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‘Expansion microscopy’ turns ten: how a tissue-swelling method brought super-resolution imaging to the masses

Correction: The last giants: New evidence for giant Late Triassic (Rhaetian) ichthyosaurs from the UK

PhD parents: the pros and cons of having a child during your doctorate

Analysis of key parameters influencing the permeability of cement sheath based on multiphysical fields

This paper develops a finite element analysis model to investigate the seepage characteristics of cement sheaths, considering the flow properties of their porous medium. The model’s applicability under various conditions was evaluated through grid sensitivity tests and model validation, indicating that it effectively captures the seepage behavior of cement sheaths with a reasonable degree of reliability. Key parameters, including cement sheath length, permeability, gap structure, pressure differential, and fluid properties, were analyzed using finite element methods to determine their impact on seepage flow. The findings reveal that crack width, permeability, and cement sheath length significantly influence seepage flow in both liquid and gas media. These insights enhance the understanding and prediction of cement sheath seepage characteristics under diverse conditions.

Pictograms, comics and other illustrations: Books in brief

Changes in stress-related outcomes among graduate students following the Mindfulness Ambassador Program: A pilot study

Objectives Graduate students face numerous demands, high stress levels, and associated challenges to intra- and inter-personal relationships. Mindfulness may help to ease such challenging experiences. The Mindfulness Ambassador Program (MAP) is a promising group-based program that has not yet been studied among graduate students. The primary objectives of this study were to: (1) explore graduate students’ perceptions of stress, and their relationships with themselves and meaningful others; (2) explore graduate students’ perspectives of and satisfaction with the MAP; and (3) investigate if participation in the MAP elicited changes in graduate students’ perceived levels of stress, self-awareness, interpersonal skills, and/or social connectedness. Methods In this one-group, pre/post mixed-methods pilot study, nine participants completed pre-post questionnaires and participated in a semi-structured interview post-intervention. Data were analyzed using descriptive statistics, thematic analysis, and paired t-tests. Results Pre-intervention, qualitative themes included participants experiencing moderate-to-high stress levels, intrapersonal conflict, interpersonal relationship challenges, and seeing oneself as a work in progress. Post-intervention themes included better stress management, increased consideration for oneself and others, feelings of connection with others, and overall satisfaction with the MAP. Statistically significant improvements were found from pre- to post-intervention in mean score differences for perceived stress (p = .043), private self-awareness (p = .006), awareness of immediate surroundings (p = .044), and social connectedness (p = .006). Conclusions Participants reported several benefits from their positive experience participating in the MAP. These findings may be used to inform future mindfulness-based programming for graduate students.

Unlocking prognostic potential: A genomic signature of caloric restriction in patients with epithelial ovarian cancer

Objectives Epithelial ovarian cancer is a significant contributor to cancer-related mortality in women, frequently recurring post-treatment, often accompanied by chemotherapy resistance. Dietary interventions have demonstrated influence on cancer progression; for instance, caloric restriction has exhibited tumor growth reduction and enhanced survival in animal cancer models. In this study, we calculated a transcriptomic signature based on caloric-restriction for ovarian cancer patients and explored its correlation with ovarian cancer progression. Methods We conducted a literature search to identify proteins modulated by fasting, intermittent fasting or prolonged caloric restriction in human females. Based on the gene expression of these proteins, we calculated a Non-Fasting Genomic Signature score for each ovarian cancer sample sourced from the Cancer Genome Atlas (TCGA) database. Subsequently, we examined the association between this genomic profile and various clinical characteristics. Results The non-fasting genomic signature, comprising eight genes, demonstrated higher prevalence in primary ovarian tumors compared to normal tissue. Patients with elevated signature expression exhibited reduced overall survival and increased lymphatic invasion. The mesenchymal subtype, associated with chemotherapy resistance, displayed the highest signature expression. Multivariate analysis suggested the non-fasting genomic signature as a potential independent prognostic factor. Conclusions Ovarian cancer tumors expressing a “non-fasting” transcriptional profile correlate with poorer outcomes, emphasizing the potential impact of caloric restriction in improving patient survival and treatment response. Further investigations, including clinical trials, are warranted to validate these findings and explore the broader applicability of non-fasting genomic signatures in other cancer types.

