Breast cancer is the leading cause of cancer among women and remains one of the most prevalent contributors to cancer-related mortality worldwide. This study aims to evaluate biomarker expression in women with breast cancer and the correlations between them and other prognostic parameters. A retrospective analysis of 252 subjects was conducted at the Oncology Department of Mother Teresa University Hospital in Albania between 2021 and 2024. The highest rate of the disease was observed in the over-45 age group (92.5%). A family history of cancer was reported in 13.9% of patients. The most common histological type identified was ductal carcinoma (81.3%), which predominantly affected the left breast (57.1%) and was most frequently stage 2 (69.8%). A significant association (p < 0.001) was found between disease stage and expression of ER (Estrogen Receptors), PR (Progesterone Receptors), and HER2 (Human Epidermal Growth Factor Receptor 2), as well as between patient age and expression of ER, PR, and HER2 receptors (p = 0.02). HER2 and Ki-67 expression were inversely associated with ER and PR. Ki-67 was significantly correlated with age (p = 0.008) and stage (p < 0.001). Nodal metastasis correlated with Ki-67 (p = 0.02) and ER (p = 0.01).
Henrik Häggström, Sebastian Persson, Marija Cvijovic
et al.
The analysis of data from multiple experiments, such as observations of several individuals, is commonly approached using mixed-effects models, which account for variation between individuals through hierarchical representations. This makes mixed-effects models widely applied in fields such as biology, pharmacokinetics, and sociology. In this work, we propose a novel methodology for scalable Bayesian inference in hierarchical mixed-effects models. Our framework first constructs amortized approximations of the likelihood and the posterior distribution, which are then rapidly refined for each individual dataset, to ultimately approximate the parameters posterior across many individuals. The framework is easily trainable, as it uses mixtures of experts but without neural networks, leading to parsimonious yet expressive surrogate models of the likelihood and the posterior. We demonstrate the effectiveness of our methodology using challenging stochastic models, such as mixed-effects stochastic differential equations emerging in systems biology-driven problems. However, the approach is broadly applicable and can accommodate both stochastic and deterministic models. We show that our approach can seamlessly handle inference for many parameters. Additionally, we applied our method to a real-data case study of mRNA transfection. When compared to exact pseudomarginal Bayesian inference, our approach proved to be both fast and competitive in terms of statistical accuracy.
Shaheena Umbreen, Naila Mukhtar, Nidaa Harun
et al.
ABSTRACT Salvadora faces a significant threat of being in decline in semi‐arid regions. This study investigates the distribution status of Salvadora species in semi‐arid habitats, moreover examines how habitat types, climatic conditions and soil variability influence plant's functional traits and distribution. The study was organized in the semi‐arid lowlands of the Sahiwal Division, Pakistan. Field surveys were conducted from 2021 to 2023 across 51 sites comprised of four types of habitats, i.e., archaeological sites, graveyards, roadsides, and railway lines. Principal Component Analysis (PCA) and Canonical Correspondence Analysis (CCA) were applied to examine the impact of habitat types and environmental variables on Salvadora distribution. Two species of Salvadora, i.e., Salvadora persica Linn and Salvadora oleoides Decne, were identified taxonomically in the study area. S. persica was found to be more abundant than S. oleoides. These results recommend that S. persica was more dominant in most sites except for Sahiwal, where both species had similar densities. The number of tree trunks, tree height, and leaf size, leaf biomass are some of the dominant traits that were influenced by habitat variability. Other factors like temperature, precipitation, th soil's pH and moisture levels play important roles in species distribution within these habitats. Despite Salvadora notable economic and ecological importance, its ecological situation is critical because of overexploitation, climate change, and habitat destruction. To ensure that Salvadora continues to exist and perform its ecological functions in its natural habitat, protecting and managing strategies need to be planned and enforced.
Simplicity is held by many to be the key to general intelligence. Simpler models tend to "generalise", identifying the cause or generator of data with greater sample efficiency. The implications of the correlation between simplicity and generalisation extend far beyond computer science, addressing questions of physics and even biology. Yet simplicity is a property of form, while generalisation is of function. In interactive settings, any correlation between the two depends on interpretation. In theory there could be no correlation and yet in practice, there is. Previous theoretical work showed generalisation to be a consequence of "weak" constraints implied by function, not form. Experiments demonstrated choosing weak constraints over simple forms yielded a 110-500% improvement in generalisation rate. Here we show that all constraints can take equally simple forms, regardless of weakness. However if forms are spatially extended, then function is represented using a finite subset of forms. If function is represented using a finite subset of forms, then we can force a correlation between simplicity and generalisation by making weak constraints take simple forms. If function is determined by a goal directed process that favours versatility (e.g. natural selection), then efficiency demands weak constraints take simple forms. Complexity has no causal influence on generalisation, but appears to due to confounding.
