Search Results (1,674)

Arsenic, the 20th most common element in Earth’s crust and historically regarded as the King of Poisons, occurs naturally in two oxidation states, Arsenate (V) and Arsenite (III), and is prevalent worldwide through natural and anthropogenic means. The cations of the metalloid exhibit unique chemical behaviour in water and are found to be components of approximately 245 natural minerals, making its occurrence in drinking water a compelling challenge, especially in groundwater. This comprehensive review collates information regarding the prevalence of arsenic contamination in water worldwide and its impact on human health, its chemical behaviour, methods for detection and quantification, and treatment strategies. A comprehensive search was conducted, and the selection of eligible studies was carried out using the PRISMA (the preferred reporting items for systematic reviews and meta-analyses) guidelines. Essential characteristics of eligible research studies were extracted based on geographical areas, origins, concentration levels and the magnitude of populations vulnerable to arsenic contamination in groundwater sources. Arsenic contamination of water affects over 100 countries including Canada, the United States, Pakistan, China, India, Brazil and Bangladesh, where hydrogeological conditions favour prevalence and groundwater is the primary water source for food preparation, irrigation of food crops and drinking water. This leads to human exposure through absorption, ingestion and inhalation, causing numerous health disorders affecting nearly all systems within the human body, with acute and chronic toxicity including cancers. The presence of arsenic in water poses a considerable challenge to humanity, prompting scientists to devise diverse mitigation approaches categorized as (a) oxidation processes, (b) precipitation methods, (c) membrane technologies, (d) adsorption and ion exchange methods, and (e) social interventions. This comprehensive review is expected to be a valuable source for professionals in the water industry, public management, and policymaking, aiding their ongoing and future research and development efforts. Full article

Lung cancer is the leading cause of death among all the oncological diseases worldwide. This applies to both women and men; however, the incidence and mortality among women is on the rise. In 2020, lung cancer was responsible for 1.8 million deaths (18%). More than 90% of lung cancer cases and 77.1% of lung cancer deaths occur in countries with high and very high HDI (human development index) values. The aim of our study is to the present trends and most recent studies aimed at lung cancer screening. In the face of the persistently high mortality rate, conducting research aimed at extending already-implemented diagnostic algorithms and behavioural interventions focused on smoking cessation is recommended. Full article

Dental anthropology provides a deep insight into biological, ecological and cultural aspects associated with human individuality, behaviour and living conditions and the environment. Our study uses a correlation analysis to test the metric relationships between tooth sizes and jaw dimensions and juxtaposes them with biological sex and stature. A sample of n = 100 dental casts was used to record metric dental data including the mesio-distal and bucco-lingual tooth crown diameters and nine upper and lower jaw dimensions. All crown diameters were highly correlated with both stature and biological sex, with the canines exhibiting the highest correlation. The majority of jaw dimensions exhibited similar correlations. Our results suggest that the differences between the sexes in most crown diameters and some jaw dimensions may be related to the stature of the individuals measured. Two groups of closely correlating features emerged among the jaw dimensions, differing in their degree of correlation with crown diameters and with sex. The results and insights obtained are highly relevant for evolutionary biology, dentistry, craniofacial research, bioarchaeology and forensic odontology. Full article

In contrast to plants, humans are unable to synthesise carotenoids and have to obtain them from diet. Carotenoids fulfil several crucial biological functions in the organism; however, due to poor solubility in water, their bioavailability from plant-based food is low. The processes of carotenoid absorption and availability in the human body have been intensively studied. The recent experimental findings concerning these processes are briefly presented in the introductory part of this review, together with a summary of such topics as carotenoid carriers, body transport and tissue delivery, to finally report on molecular-level studies of carotenoid binding by membrane receptors. The main message of the review is contained in the section describing computational investigations of carotenoid intercalation and dynamic behaviour in lipid bilayers. The relevance of these computational studies lies in showing the direct link between the microscopic behaviour of molecules and the characteristics of their macroscopic ensembles. Furthermore, studying the interactions between carotenoids and lipid bilayers, and certainly proteins, on the molecular- and atomic-level using computational methods facilitates the interpretation and explanation of their macroscopic properties and, hopefully, helps to better understand the biological functions of carotenoids. Full article