Uncovering women’s healthcare access challenges in low- and middle-income countries using mixed effects modelling approach: Insights for achieving the Sustainable Development Goals

Background Access to healthcare services for women in low- and middle-income countries (LMICs) is crucial for maternal and child health and achieving the Sustainable Development Goals (SDGs). However, women in LMICs face barriers to accessing healthcare, leading to poor health outcomes. This study used Demographic and Health Survey (DHS) data from 61 LMICs between 2010–2023 to identify women’s healthcare access challenges. Methods This study used data from the DHS conducted in 61 LMICs to identify women’s healthcare access challenges from 2010 to 2023. A weighted sample of 1,722,473 women was included in the study using R-4.4.0 version software. A mixed-effects modeling approach was used to analyze access to healthcare, considering individual-level factors and contextual factors. The mixed-effects model takes into account clustering within countries and allows for the examination of fixed and random effects that influence women’s healthcare access across LMICs. For the multivariable analysis, variables with a p-value ≤0.2 in the bivariate analysis were considered. The Adjusted Odds Ratio (AOR) with a 95% Confidence Interval (CI) and a P value < 0.05 was reported to indicate statistical significance and the degree of association in the final model. Results The pooled prevalence of the healthcare access problem was found to be 66.06 (95% CI: 61.86, 70.00) with highly heterogeneity across countries and regions. Women aged 25–34 years, and 35–49 years, had primary education, and secondary or higher education, married women, poorer, middle, richer, and richest wealth indices, had mass media exposure, first birth at age ≥20 years, birth interval of 24–36, 37–59 and >59 months as compared to < 24 months birth interval, had health insurance, delivered at a health facility, had at least one ANC visit, being from lower-middle-income countries, upper-middle-income countries, regions like West Africa, South Asia, and East Asia/Pacific compared to women living in East Africa, low literacy rates, medium literacy rates, and high literacy rates as compared to very low literacy rate were associated with lower odds of having problems accessing healthcare respectively. On the other hand, divorced/widowed women, having 1–2, and more than two under five, living in households with 6–10 family members and >10 members, female household heads, living in rural areas, women living in South/Central Africa, Middle East/North Africa, Europe/Central Asia, and living in Latin America/Caribbean were associated with higher odds of having problems accessing healthcare respectively. Conclusions Approximately two-thirds of women face healthcare access problems. Sociodemographic factors such as age, education, marital status, wealth, media exposure, and health insurance are associated with lower odds of experiencing healthcare access issues. On the other hand, factors such as divorce/widowhood, the number of young children, household size, female household heads, rural residence, and region have been linked to higher odds of facing healthcare access challenges. To address these disparities, policies, and interventions should focus on vulnerable populations by improving access to health insurance, increasing educational attainment, and providing support for single mothers and large households. Additionally, tailored regional approaches may be necessary to overcome barriers to healthcare access.

Did Pluto ‘kiss and capture’ its largest moon?

Antioxidative and anticancer effects of Tacca chantrieri extract enhancing cisplatin sensitivity in cholangiocarcinoma cells

Cholangiocarcinoma (CCA) poses a significant healthcare challenge due to the limited effects of chemotherapeutic drugs. Natural products have gained widespread attention in cancer research according to their promising anti-cancer effects with minimal adverse side effects. This study explored the potential of Tacca chantrieri (TC), a plant rich in bioactive compounds, as a therapeutic agent for CCA. TC, a traditional remedy in Southeast Asia, exhibits anti-inflammatory and cytotoxic properties against cancer cells. Ethanol extraction of TC’s rhizome was conducted, and antioxidant activities were assessed through various assays, including total phenolic and flavonoid contents, DPPH radical scavenging, and FRAP assays. The cytotoxic effects of TC extracts on CCA cell lines (KKU-213A and KKU-213C) were evaluated using MTT assays and flow cytometry. Protein levels of Bax and Bcl-2 were determined through western blot analysis. Additionally, the study investigated whether the combined impact of TC extract and cisplatin on CCA cells enhanced cisplatin’s efficacy as an anti-cancer treatment. Results indicated that ethanolic extracts from TC contained phenolic and flavonoid compounds with robust antioxidant activity. TC treatments reduce CCA cell viability, inhibiting growth and inducing apoptosis in a dose-dependent manner. The Bax/Bcl-2 ratio increases, signifying a pro-apoptotic shift. Importantly, TC extract not only decreases cell viability but also augments the inhibitory effect of cisplatin in CCA cells. These results provide valuable insights into TC’s therapeutic mechanisms and its potential to synergize with conventional chemotherapeutic agents, offering a promising avenue for the development of alternative and more effective strategies for CCA treatment.

