In particular, we construct QUB algorithms by replacing the matrix B by a continuous matrix-valued function B n ( θ ) that dominates the Hessian d 2 f ( θ ) and depends on the both the current iterate θ n and the next potential iterate θ . In practice, we require B n ( θ ) to be diagonal with its diagonal entries separated in θ . In other words, the i th diagonal entry of B n ( θ ) depends on θ only through its i th entry θ i . Theoretical analysis confirms that this class of generalized QB algorithms enjoys global convergence in favorable circumstances. For the scalar case, the tangency condition that the second derivative equals the bound function at the current point promotes superlinear convergence. Several numerical experiments implemented in Julia illustrate the power of the generalized QB principle.

Impact of level of nutritional dose and diet specific components of colostrum in promoting 24 h gain, circulating lipid profile, and circulating levels of immunocrit, proteins, glucose, and free amino acids in neonatal gilt piglets

Colostrum (COL) intake relates to growth trajectory of pigs, which may be driven by differences in nutrient level, bioactive factors, or both. This study’s objective was to determine the effect of feeding COL versus milk replacer (MR) at high and low doses [20% or 10% of birth body weight (BBW)] on 24 h weight gain, body temperature, circulating levels of glucose, protein, immunocrit, free amino acids, lipids and small metabolites. At birth, gilt piglets (n = 57) were assigned to: pooled COL fed at 20% (COL20) or 10% of BBW (COL10); MR fed at 20% (MR20) or 10% of BBW (MR10); stay on sow (SOS) to suckle COL; or immediately euthanized at birth (zero hour; ZH). COL20, COL10, MR20, and MR10 were bottle fed diets every 2 h for 24 h, then piglets were euthanized, and blood collected. Serum samples were analyzed for glucose and protein using a colorimetric assay, immunocrit using the immunocrit ratio, free amino acids using liquid chromatography mass spectrometry, and lipidome using multiple reaction monitoring profiling. Dose affected glucose ( P  = 0.02), being greater in 20% treatments than 10%. Diet and dose impacted immunocrit ( P  < 0.0001) and protein ( P  = 0.04), being highest in COL20, intermediate in COL10, and lowest in MR treatments. Diet type impacted all free amino acids ( P  < 0.05). Diet and dose impacted concentration of triacylglycerols ( P  = 0.0003), cholesterol esters (diet P  = 0.001; dose P  = 0.05), and only diet impacted phospholipids ( P  = 0.04). Diet impacted individual triacylglycerol profile, with fatty acids longer and more unsaturated in COL than MR. Piglets on SOS, COL20, MR20 gained weight and maintained rectal temperature, whereas COL10 and MR10 lost weight and had lower temperatures ( P  < 0.05). These data and previous studies indicate colostral proteins remain intact post-absorption preventing use for energy. Due to relatively high lactose in MR and circulating metabolite profiles, we postulated piglets fed MR prioritized glycolysis to support growth, whereas COL-fed depended on fatty acid oxidation. Further studies are warranted to understand how absorptive and post-absorptive metabolism respond to diet type and dose and contribute to circulating profiles of nutrients and metabolites.

Neural network approach enhancing churn prediction with categorical encoding and standard scaling

MTFR1L is a cardiac antiaging factor for maintenance of mitochondrial homeostasis

Mitochondrial dysfunction is a hallmark of aging and a key contributor to age-related diseases including cardiovascular disease. However, molecular pathways that safeguard mitochondrial homeostasis in the aging heart remain poorly understood. Here, we identify MTFR1L as a regulator of mitophagy that binds p-S65-Ub, a key signal amplifying the PINK1/Parkin axis. We find that MTFR1L is enriched in metabolically active tissues, particularly in the heart, where it regulates Parkin signaling. Genetic deletion of Mtfr1l in mice impairs stress-induced mitophagy and Parkin activation, leading to accumulation of damaged mitochondria, increased inflammation and senescence, and accelerated age-related cardiac dysfunction. Strikingly, cardiac expression of MTFR1L progressively decreases along with aging in mice, primates, and humans, coinciding with cardiomyocyte senescence and lipofuscin accumulation. Together, these findings uncover a role for MTFR1L in regulation of the p-S65-Ub/Parkin mitophagy axis and maintenance of mitochondrial homeostasis during cardiac aging and suggest that age-associated loss of MTFR1L may contribute to age-related cardiac dysfunction. Based on these findings, we propose a therapeutic paradigm for the prevention of heart aging by restoring MTFR1L function.

Backward cloud transformation algorithm based on Kullback Leibler divergence

As a bidirectional cognitive model for dealing with uncertainty, cloud model (CM) are commonly used in application scenarios such as fault diagnosis, system modeling, and evaluation. CM achieves bidirectional conversion between qualitative concepts and quantitative values through forward cloud transformation (FCT) and backward cloud transformation (BCT) algorithms. Among them, the BCT algorithm obtains key parameters that characterize the randomness and fuzziness of concepts through the analysis of quantitative sample data, namely the expectation ( Ex ), entropy ( En ), and hyper entropy ( He ) for CM. However, the existing BCT algorithms adopt an integrated modeling approach, ignoring the impact of data with different distribution characteristics on obtaining key parameters for CM. Therefore, this paper proposes a BCT algorithm based on Kullback Leibler (KL) divergence, aiming to refine the process for obtaining key parameters of CM by analyzing the distribution differences between sample data. Firstly, the corresponding atomization template dataset (ATD) is obtained by conducting a coarse-grained analysis of the sample data. Then, calculate the KL divergence between sample data and ATD to effectively evaluate the atomization state of CM after transforming the sample data. Based on the evaluation results, two differentiated BCT strategies are designed for both atomization and non-atomization states to obtain key parameters of CM. Finally, a comparative analysis is conducted between the proposed method and traditional BCT algorithms, using the University of California Irvine (UCI) benchmark dataset and real fault diagnosis data for error analysis. The experimental results indicate that the proposed method can obtain more accurate key parameters of CM than other BCT algorithms.

A Q-learning-based hybrid search algorithm integrating PRM and ACO for 3D UAV path planning

Gpr171 regulates embryonic hematopoietic stem cell emergence via ERK1/2 and Notch signaling

Hematopoietic stem cells (HSCs), which sustain lifelong blood cell production, emerge from hemogenic endothelium during embryonic development through the regulation of multiple signaling pathways. However, generating functional HSCs in vitro remains challenging, underscoring gaps in understanding the underlying mechanisms. Here, we identify GPR171, a P2Y-family G-protein-coupled receptor (GPCR), as a critical regulator of vertebrate embryonic HSC specification. Gpr171 is highly expressed in hemogenic endothelium and hematopoietic stem and progenitor cells. A deficiency in Gpr171 results in severe embryonic HSC deficits but does not impair vasculogenesis and primitive hematopoiesis. We further find that its endogenous ligand, coded by pcsk1nl , cooperates with Gpr171 to enhance HSC generation. Mechanistically, Gpr171 activates ERK1/2 and Notch signaling pathways independently and synergistically to promote HSC generation. Pharmacological treatment of zebrafish embryos with the human GPR171 ligand BigLEN significantly increases HSC numbers. Moreover, GPR171 signaling is evolutionarily conserved, as GPR171-deficient murine embryos also exhibit a significant reduction in functional HSCs. Overall, our findings reveal GPR171 as an evolutionarily conserved regulator of embryonic HSC specification and suggest its potential for translational applications in stem cell–based therapeutics.