Dataset for analysis of metabolic pathways and their reversibility associated with anti-proliferative effect of metformin in liver cancer cells.

Despite epidemiological indications, utility of metformin in liver cancer remains debated and the understanding of the mechanism underlying its anti-cancer effects remains incomplete. Particularly, whether it operates via similar mechanism under glucose-sufficient and glucose- deficient environments or whether these effects are reversible remains unexplored. This metabolomic dataset was collected from liver cancer (HepG2) cells treated with metformin or placebo over a period of 3 h to 48 h as well as from cells recovering after metformin withdrawal. Cells were exposed to placebo or 2.5 mM metformin with or without glucose (5 mM) supplementation. The cells were harvested at 3, 6, 12, 24, and 48 h post-treatment. Cells were also harvested after 24 h of treatment under one of these conditions followed by reversal of glucose and/or metformin exposure status for 48 h. Metabolites from six biological replicates of each experimental group were extracted using chilled monophasic metabolite extraction solvent (Water: Acetonitrile: Isopropanol= 2:3:3) containing homovanillic acid as an internal standard. Samples were derivatized using MOX reagent followed by MSTFA. Untargeted metabolomic profiling of derivatized samples were performed using an Agilent 7890B gas chromatograph coupled to a 5977B single quadrupole mass spectrometer. Analytes were injected through a splitless liner and separated on a HP-5MS ultra-inert column using ultrapure helium as the carrier gas. Peak alignment, annotation, and integration were done using Agilent MassHunter Quantitative analysis software. Multivariate analysis was performed using MetaboAnalyst 5.0. These experiments were performed to unravel the longitudinal evolution of cellular metabolome in response to metformin treatment, its glucose dependence, as well as to examine the reversibility of these changes. The dataset can help to identify glucose-independent pathways involved in anti-cancer effect of metformin. The dataset can be used to design experiments to develop novel therapeutic combinations synergistically acting with metformin to cripple the metabolic fitness of cancer cells. It can also help to develop experiments to test the effect of metformin withdrawal in liver cancer.

Diagnosing and managing prescription opioid use disorder in patients prescribed opioids for chronic pain in Australian general practice settings: a qualitative study using the theory of Planned Behaviour.

BACKGROUND: Chronic pain is a debilitating and common health issue. General Practitioners (GPs) often prescribe opioids to treat chronic pain, despite limited evidence of benefit and increasing evidence of harms, including prescription Opioid Use Disorder (pOUD). Australian GPs are worried about the harms of long-term opioids, but few are involved in the treatment of pOUD. There is little research on GPs' experiences diagnosing and managing pOUD in their chronic pain patients. METHODS: This qualitative research used semi-structured interviews and a case study to investigate GPs' experiences through the lens of the Theory of Planned Behaviour (TPB). TPB describes three factors, an individual's perceived beliefs/attitudes, perceived social norms and perceived behavioural controls. Participants were interviewed via an online video conferencing platform. Interviews were transcribed verbatim and thematically analysed. RESULTS: Twenty-four GPs took part. Participants were aware of the complex presentations for chronic pain patients and concerned about long-term opioid use. Their approach was holistic, but they had limited understanding of pOUD diagnosis and suggested that pOUD had only one treatment: Opioid Agonist Treatment (OAT). Participants felt uncomfortable prescribing opioids and were fearful of difficult, conflictual conversations with patients about the possibility of pOUD. This led to avoidance and negative attitudes towards diagnosing pOUD. There were few positive social norms, few colleagues diagnosed or managed pOUD. Participants reported that their colleagues only offered positive support as this would allow them to avoid managing pOUD themselves, while patients and other staff were often unsupportive. Negative behavioural controls were common with low levels of knowledge, skill, professional supports, inadequate time and remuneration described by many participants. They felt OAT was not core general practice and required specialist management. This dichotomous approach was reflected in their views that the health system only supported treatment for chronic pain or pOUD, not both conditions. CONCLUSIONS: Negative beliefs, negative social norms and negative behavioural controls decreased individual behavioural intention for this group of GPs. Diagnosing and managing pOUD in chronic pain patients prescribed opioids was perceived as difficult and unsupported. Interventions to change behaviour must address negative perceptions in order to lead to more positive intentions to engage in the management of pOUD.