Torsion-Induced Traumatic Optic Neuropathy (TITON): A physiologically relevant animal model of traumatic optic neuropathy

Traumatic optic neuropathy (TON) is a common cause of irreversible blindness following head injury. TON is characterized by axon damage in the optic nerve followed by retinal ganglion cell death in the days and weeks following injury. At present, no therapeutic or surgical approach has been found to offer any benefit beyond observation alone. This is due in part to the lack of translational animal models suitable for understanding mechanisms and evaluating candidate treatments. In this study, we developed a rat model of TON in which the eye is rapidly rotated, inflicting mechanical stress on the optic nerve and leading to significant visual deficits. These functional deficits were thoroughly characterized up to one week after injury using electrophysiology and immunohistochemistry. The photopic negative response (PhNR) of the light adapted full field electroretinogram (LA ffERG) was significantly altered following injury. This correlated with increased biomarkers of retinal stress, axon disruption, and cell death. Together, this evidence suggests the utility of our model for mimicking clinically relevant TON and that the PhNR may be an early diagnostic for TON. Future studies will utilize this animal model for evaluation of candidate treatments.

How the brain cleans itself during deep sleep

Knowledge and occupational practices of beauticians and barbers in the transmission of viral hepatitis: A mixed-methods study in Volta Region of Ghana

Background Hepatitis B and C viral (HBV and HCV) infections are endemic in Ghana. Also, the National Policy on Viral Hepatitis stipulates that there is unreliable data, limited knowledge, and a deficiency in research on viral hepatitis, especially among some high-risk workers in the eastern part of the country. This study therefore assessed the knowledge level and occupational practices of street beauticians and barbers in the transmission of HBV and HCV in the Volta Region of Ghana. Methods A cross-sectional mixed methods study was conducted in Volta Ghana from April to June 2021. An in-depth interview was used to collect data from five environmental health officers who were selected as key informants in the qualitative stage. Structured questionnaires/checklists and direct observations were employed to collect data from 340 street beauticians and barbers in the quantitative stage. During the qualitative stage, the process of coding, and mind mapping via thematic analysis was carried out. Furthermore, descriptive and inferential analyses were performed using Stata version 17.0 at a 95% significance level in the quantitative stage. Results Most street beauticians and barbers reported poor knowledge levels about HBV and HCV (67.0%), although the awareness of this viral hepatitis was high (88.2%). While almost one-third of the participants observed safe occupational practices (31.5%), about 29.0%, 49.4%, and 55.3% of them also followed hand hygiene protocols, wore protective clothes/gloves, and sterilized or disinfected tools after use respectively. Street beauticians and barbers with higher (tertiary) education (AOR = 6.15; 95%CI = 1.26–29.9; p = 0.024), those who had heavy workload of more than 20 customers per day (AOR = 3.93; 95%CI = 1.26–12.3; p = 0.019), and those who had work experience of at least four years (AOR = 1.65; 95%CI = 1.02–2.69; p = 0.040) were more likely to have good knowledge level about viral hepatitis. Additionally, beauticians were more likely to adhere to safe occupational practices as compared to barbers (AOR = 11.2; 95%CI = 3.46–36.3; p<0.001). The key informant interviews revealed that there was a lack of licensing, monitoring, and planned training for street beauticians and barbers, although their services are rampant in the Volta Region. Conclusion Participants showed high awareness but limited knowledge about HBV and HCV infections. The general safety practices among the participants were poor. Our study results suggest possible viral transmission through the activities of street beauticians and barbers which could be attributed to the lack of regulatory systems and training of these cosmetologists. Policy-makers and regulatory bodies should institute and enforce rigorous policies and guidelines on job-related safety measures and health practices including regular training, monitoring, screening, and vaccination programs for these high-risk community workers in Ghana.