Major depressive disorder (MDD) is a complex and devastating illness that affects people of all ages. Despite the large use of antidepressants in current medical practice, neither their mechanisms of action nor the aetiology of MDD are completely understood. Experimental evidence supports the involvement of Parvalbumin-positive GABAergic neurons (PV-neurons) in the pathogenesis of MDD. DLX5 and DLX6 (DLX5/6) encode two homeodomain transcription factors involved in cortical GABAergic differentiation and function. In the mouse, the level of expression of these genes is correlated with the cortical density of PV-neurons and with anxiety-like behaviours. The same genomic region generates the lncRNA DLX6-AS1, which, in humans, participates in the GABAergic regulatory module downregulated in schizophrenia and ASD. Here, we show that the expression levels of Dlx5/6 in the adult mouse brain are correlated with the immobility time in the forced swim test, which is used to measure depressive-like behaviours. We show that the administration of the antidepressant fluoxetine (Flx) to normal mice induces, within 24 h, a rapid and stable reduction in Dlx5, Dlx6 and Dlx6-AS1 expression in the cerebral cortex through the activation of the TrkB-CREB pathway. Experimental Dlx5 overexpression counteracts the antidepressant effects induced by Flx treatment. Our findings show that one of the short-term effects of Flx administration is the reduction in Dlx5/6 expression in GABAergic neurons, which, in turn, has direct consequences on PV expression and on behavioural profiles. Variants in the DLX5/6 regulatory network could be implicated in the predisposition to depression and in the variability of patients’ response to antidepressant treatment. Full article

Promoting healthy eating improves both planetary and human health, aligning with sustainable development goals. Eating healthy, locally sourced foods that are rich in nutrients and low in energy density produces benefits for public health in the long term and enhances resource sustainability. Despite the importance of increasing intake of fresh fruits and vegetables, consumers still frequently choose pre-packaged foods, making packaging design crucial in influencing food choice and intake as well as promoting healthy diets. Designers of food packaging are in a crucial position to contribute to health and well-being by influencing consumer knowledge, attitudes and behaviours towards healthy eating. However, designers may yet be unaware of their potential to influence and the challenges they may face in this domain. This study investigates designers’ perspectives, understandings, needs and challenges regarding packaging design for promoting healthy eating. A total of 20 designers (n = 10 professionals, 10 students) from various design backgrounds participated in this study, engaging in a packaging design task (centred on either reducing intake of high-energy density foods or increasing intake of fruits and vegetables), followed by one-to-one interviews. A thematic analysis of the interviews revealed that the designers primarily focused on enhancing the healthiness of food items through packaging design but often overlooked the potential to regulate consumer intake of energy-dense foods. In addition, the designers expressed concerns regarding consumer preferences and market acceptance for such designs. They faced significant challenges in accessing relevant resources and emphasised the need for health-related information, data on packaging impacts and consumer preferences, practical design examples and theoretical support. These findings highlight the demand for additional support to enable designers to develop tailored packaging designs, contributing to a supportive environment for promoting healthy eating. Full article

Simulated body fluid (SBF) and artificial saliva (AS) are used in biomedical and dental research to mimic the physiological conditions of the human body. In this study, the biomimetic precipitation of double-doped amorphous calcium phosphate in SBF and AS are compared by thermodynamic modelling of chemical equilibrium in the SBF/AS-CaCl₂-MgCl₂-ZnCl₂-K₂HPO₄-H₂O and SBF/AS-CaCl₂-MgCl₂-ZnCl₂-K₂HPO₄-Glycine/Valine-H₂O systems. The saturation indices (SIs) of possible precipitate solid phases at pH 6.5, close to pH of AS, pH 7.5, close to pH of SBF, and pH 8.5, chosen by us based on our previous experimental data, were calculated. The results show possible precipitation of the same salts with almost equal SIs in the two biomimetic environments at the studied pHs. A decrease in the saturation indices of magnesium and zinc phosphates in the presence of glycine is a prerequisite for reducing their concentrations in the precipitates. Experimental studies confirmed the thermodynamic predictions. Only X-ray amorphous calcium phosphate with incorporated Mg (5.86–8.85 mol%) and Zn (0.71–2.84 mol%) was obtained in the experimental studies, irrespective of biomimetic media and synthesis route. Solid-state nuclear magnetic resonance (NMR) analysis showed that the synthesis route affects the degree of structural disorder of the precipitates. The lowest concentration of dopant ions was obtained in the presence of glycine. Further, the behaviour of the selected amorphous phase in artificial saliva was studied. The dynamic of Ca²⁺, Mg²⁺, and Zn²⁺ ions between the solid and liquid phases was monitored. Both direct excitation ³¹P NMR spectra and ¹H-³¹P CP-MAS spectra proved the increase in the nanocrystalline hydroxyapatite phase upon increasing the incubation time in AS, which is more pronounced in samples with lower additives. The effect of the initial concentration of doped ions on the solid phase transformation was assessed by solid-state NMR. Full article