The association of genetic polymorphisms within the dopaminergic system with nicotine dependence: A narrative review.

Nicotine, the main compound in cigarettes, leads to smoking addiction. Nicotine acts on the limbic dopamine reward loop in the midbrain by binding to nicotinic acetylcholine receptors, promoting the release of dopamine, and resulting in a rewarding effect or satisfaction. This satisfaction is essential for continued and compulsive tobacco use, and therefore dopamine plays a crucial role in nicotine dependence. Numerous studies have identified genetic polymorphisms of dopaminergic pathways which may influence susceptibility to nicotine addiction. Dopamine levels are greatly influenced by synthesis, storage, release, degradation, and reuptake-related genes, including genes encoding tyrosine hydroxylase, dopamine decarboxylase, dopamine transporter, dopamine receptor, dopamine 3-hydroxylase, catechol-O-methyltransferase, and monoamine oxidase. In this paper, we review research progress on the effects of polymorphisms in the above genes on downstream smoking behavior and nicotine dependence, to offer a theoretical basis for the elucidation of the genetic mechanism underlying nicotine dependence and future personalized treatment for smoking cessation.

Sex differences in dorsolateral prefrontal cortical and superior colliculus activities support the impact of alcohol use severity and sleep deficiency on two-back memory.

Background: Working memory refers to a process of temporary storage and manipulation of information to support planning, decision-making, and action. Frequently comorbid alcohol misuse and sleep deficiency have both been associated with working memory deficits. However, how alcohol misuse and sleep deficiency interact to impact working memory remains unclear. In this study, we aim to investigate the neural processes inter-relating alcohol misuse, sleep deficiency and working memory. Methods: We curated the Human Connectome Project (HCP) dataset and investigated the neural correlation of working memory in link with alcohol use severity and sleep deficiency in 991 young adults (521 women). The two were indexed by the first principal component (PC1) of principal component analysis of all drinking metrics and Pittsburgh Sleep Quality Index (PSQI) score, respectively. We processed the imaging data with published routines and evaluated the results with a corrected threshold. We used path model to characterize the inter-relationship between the clinical, behavioral, and neural measures, and explored sex differences in the findings. Results: In whole-brain regression, we identified ß estimates of dorsolateral prefrontal cortex response (DLPFC ß) to 2- vs. 0-back in correlation with PC1. The DLPFC showed higher activation in positive correlation with PC1 across men and women (r=0.16, P<0.001). Path analyses showed the model PC1 → DLPFC ß â†’ differences in reaction time (2- minus 0-back; RT2-0) of correct trials → differences in critical success index (2- minus 0-back; CSI2-0) with the best fit. In women alone, in addition to the DLPFC, a cluster in the superior colliculus (SC) showed a significant negative correlation with the PSQI score (r=-0.23, P<0.001), and the path model showed the inter-relationship of PC1, PSQI score, DLPFC and SC ß's, and CSI2-0 in women. Conclusions: Alcohol misuse may involve higher DLPFC activation in functional compensation, whereas, in women only, sleep deficiency affects 2-back memory by depressing SC activity. In women only, path model suggests inter-related impact of drinking severity and sleep deficiency on 2-back memory. These findings suggest potential sex differences in the impact of drinking and sleep problems on working memory that need to be further investigated.

Growing pains with kratom: experiences discussed in subreddits contrast with satisfaction expressed in surveys.