Tyrosine supplementation is ineffective in facilitating soccer players’ physical and cognitive performance during high-intensity intermittent exercise in hot conditions

Tyrosine has been proposed to potentially provide ergogenic benefits to cognitive and physical performance in physiologically demanding environments. However research into its effectiveness on cognitive and physical performance during exercise in the heat has revealed mixed findings. This study examined the effects of a commonly employed dosage of tyrosine supplementation on soccer players’ physical and decision-making performance, cognitive appraisal, and affective states, during prolonged high-intensity intermittent exercise in hot conditions. Eight trained male soccer players completed a 92-minute high-intensity intermittent cycling sprint protocol whilst responding to soccer-specific decision-making tasks at various time points in 32°C (50%rh), in two counterbalanced conditions; tyrosine (150mg.kg-1) and placebo. No differences were found for peak power output (p = .486; 715 ± 98W vs 724 ± 98W, respectively), decision-making (p = .627; 86.9 ± 10.7% vs 88.6 ± 7.0%, respectively), cognitive appraisal (p = .693, 0.90 ± 0.42 vs 0.88 ± 0.39, respectively) nor affective states (p = .918; 1.15 ± 1.55 vs 1.14 ± 1.70, respectively) between tyrosine and placebo conditions. Also, no condition by time interaction effects were noted for these outcomes. In sum, tyrosine supplementation was ineffective for facilitating prolonged intermittent sprint (self-paced) activity, soccer-specific decision-making, and in alleviating perceptual strain, for soccer players’ exercising in the heat. However, future research may wish to consider alternative approaches for tyrosine supplementation (e.g., timing, dosage) or induce heightened physiological strain to extend on these findings.

Improving reading competence in aphasia with combined aerobic exercise and phono-motor treatment: Protocol for a randomized controlled trial

Aphasia, a communication disorder caused primarily by left-hemisphere stroke, affects millions of individuals worldwide, with up to 70% experiencing significant reading impairments. These deficits negatively impact independence and quality of life, highlighting the need for effective treatments that target the cognitive and neural processes essential to reading recovery. This Randomized Clinical Trial (RCT) aims to test the efficacy of a combined intervention incorporating aerobic exercise training (AET) and phono-motor treatment (PMT) to enhance reading recovery in individuals with post-stroke aphasia. AET, known for its positive impact on cerebral blood flow (CBF) and oxygenation, is hypothesized to facilitate neuroplasticity when administered before PMT, an intensive therapy aimed at strengthening phonological processing. While most existing treatments focus on spoken language production, this study builds on evidence that PMT can also improve reading skills. The study is structured as a Phase I/II clinical trial and compares the effects of AET plus PMT to a control condition of stretching plus PMT on reading and other language outcomes including naming, auditory comprehension, and spontaneous speech. Additionally, it investigates the immediate and sustained impacts of the intervention on CBF, functional connectivity, and task-evoked brain activity. The central hypothesis posits that AET will increase CBF and, when combined with PMT, will lead to enhanced reading recovery, supporting treatment-induced plasticity. This trial represents one of the first large-scale interventions targeting post-stroke reading impairments and provides critical insights into the potential of combining AET with cognitive rehabilitation to improve language recovery in aphasia.