Numerical difference computation is one of the cores and indispensable in the modern digital era. Tao general difference (TGD) is a novel theory and approach to difference computation for discrete sequences and arrays in multidimensional space. Built on the solid theoretical foundation of the general difference in a finite interval, the TGD operators demonstrate exceptional signal processing capabilities in real-world applications. A novel smoothness property of a sequence is defined on the first- and second TGD. This property is used to denoise one-dimensional signals, where the noise is the non-smooth points in the sequence. Meanwhile, the center of the gradient in a finite interval can be accurately location via TGD calculation. This solves a traditional challenge in computer vision, which is the precise localization of image edges with noise robustness. Furthermore, the power of TGD operators extends to spatio-temporal edge detection in three-dimensional arrays, enabling the identification of kinetic edges in video data. These diverse applications highlight the properties of TGD in discrete domain and the significant promise of TGD for the computation across signal processing, image analysis, and video analytic.
Nektaria-Ioanna Karma, Fotini Mellou, Panagoula Pavlou
et al.
It is well established that marine organisms consist of a great variety of active compounds that appear exclusively in the marine environment while having the ability to be vastly reproduced, irrespective of the existing conditions. As a result, marine organisms can be used in many scientific fields, including the ones of pharmaceutics, nutrition, and cosmetic science. As for the latter, marine ingredients have been successfully included in cosmetic formulations for many decades, providing numerous benefits for the skin. In the present review, the contribution of marine compounds in wound healing is thoroughly discussed, focusing on their role both as active ingredients in suitable formulations, designed to contribute to different stages of skin regeneration and restoration and also, indirectly, as a tool for facilitating wound closure as part of a wound dressing. Additionally, the advantages of these marine ingredients are presented, as well as ways of incorporating them effectively in formulations, so as to enhance their performance. Numerous studies have been referenced, showcasing their efficacy in wound healing. Finally, important data in regard to their stability, limitations, and challenges to their use, safety issues, and the existing legislative framework are extensively reviewed.
Tahir Abbas KHAN, Hadiqa HASSAN, Haocheng WANG
et al.
Drought stress poses a significant challenge to agriculture sustainability across the globe. Drought stress negatively affects the plant growth and productivity and the intensity of this serious abiotic stress is continuously increasing which is a serious threat across the globe. Different measures are being used to mitigate the adverse impacts of drought stress. Among these measures, the application of exogenous osmolytes and growth hormones is considered an important way to mitigate the adverse impacts of drought. Recently, jasmonic acid (JA) has emerged as an excellent growth hormone to improve drought tolerance owing to its involvement in different plant physiological and biochemical processes. Jasmonic acid improves membrane stability plant water relations, nutrient uptake, osmolyte accumulation, and antioxidant activities that can counter the toxic effects of drought. It also contributes to signaling pathways, i.e., genes network, stress-responsive proteins, signaling intermediates, and enzymes that protect the plants from the toxic effects of drought. Further, JA also protects and maintains the integrity of plant cells by up-regulating the antioxidant defense system and increasing osmolyte accumulation. In this review, we have documented the protective role of JA under drought stress. The various mechanisms of JA in inducing drought tolerance are discussed and different research gaps are also identified. This review will help the readers to learn more about the role of JA to mitigate the toxic effects of drought and it will provide new knowledge to develop the drought tolerance in plants.
Odhran O'Donoghue, Aleksandar Shtedritski, John Ginger
et al.
The ability to automatically generate accurate protocols for scientific experiments would represent a major step towards the automation of science. Large Language Models (LLMs) have impressive capabilities on a wide range of tasks, such as question answering and the generation of coherent text and code. However, LLMs can struggle with multi-step problems and long-term planning, which are crucial for designing scientific experiments. Moreover, evaluation of the accuracy of scientific protocols is challenging, because experiments can be described correctly in many different ways, require expert knowledge to evaluate, and cannot usually be executed automatically. Here we present an automatic evaluation framework for the task of planning experimental protocols, and we introduce BioProt: a dataset of biology protocols with corresponding pseudocode representations. To measure performance on generating scientific protocols, we use an LLM to convert a natural language protocol into pseudocode, and then evaluate an LLM's ability to reconstruct the pseudocode from a high-level description and a list of admissible pseudocode functions. We evaluate GPT-3 and GPT-4 on this task and explore their robustness. We externally validate the utility of pseudocode representations of text by generating accurate novel protocols using retrieved pseudocode, and we run a generated protocol successfully in our biological laboratory. Our framework is extensible to the evaluation and improvement of language model planning abilities in other areas of science or other areas that lack automatic evaluation.