Background: "Kratom" refers to an array of bioactive products derived from Mitragyna speciosa, a tree indigenous to Southeast Asia. Most kratom consumers report analgesic and stimulatory effects, and common reasons for use are to address mental and physical health needs, manage pain, and to reduce use of other substances. Natural-history studies and survey studies suggest that many kratom consumers perceive benefits from those uses, but such studies are unlikely to capture the full range of kratom-use experiences. Methods: We collected text data from Reddit posts from 2020-2022 to qualitatively examine conceptualizations, motivations, effects, and consequences associated with kratom use among people posting to social media. Reddit posts mentioning kratom were studied using template thematic analysis, which included collecting descriptions of kratom product types and use practices. Network analyses of coded themes was performed to examine independent relationships among themes, and between themes and product types. Results: Codes were applied to 329 of the 370 posts that comprised the final sample; 134 posts contained kratom product descriptions. As Reddit accounts were functionally anonymous, demographic estimates were untenable. Themes included kratom physical dependence (tolerance, withdrawal, or use to avoid withdrawal), perceived addiction (net detrimental effects on functioning), and quitting. Extract products were positively associated with reports of perceived addiction, dependence, and experiences of quitting kratom. Many used kratom for energy and self-treatment of pain, fatigue, and problems associated with opioid and alcohol; they perceived these uses as effective. Consumers expressed frustrations about product inconsistencies and lack of product information. Conclusion: As in previous studies, kratom was deemed helpful for some and a hindrance to others, but we also found evidence of notable negative experiences with kratom products that have not been well documented in surveys. Daily kratom use may produce mild-moderate physical dependence, with greater severity being possibly more common with concentrated extracts; however, there are currently no human laboratory studies of concentrated kratom extracts. Such studies, and detailed kratom product information, are needed to help inform consumer decision-making.

Forecasting West Nile Virus With Graph Neural Networks: Harnessing Spatial Dependence in Irregularly Sampled Geospatial Data.

Machine learning methods have seen increased application to geospatial environmental problems, such as precipitation nowcasting, haze forecasting, and crop yield prediction. However, many of the machine learning methods applied to mosquito population and disease forecasting do not inherently take into account the underlying spatial structure of the given data. In our work, we apply a spatially aware graph neural network model consisting of GraphSAGE layers to forecast the presence of West Nile virus in Illinois, to aid mosquito surveillance and abatement efforts within the state. More generally, we show that graph neural networks applied to irregularly sampled geospatial data can exceed the performance of a range of baseline methods including logistic regression, XGBoost, and fully-connected neural networks.

Profiling and assessing the risks of image- and performance-enhancing drugs use during the COVID-19 lockdown.

Background: Image and Performance-Enhancing Drugs (IPEDs) can enhance mental and physical capabilities and impact one's overall health. Initially confined in sport environments, IPEDs use has become increasingly widespread in a high-performing society. The present study was aimed at profiling IPEDs use during the COVID-19 lockdown among an international sample of young adults. Methods: A cross-sectional observational study was carried out in eight countries (United Kingdom, Italy, Lithuania, Hungary, Portugal, Spain, Brazil, and Japan) between April and May 2020. The survey questionnaire included validated measurements such as Exercise Addiction Inventory (EAI), Appearance Anxiety Inventory (AAI), and Self-Compassion Scale (SCS) as well as questions about the type of IPEDs, purchasing methods and socio-demographic information. Results: A total of 736 IPEDs users were included in the survey. Their mean age was 33.05 years (±SD = 10.06), and 64.2% were female participants. Overall, 6.8% were found at risk of exercise addiction (EAI >24), 27.6% presented high levels of appearance anxiety, and 24.9% revealed low levels of emotional regulation's self-compassion. Most participants (55.6%) purchased IPEDs through pharmacies/specialized shops, while 41.3% purchased IPEDs on the Internet. Online IPEDs buyers were mainly men who had higher scores on the Exercise Addiction Inventory. One or more IPEDs classifiable as "potentially risky" were used by 66.3% of the sample. Users of "potentially risky IPEDs" were younger and primarily men. They showed higher scores both on the Exercise Addiction Inventory and Appearance Anxiety Inventory. Conclusion: This study profiled users of IPEDs when the most restrictive COVID-19 lockdown policies were implemented in all the participating countries. More targeted post-COVID 19 prevention strategies should be implemented according to the emerged socio-demographic and psychopathological traits and cross-cultural differences emerged. Longitudinal studies will also be needed to determine the long-term effect of the COVID-19 lockdown on IPEDs consumption.

Glycerol-slaved 1H-1H NMR cross-relaxation in quasi-native lysozyme.