Even from infancy, a human’s day-life alternates from a period of wakefulness to a period of sleep at night, during the 24-hour cycle. Sleep is a normal process necessary for human physical and mental health. A lack of sleep makes it difficult to control emotions and behaviour, reduces productivity at work, and can even increase stress or depression. In addition, poor sleep affects health; when sleep is insufficient, the chances of developing serious diseases greatly increase. Researchers in sleep medicine have identified an extensive list of sleep disorders, and thus leveraged Artificial Intelligence (AI) to automate their analysis and gain a deeper understanding of sleep patterns and related disorders. In this research, we seek a Machine Learning (ML) solution that will allow for efficient classification of unlabeled instances as being Sleep Apnea, Insomnia or Normal (subjects without a specific sleep disorder) by assessing the performance of two well-established strategies for multi-class classification tasks: the One-Vs-All (OVA) and One-Vs-One (OVO). In the context of the specific strategies, two well-known binary classification models were assumed, Logistic Regression (LR) and Support Vector Machines (SVMs). Both strategies’ validity was verified upon a dataset of diverse information related to the profiles (anthropometric data, sleep metrics, lifestyle and cardiovascular health factors) of potential patients or individuals not exhibiting any specific sleep disorder. Performance evaluation was carried out by comparing the weighted average results in all involved classes that represent these two specific sleep disorders and no-disorder occurrence; accuracy, kappa score, precision, recall, f-measure, and Area Under the ROC curve (AUC) were recorded and compared to identify an effective and robust model and strategy, both class-wise and on average. The experimental evaluation unveiled that after feature selection, 2-degree polynomial SVM under both strategies was the least complex and most efficient, recording an accuracy of 91.44%, a kappa score of 84.97%, precision, recall and f-measure equal to 0.914, and an AUC of 0.927. Full article

Experimental protocols are fundamental for quantifying the mechanical behaviour of soft tissue. These data are crucial for advancing the understanding of soft tissue mechanics, developing and calibrating constitutive models, and informing the development of more accurate and predictive computational simulations and artificial intelligence tools. This paper offers a comprehensive review of experimental tests conducted on soft aortic tissues, employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, based on the Scopus, Web of Science, IEEE, Google Scholar and PubMed databases. This study includes a detailed overview of the test method protocols, providing insights into practical methodologies, specimen preparation and full-field measurements. The review also briefly discusses the post-processing methods applied to extract material parameters from experimental data. In particular, the results are analysed and discussed providing representative domains of stress–strain curves for both uniaxial and biaxial tests on human aortic tissue. Full article

Biomechanical characteristics can be used to assist the early detection of many diseases, including breast cancer, thyroid nodules, prostate cancer, liver fibrosis, ovarian diseases, and tendon disorders. In this paper, a scale-dependent viscoelastic model is developed to assess the biomechanical behaviour of biological tissues subject to flexural waves. The nonlocal strain gradient theory, in conjunction with machine learning techniques such as extreme gradient boosting, k-nearest neighbours, support vector machines, and random forest, is utilised to develop a computational platform for biomechanical analysis. The coupled governing differential equations are derived using Hamilton’s law. Transverse wave analysis is conducted to investigate different normal and pathological human conditions including ovarian cancer, breast cancer, and ovarian fibrosis. Viscoelastic, strain gradient, and nonlocal effects are used to describe the impact of fluid content, stiffness hardening caused by the gradients of strain components, and stiffness softening associated with the nonlocality of stress components within the biological tissues and cells. The integration of the scale-dependent biomechanical continuum model with machine learning facilitates the adoption of the developed model in practical applications by allowing for learning from clinical data, alongside the intrinsic mechanical laws that govern biomechanical responses. Full article

Paradoxical decision-making behaviours such as preference reversal often arise from imprecise or noisy human preferences. Harnessing the physical principle of magnetisation reversal in ferromagnetic nanostructures, we developed a model that closely reflects human decision-making dynamics. Tested against a spectrum of psychological data, our model adeptly captures the complexities inherent in individual choices. This blend of physics and psychology paves the way for fresh perspectives on understanding the imprecision of human decision-making processes, extending the reach of the current classical and quantum physical models of human behaviour and decision making. Full article