Dlovan Ali Jalal, Barna Vásárhelyi, Béla Blaha
et al.
Introduction: Hemoglobin A1c (HbA1c) is used to monitor glucose homeostasis and to identify risk for diabetes. As diabetic patients are frequently present with dyslipidaemia, low-grade inflammation and hyperuricemia, we tested whether HbA1c levels can be estimated having the information about lipid profile, uric acid (UA) and C-reactive protein (CRP) levels. We developed formulas to describe the association of these parameters with HbA1c levels. Methods: Data of 9599 male and 10,817 female patients, measured between 2008 and 2018, were analysed. Patients represented a general hospital patient population with overrepresentation of those with elevated HbA1c over 5.6%. The impact of gender, age, CRP, lipid profile and UA levels on HbA1c % on HbA1c levels was tested with multiple linear regression model. The magnitude of effects of individual factors was used to develop formulas to describe the association between HbA1c and other cardiometabolic parameters. With these formulas we estimated median HbA1c values in each age in both gender and compared them to measured HbA1c levels. Results: The developed formulas are as follow: HbA1c (estimated) in women = 0.752 + 0.237*log10(HDL/cholesterol) + 0.156*log10 (cholesterol) + 0.077*log10 (triglyceride) + 0.025*log10(CRP) +0.001*log10 (age) −0.026*log10(HDL/LDL) −0.063*log10 (uric acid)-0.075*log10 (LDL)-0.199*log10(HDL); HbA1c (estimated) in men = 1.146 + 0.08*log10 (triglyceride) + 0.046*log10(CRP) + 0.01*log10 (cholesterol) + 0.001*log10 (age) −0.014*log10(HDL)-0.018*log10(HDL/LDL)-0.025*log10(HDL/cholesterol) −0.068*log10 (LDL)-0.159*log10 (uric acid)Between 20 and 70 years of age, estimated HbA1c matched perfectly to measured HbA1c in. Conclusion: At population level, HbA1c levels can be estimated almost exactly based on lipid profile, CRP and uric acid levels in female patients between 20 and 70 years.
Yuquan W. Zhang, Bruce A. McCarl, Zhengwei Cao
et al.
Pesticide use in peri-urban areas affects the urban environment and public health, and reducing the use may present food security issues for urban dwellers. In this study, we explore how a municipality-adopted goal of a 20% reduction in pesticide use could be achieved, along with local food security and environmental implications, for Shanghai located in the densely populated East China. A regional Shanghai Agricultural Sector Model incorporating district- and technology-varying crop budgets, was developed to simulate the effects of pesticide reduction policy. Here we find that achieving the reduction goal had the largest implications in districts with high pesticide use totals and intensities, potentially reducing pesticide non-point source pollution in the Yangtze River Estuary and Dianshan Lake; the production levels of rice and leafy vegetables would be most affected; and adopting machinery that allows more precise pesticide application modulates these results. Moreover, imposing the requirements at the district-level caused more severe local food security concerns, and less environmental benefits. Furthermore, a closed Shanghai's agricultural economy would substantially enlarge the regional heterogeneity in the above-mentioned outcomes. Exploring the effects of a quantity control policy on current-use pesticides at different aggregation levels has important implications for regulating the use of agrochemicals.
Abstract Background Understanding the synergetic and antagonistic effects of combinations of drugs and toxins is vital for many applications, including treatment of multifactorial diseases and ecotoxicological monitoring. Synergy is usually assessed by comparing the response of drug combinations to a predicted non-interactive response from reference (null) models. Possible choices of null models are Loewe additivity, Bliss independence and the recently rediscovered Hand model. A different approach is taken by the MuSyC model, which directly fits a generalization of the Hill model to the data. All of these models, however, fit the dose–response relationship with a parametric model. Results We propose the Hand-GP model, a non-parametric model based on the combination of the Hand model with Gaussian processes. We introduce a new logarithmic squared exponential kernel for the Gaussian process which captures the logarithmic dependence of response on dose. From the monotherapeutic response and the Hand principle, we construct a null reference response and synergy is assessed from the difference between this null reference and the Gaussian process fitted response. Statistical significance of the difference is assessed from the confidence intervals of the Gaussian process fits. We evaluate performance of our model on a simulated data set from Greco, two simulated data sets of our own design and two benchmark data sets from Chou and Talalay. We compare the Hand-GP model to standard synergy models and show that our model performs better on these data sets. We also compare our model to the MuSyC model as an example of a recent method on these five data sets and on two-drug combination screens: Mott et al. anti-malarial screen and O’Neil et al. anti-cancer screen. We identify cases in which the HandGP model is preferred and cases in which the MuSyC model is preferred. Conclusion The Hand-GP model is a flexible model to capture synergy. Its non-parametric and probabilistic nature allows it to model a wide variety of response patterns.