1H-1H nuclear cross-relaxation experiments have been carried out with lysozyme in variable glycerol viscosity to study intramolecular motion, self-diffusion, and isotropic rigid-body rotational tumbling at 298 K, pH 3.8. Dynamics of intramolecular 1H-1H cross-relaxation rates, the increase in internuclear spatial distances, and lateral and rotational diffusion coefficients all show fractional viscosity dependence with a power law exponent κ in the 0.17-0.83 range. The diffusion coefficient of glycerol Ds with the bulk viscosity itself is non-Stokesian, having a fractional viscosity dependence on the medium viscosity (Ds âˆ¼ Î·-κ, κ ≈ 0.71). The concurrence and close similarity of the fractional viscosity dependence of glycerol diffusion on the one hand, and diffusion and intramolecular cross-relaxation rates of the protein on the other lead to infer that relaxation of glycerol slaves protein relaxations. Glycerol-transformed native lysozyme to a quasi-native state does not affect the conclusion that both global and internal fluctuations are slaved to glycerol relaxation.

Packing in multimodal crystals and particle assemblies as models for dynamic packing during spontaneous and enforced particle movement: Settling, viscosity and elasticity.

Colloid particles (CP, 10-8-10-6 m = 10-1000 nm) are used as models for atom scale processes, such as crystallization since the process is experimentally observable. Packing of atoms in crystals resemble mono-, bi-, and trimodal packing of noncharged hard spheres (particles). When the size of one particle exceeds the two others an excluded volume consisting of small particles is created around large particles. This is also the case when colloid particles are dispersed in water. The formation of an excluded volume does not require attraction forces, but it is enforced by the presence of dissolved primary (cations) and secondary (protons of surface hydroxyls) potential determining ions. The outcome is an interfacial solid-liquid charge. This excluded volume, denoted Stern layer is characterized by the surface potential and charge density. Charge neutrality is identified by point of zero charge (pHpzc and pcpzc). Outside Stern layer another excluded volume is formed of loosely bound counterions which interact with Stern layer. The extent of this diffuse layer is given by inverse Debye length and effective ζ-potential. The overall balance between attractive and repulsive energies is provided by Derjaguin-Landau-Veerwey-Overbeek (DLVO) model. Charge neutrality is identified at isoelectric point (pHiep and pciep). The dependence of viscosity and yield stress on shear rate may be modeled by von Smoluchowski's volumetric collision frequency multiplied by some total interaction energy given by DLVO model. Equilibrium and dynamic models for settling and enforced particle movement (viscosity) are presented. Both compressive yield stress (sedimentation) and cohesive energy (viscoelasticity) are characterized by power law exponents of volume fraction. The transition of disperse suspensions (sols) to spanning clusters (gels) is identified by oscillatory rheology. The slope of linear plots of logarithmic storage (G´) and loss (G") moduli against logarithm of frequency or logarithm of volume fraction provide power law exponents from the slopes. These exponents relate to percolation and fractal dimensions characterizing the particle network. Moreover, it identifies the structure formation process either as diffusion limited cluster-cluster (DLCCA) or as reaction limited cluster-cluster (RLCCA) aggregation.

Analytical Calculation of Relationship Temperature and Fatigue and Creep Strength Based on Thermal Activation.

The purpose of this study was to formulate a mathematical expression for the temperature dependence of adhesive strength using various parameters. Adhesive structures are typically exposed to a broad temperature range, spanning from low to high temperatures; therefore, understanding how their strength depends on temperature is crucial. The strength was measured through tensile, fatigue, and creep tests at temperatures ranging from -60 °C to 135 °C. The properties of these test types were thoroughly investigated by analyzing the strength of the test results from a thermal activity perspective. The results demonstrate that there is a clear relationship between temperature and strength. The intensity decreased with temperature according to the exponential function and could be accurately represented using the parameters of thermal activity. The temperature at which the strength begins to decrease in the fatigue test was higher than in the static tests. Consequently, we were able to accurately express the relationship between the temperature and intensity using certain parameters. Few studies successfully developed a precise nonlinear relationship between temperature and intensity using approximate expressions.

Competitive interactions affect introgression and population viability amidst maladaptive hybridization.