Sediments are sources and sinks of heavy metals in water, and estuaries are heavily influenced by human production and life. Therefore, it is of great significance to study the composition of estuarine sediments and the relationship between their components to understand the transport and transformation pathways of heavy metals in the environment. In this research, we investigated the characteristics and patterns of Zn adsorption by organic–inorganic composites, organic–clay mineral composites, and iron oxide–clay mineral composites in eight estuarine sediment samples from Dianchi Lake. The results show that both Langmuir and Freundlich isothermal models can describe the adsorption behaviour of the adsorbent better. The order of the adsorption capacity of the three groups of samples for zinc was organic–inorganic composites > organic–clay mineral composites > iron oxide–clay mineral composites. Through FTIR and XRD analyses, the adsorption of Zn²⁺ on the three groups of samples was dominated by electrostatic attraction and coordination adsorption, accompanied by the occurrence of ion exchange and co-precipitation. After FTIR semi-quantitative analysis, it was found that the source of the differences in the high and low Zn adsorption of the three types of samples may be mainly due to the content of phenolic functional groups in the organic matter. This may be related to the low redox site of the phenolic hydroxyl group, which, as an electron donor, is susceptible to electrostatic attraction and complexation with heavy metal cations. The organic–inorganic composite has a higher adsorption capacity for Zn when the ratio of the active fraction of organic matter to the free iron oxide content is 0.65–0.70. In this range, the organic matter can provide enough negative charge without making the sample surface too dense. Iron oxides can also activate the sample by providing sufficient contact between the clay minerals and the organic matter. When this ratio is too high or too low, it will be unfavourable for Zn adsorption. Full article

Medical and agricultural robots that interact with living tissue or pick fruit require tactile and flexible sensors to minimise or eliminate damage. Until recently, research has focused on the development of robots made of rigid materials, such as metal or plastic. Due to their complex configuration, poor spatial adaptability and low flexibility, rigid robots are not fully applicable in some special environments such as limb rehabilitation, fragile objects gripping, human–machine interaction, and locomotion. All these should be done in an accurate and safe manner for them to be useful. However, the design and manufacture of soft robot parts that interact with living tissue or fragile objects is not as straightforward. Given that hyper-elasticity and conductivity are involved, conventional (subtractive) manufacturing can result in wasted materials (which are expensive), incompatible parts due to different physical properties, and high costs. In this work, additive manufacturing (3D printing) is used to produce a conductive, composite flexible sensor. Its electrical response was tested based on various physical conditions. Finite element analysis (FEA) was used to characterise its deformation and stress behaviour for optimisation to achieve functionality and durability. Also, a nonlinear regression model was developed for the sensor’s performance. Full article

Road transport systems kill millions of animals on every inhabited continent each year, and thousands of human lives are lost. Odour repellents (ORE) are a WVC mitigation measure which have been extensively applied across central Europe to prevent or minimise the number of ungulate–vehicle collisions (UVCs). OREs aim to increase the vigilance of ungulates near roads and therefore change their behaviour in areas where vehicle collisions may occur. Despite many scientific papers on the topic of odour repellent effectiveness, a lack of behavioural studies means there is still little understanding of the mechanism of ORE functionality. OREs are applied as an area repellent, so their effectiveness is influenced by multiple factors, and constantly discussed by both academics and the lay public. This paper summarises the state of knowledge about application and effectiveness of odour repellents in road ecology, and suggests research questions to fill information gaps. Full article

Many people wonder whether biology, including humans, will benefit or experience harm from new developments in information such as artificial intelligence (AI). Here, it is proposed that biological and non-biological information might be components of a unified process, ‘Panevolution’ or ‘Pan-Evo’, based on four basic operations—innovation, transmission, adaptation, and movement. Pan-Evo contains many types of variable objects, from molecules to ecosystems. Biological innovation includes mutations and behavioural changes; non-biological innovation includes naturally occurring physical innovations and innovation in software. Replication is commonplace in and outside biology, including autocatalytic chemicals and autonomous software replication. Adaptation includes biological selection, autocatalytic chemicals, and ‘evolutionary programming’, which is used in AI. The extension of biological speciation to non-biological information creates a concept called ‘Panspeciation’. Panevolution might benefit or harm biology, but the harm might be minimal if AI and humans behave intelligently because humans and the machines in which an AI resides might split into vastly different environments that suit them. That is a possible example of Panspeciation and would be the first speciation event involving humans for thousands of years. This event will not be particularly hostile to humans if humans learn to evaluate information and cooperate better to minimise both human stupidity and artificial simulated stupidity (ASS—a failure of AI). Full article