Computer applications to medicine. Medical informatics, Biology (General)
Urbanization has induced substantial changes in soil physicochemical characteristic, which plays an important role in regulating soil fauna biodiversity in forests and grasslands. However, less is known about the urbanization effect on soil fauna biodiversity and how soil physicochemical changes mediate this effect. Along an urbanization gradient in the city of Guangzhou, we established four sites with different urbanization intensities, including an urban site, two suburban sites, and a rural site, and then studied their soil physicochemical characteristic and soil fauna biodiversity. The soil physicochemical characteristic dramatically changed along the urbanization gradient. In contrast, the soil fauna biodiversity exhibited a very different pattern. Soil fauna abundance was highest in the suburban sites. Moreover, there were significant changes of Pielou’s evenness and community structure in the suburban sites. Soil fauna biodiversity property in the urban site was similar to that in the rural site, except that the rural site was characterized by Enchytraeidae while the urban site was not characterized by any taxa. Our linear and canonical correspondence analysis models suggested that soil physicochemical characteristic only contributed a little to the variance of soil fauna abundance (19%), taxa number (27%), and community structure (12%). In contrast, soil physicochemical characteristic explained about half of the variance in Shannon’s diversity and Pielou’s evenness. However, with urbanization intensity increasing, soil physicochemical changes could both increase and decrease the diversity and evenness. Thus, our results revealed an inconsistent pattern between soil fauna biodiversity and soil physicochemical characteristic along an urbanization gradient. This study suggested that soil physicochemical change was less important as expected in regulating soil fauna biodiversity pattern under an urbanization context. To elucidate the effect of urbanization on soil fauna biodiversity, further studies should take other urbanization agents into account.
Algirdas Juozapaitis, Giedrė Sandovič, Ronaldas Jakubovskis
et al.
Stress-ribbon systems develop the most flexible and slender bridges. A structural system of such elegant bridges consists of cables or ribbons and deck slabs placed to these strips to distribute the live load. Although this structural system is simple, the design of such structures is a challenging issue. Design limitations of the bridge deck slope induce considerable forces in the ribbons, which transfer the tension to massive foundations. The deformation increase under concentrated and asymmetrical loads causes another problem of stress-ribbon bridges—the kinematic component, the design object of such structures, exceeds the dead load-induced vertical displacement several times. This paper introduces a new concept of such a structural system, comprising ribbons made of flexural-stiff profiles. The proposed approach to reduce kinematic displacements is illustrated experimentally by testing two pedestrian bridge prototypes with different flexural stiffness of the steel ribbons. Numerical models calibrated using the test results are used for the parametric analysis of the flexural stiffness effect on the deformation behaviour of the bridge system with steel and fibre-reinforced polymer (FRP) ribbons. A practical approach to the choice of the efficient flexural stiffness of the ribbon-profiles is also proposed.
Sex differences in early age mortality have been explained in prior literature by differences in biological make-up and gender discrimination in the allocation of household resources. Studies estimating the effects of these factors have generally assumed that offspring sex ratio is random, which is implausible in view of recent evidence that the sex of a child is partly determined by prenatal environmental factors. These factors may also affect child health and survival in utero or after birth, which implies that conventional approaches to explaining sex differences in mortality are likely to yield biased estimates. We propose a methodology for decomposing these differences into the effects of prenatal environment, child biology, and parental preferences. Using a large sample of twins, we compare mortality rates in male-female twin pairs in India, a region known for discriminating against daughters, and sub-Saharan Africa, a region where sons and daughters are thought to be valued by their parents about equally. We find that: (1) prenatal environment positively affects the mortality of male children; (2) biological make-up of the latter contributes to their excess mortality, but its effect has been previously overestimated; and (3) parental discrimination against female children in India negatively affects their survival; but failure to control for the effects of prenatal and biological factors leads conventional approaches to underestimating its effect by 237 percent during infancy, and 44 percent during childhood.