The deliberate release of captive-bred individuals, the accidental escape of domesticated strains, or the invasion of closely related conspecifics into wild populations can all lead to introgressive hybridization, which poses a challenge for conservation and wildlife management. Rates of introgression and the magnitude of associated demographic impacts vary widely across ecological contexts. However, the reasons for this variation remain poorly understood. One rarely considered phenomenon in this context is soft selection, wherein relative trait values determine success in intraspecific competition for a limiting resource. Here we develop an eco-genetic model explicitly focussed on understanding the influence of such competitive interactions on the eco-evolutionary dynamics of wild populations experiencing an influx of foreign/domesticated individuals. The model is applicable to any taxon that experiences natural or human-mediated inputs of locally maladapted genotypes ('intrusion'), in addition to phenotype-dependent competition for a limiting resource (e.g. breeding sites, feeding territories). The effects of both acute and chronic intrusion depended strongly on the relative competitiveness of intruders versus locals. When intruders were competitively inferior, density-dependent regulation limited their reproductive success (ability to compete for limited spawning sites), which prevented strong introgression or population declines from occurring. In contrast, when intruders were competitively superior, this amplified introgression and led to increased maladaptation of the admixed population. This had negative consequences for population size and population viability. The results were sensitive to the intrusion level, the magnitude of reproductive excess, trait heritability and the extent to which intruders were maladapted relative to locals. Our findings draw attention to under-appreciated interactions between phenotype-dependent competitive interactions and maladaptive hybridization, which may be critical to determining the impact captive breeding programmes and domesticated escapees can have on otherwise self-sustaining wild populations.

Voltage dependence of M2 muscarinic receptor antagonists and allosteric modulators.

Muscarinic receptors are G protein-coupled receptors (GPCRs) that play a role in various physiological functions. Previous studies have shown that these receptors, along with other GPCRs, are voltage-sensitive; both their affinity toward agonists and their activation are regulated by membrane potential. To our knowledge, whether the effect of antagonists on these receptors is voltage-dependent has not yet been studied. In this study, we used Xenopus oocytes expressing the M2 muscarinic receptor (M2R) to investigate this question. Our results indicate that the potencies of two M2R antagonists, atropine and scopolamine, are voltage-dependent; they are more effective at resting potential than under depolarization. In contrast, the M2R antagonist AF-DX 386 did not exhibit voltage-dependent potency.Furthermore, we discovered that the voltage dependence of M2R activation by acetylcholine remains unchanged in the presence of two allosteric modulators, the negative modulator gallamine and the positive modulator LY2119620. These findings enhance our understanding of GPCRs' voltage dependence and may have pharmacological implications.

The neural representation of stereotype content.

Judgments about social groups are characterized by their position in a representational space defined by two axes, warmth and competence. We examined serial dependence (SD) in evaluations of warmth and competence while measuring participants' electroencephalographic (EEG) activity, as a means to address the independence between these two psychological axes. SD is the attraction of perceptual reports towards things seen in the recent past and has recently been intensely investigated in vision. SD occurs at multiple levels of visual processing, from basic features to meaningful objects. The current study aims to (1) measure whether SD occurs between non-visual objects, in particular social groups and (2) uncover the neural correlates of social group evaluation and SD using EEG. Participants' judgments about social groups such as "nurses" or "accountants" were serially dependent, but only when the two successive groups were close in representational space. The pattern of results argues in favor of a non-separability between the two axes, because groups nearby on one dimension but far on the other were not subject to SD, even though that other dimension was irrelevant to the task at hand. Using representational similarity analysis, we found a brain signature that differentiated social groups as a function of their position in the representational space. Our results thus argue that SD may be a ubiquitous cognitive phenomenon, that social evaluations are serially dependent, and that reproducible neural signatures of social evaluations can be uncovered.

Prospective multicenter study of the epidemiological features of emergency patients with overdose of over-the-counter drugs in Japan.

Aim: To investigate the epidemiological characteristics of patients presenting to the emergency department with an overdose of over-the-counter (OTC) drugs. Methods: A questionnaire survey was conducted to examine the sociodemographic characteristics of patients with OTC drugs overdoses visiting emergency departments at eight sites across the country. The patients were divided into "habitual" and "nonhabitual" groups according to their history of OTC drugs overdose. Student's t-test or Welch's t-test was performed for numerical variables, and Pearson's χ 2 test was performed for dichotomous and nominal variables between the two groups. Results: Of the 124 patients included in this study, 79% were women. The habitual (26.6%) and the nonhabitual (73.4%) groups showed no differences in sex, occupation, cohabitants, history of mental illness, or history of alcohol consumption or smoking; however, those in the habitual group were significantly younger. The proportion of OTC drugs obtained from physical stores was higher in the habitual group, whereas the nonhabitual group used more household medicines. Suicide and self-harm were more common reasons for overdose in the nonhabitual group. Antipyretic analgesics were significantly more common in the nonhabitual group, whereas antitussive expectorants and antihistamines were significantly more common in the habitual group. Conclusion: This is the first multicenter study to determine the status of OTC drugs overdose patients treated at emergency departments of medical facilities in Japan. To prevent new overdoses of OTC drugs, continued detailed epidemiologic studies of patient backgrounds and drug acquisition routes, and investigation of the components of OTC drugs that cause dependency are necessary.

Photodegradation of Organic Solar Cells under Visible Light and the Crucial Influence of Its Spectral Composition.

While wavelength-dependent photodegradation of organic solar cells (OSCs) under visible light is typically discussed in terms of UV/blue light-activated phenomena, we recently demonstrated wavelength-dependent degradation rates up to 660 nm for PM6:Y6. In this study, we systematically investigated this phenomenon for a broad variety of devices based on different donor:acceptor combinations. We found that the spectral composition of the light used for degradation, tuned in a spectral range from 457 to 740 nm and under high irradiances of up to 30 suns, has a crucial influence on the device stability of almost all tested semiconductors. The relevance of this phenomenon was investigated in the context of simulated AM1.5 illumination with metal halide lamps and white LEDs. It is concluded that the current stability testing protocols in OSC research have to be adjusted to account for this effect to reveal the underlying physics of this still poorly understood mechanism.

Breaking down barriers: rationalisations and motivation to stop among Chinese male smokers under cigarette dependence.

BACKGROUND: Smoking rationalisation beliefs are a huge barrier to quitting smoking. What types of rationalisations should be emphasised in smoking cessation interventions? Although past literature has confirmed the negative relationship between those beliefs and motivation to stop smoking, little is known regarding the importance and performance of those beliefs on motivation with varying cigarette dependence. The study aimed to ascertain rationalisations that are highly important for motivation yet perform poorly in different cigarette dependence groups. METHODS: The cross-sectional study was conducted from November 19 to December 9, 2023 in Guiyang City, China. Adult male current smokers were enrolled. Partial least squares structural equation modelling was used to test the hypothesis. The multi-group analysis was used to determine the moderating effect of cigarette dependence, and the importance-performance map analysis was utilised to assess the importance and performance of rationalisations. RESULTS: A total of 616 adult male current smokers were analysed, and they were divided into the low cigarette dependence group (n = 297) and the high cigarette dependence group (n = 319). Except for risk generalisation beliefs, smoking functional beliefs (H1: -ß = 0.131, P < 0.01), social acceptability beliefs (H3: ß = -0.258, P < 0.001), safe smoking beliefs (H4: ß = -0.078, P < 0.05), self-exempting beliefs (H5: ß = -0.244, P < 0.001), and quitting is harmful beliefs (H6: ß = -0.148, P < 0.01) all had a significant positive influence on motivation. Cigarette dependence moderated the correlation between rationalisations and motivation. In the high-dependence group, the social acceptability beliefs and smoking functional beliefs were located in the "Concentrate Here" area. In the low-dependence group, the social acceptability beliefs were also situated in there. CONCLUSIONS: Social acceptability beliefs and smoking functional beliefs showed great potential and value for improvement among high-dependence smokers, while only social acceptability beliefs had great potential and value for improvement among low-dependence smokers. Addressing these beliefs will be helpful for smoking cessation. The multi-group analysis and the importance-performance map analysis technique have practical implications and can be expanded to other domains of health education and intervention practice.

Clinical Reasoning and Challenges Faced With Onset Psychotic Symptoms in a Case of Combined Huntington's Disease and Gayet-Wernicke Encephalopathy.

Physicians are occasionally confronted with patients presenting psychotic symptoms of organic origin. Therefore, precision in diagnosing the organic basis is pivotal for targeted treatment, addressing the underlying etiology. This case study delineates the nuanced phases of clinical reasoning employed to ascertain a diagnosis of Huntington's disease (HD), notably amidst concurrent alcohol dependence. A comprehensive clinical examination and meticulous review of the patient's medical history served as linchpins in guiding subsequent investigations toward identifying the etiological underpinnings of the psychotic symptomatology. Furthermore, this case sheds light on the uncommon overlap of HD and Wernicke's encephalopathy, compounding diagnostic complexities, especially given the polymorphic nature of HD. The diagnostic intricacies needed precise analysis of the clinical picture and a deep understanding of potential interactions between neurological pathologies and the deleterious effects of alcoholism on the nervous system.

Predicting anion diffusion in bentonite using hybrid machine learning model and correlation of physical quantities.

Radionuclide diffusion will be influenced by numerous factors. Establishing a model that can elucidate the internal correlation between mesoscopic diffusion and the microscopic structure of bentonite can enhance the comprehension of radionuclide diffusion mechanisms. In this study, a light gradient boosting machine (LightGBM) was employed to predict the effective diffusion coefficients of HCrO4-, I-, and CoEDTA2- in bentonite. The model's hyperparameters were optimized using the particle swarm optimization (PSO) algorithm. Several correlated physical quantities, such as mesoscopic parameters (total porosity, rock capacity factor, and ion molar conductivity) and microscopic parameters (ionic radius and montmorillonite stacking number) were incorporated to develop a machine learning model that incorporated micro- and meso-scale features. The predictive performance of PSO-LightGBM was verified using diffusion experiments, which investigated the diffusion of HCrO4-, I-, and CoEDTA2- at compacted dry densities of 1200-1800 kg/m3 using a through-diffusion method. Spearman correlation and Shapley additive explanation analyses revealed that the compacted dry density, ionic diffusion coefficient in water, ionic radius, and total porosity were the top-four influencing factors among the 16 input features. Partial dependence plot analysis elucidated the relationship between the effective diffusion coefficient and each input feature. The analysis results were consistent with the experimental findings, demonstrating the reliability of machine learning. Due to the incorporation of multi-scale features, the PSO-LightGBM model demonstrated enhanced predictive accuracy, linking the microstructure of bentonite to radionuclide diffusion, and providing a comprehensive interpretation of the diffusion mechanism.

Commentary: The microbial dependence continuum: Towards a comparative physiology approach to understand host reliance on microbes.

Comparative physiologists often compare physiological traits across organisms to understand the selective pressures influencing their evolution in different environments. Traditionally focused on the organisms themselves, comparative physiology has more recently incorporated studies of the microbiome-the communities of microbes living in and on animals that influence host physiology. In this commentary, we describe the utility of applying a comparative framework to study the microbiome, particularly in understanding how hosts vary in their dependence on microbial communities for physiological function, a concept we term the "microbial dependence continuum". This hypothesis suggests that hosts exist on a spectrum ranging from high to low reliance on their microbiota. Certain physiological traits may be highly dependent on microbes for proper function in some species but microbially independent in others. Comparative physiology can elucidate the selective pressures driving species along this continuum. Here, we discuss the microbial dependence continuum in detail and how comparative physiology can be useful to study it. Then, we discuss two example traits, herbivory and flight, where comparative physiology has helped reveal the selective pressures influencing host dependence on microbial communities. Lastly, we discuss useful experimental approaches for studying the microbial dependence continuum in a comparative physiology context.

Dynamics of visual attention in exploration and exploitation for reward-guided adjustment tasks.

The learning process encompasses exploration and exploitation phases. While reinforcement learning models have revealed functional and neuroscientific distinctions between these phases, knowledge regarding how they affect visual attention while observing the external environment is limited. This study sought to elucidate the interplay between these learning phases and visual attention allocation using visual adjustment tasks combined with a two-armed bandit problem tailored to detect serial effects only when attention is dispersed across both arms. Per our findings, human participants exhibited a distinct serial effect only during the exploration phase, suggesting enhanced attention to the visual stimulus associated with the non-target arm. Remarkably, although rewards did not motivate attention dispersion in our task, during the exploration phase, individuals engaged in active observation and searched for targets to observe. This behavior highlights a unique information-seeking process in exploration that is distinct from exploitation.