Quality of life identification by unsupervised cluster analysis: A new approach to modelling the burden of endometriosis

Background Symptoms frequently associated with endometriosis affect quality of life (QoL). Our aim investigated the hypothesis that cluster analysis can be used to identify homogeneous phenotyping subgroups of women according to the burden of the endometriosis for their QoL, and then to investigate the phenotype differences observed between these subgroups. Methods We developed an anonymous online survey, which received responses from 1,586 French women with endometriosis. K‐means, a major clustering algorithm, was performed to show structure in data and divide women into groups based on the burden of endometriosis. This was defined using 9 dimensions. Multivariable logistic regression was performed to highlight the association between QoL and several factors. Covariables were age, BMI, smoking, education, children, marital status and surgery. Results K‐means clustering was implemented with 8 clusters (optimal CCC value of 17.2162). In one cluster, women presented a high level of QoL and represented 234 women for 60% of women with a high level of QoL, and another with 410 women for 34% of women with worse QoL. Independent factors determining high QoL were age (over 45 years compared to below 25 years, OR = 0.17 [0.07–0.46], p<0.001), BMI (high vs low, OR = 0.47 [0.28–0.80], p = 0.005), having children (OR = 0.30 [0.18–0.48], p<0.001), having surgery for endometriosis (OR = 0.55 [0.32–0.94], p = 0.029), and education (high vs low, OR = 2.75 [1.75–4.31], p<0.001) Conclusion Cluster analysis identifies homogeneous women phenotypes for QoL with endometriosis. Implementing new methodological approaches improves QoL of endometriosis women and allows appropriate preventive strategies.

Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification

In recent years, the utilization of motor imagery (MI) signals derived from electroencephalography (EEG) has shown promising applications in controlling various devices such as wheelchairs, assistive technologies, and driverless vehicles. However, decoding EEG signals poses significant challenges due to their complexity, dynamic nature, and low signal-to-noise ratio (SNR). Traditional EEG pattern recognition algorithms typically involve two key steps: feature extraction and feature classification, both crucial for accurate operation. In this work, we propose a novel method that addresses these challenges by employing empirical mode decomposition (EMD) for feature extraction and a parallel convolutional neural network (PCNN) for feature classification. This approach aims to mitigate non-stationary issues, improve performance speed, and enhance classification accuracy. We validate the effectiveness of our proposed method using datasets from the BCI competition IV, specifically datasets 2a and 2b, which contain motor imagery EEG signals. Our method focuses on identifying two- and four-class motor imagery EEG signal classifications. Additionally, we introduce a transfer learning technique to fine-tune the model for individual subjects, leveraging important features extracted from a group dataset. Our results demonstrate that the proposed EMD-PCNN method outperforms existing approaches in terms of classification accuracy. We conduct both qualitative and quantitative analyses to evaluate our method. Qualitatively, we employ confusion matrices and various performance metrics such as specificity, sensitivity, precision, accuracy, recall, and f1-score. Quantitatively, we compare the classification accuracies of our method with those of existing approaches. Our findings highlight the superiority of the proposed EMD-PCNN method in accurately classifying motor imagery EEG signals. The enhanced performance and robustness of our method underscore its potential for broader applicability in real-world scenarios.

Sustainable development through eco-innovation: A focus on small and medium enterprises in Colombia

This study examines the impact of eco-innovation on the economic, social, and environmental performance of small and medium enterprises (SMEs) in Colombia. SMEs are pivotal to Colombia’s economic landscape, contributing significantly to job creation, economic growth, and regional development. The research utilizes structural equation modeling (SEM) to analyze data collected from 568 SMEs through an electronic survey. The findings indicate that eco-innovation positively influences both environmental and economic-social performance. Enhanced environmental performance, driven by eco-innovation, is associated with improved resource efficiency, reduced emissions, and waste management. Moreover, economic and social performance, measured through profitability, product quality, and job satisfaction, also benefits from eco-innovative practices. These results underscore the importance of eco-innovation in promoting sustainable development within the SME sector. The study advocates for further large-scale investigations to validate these findings and to explore the broader implications of eco-innovation in diverse economic contexts.

Edge intelligence for poultry welfare: Utilizing tiny machine learning neural network processors for vocalization analysis

The health of poultry flock is crucial in sustainable farming. Recent advances in machine learning and speech analysis have opened up opportunities for real-time monitoring of the behavior and health of flock. However, there has been little research on using Tiny Machine Learning (Tiny ML) for continuous vocalization monitoring in poultry. This study addresses this gap by developing and deploying Tiny ML models on low-power edge devices to monitor chicken vocalizations. The focus is on overcoming challenges such as memory limitations, processing power, and battery life to ensure practical implementation in agricultural settings. In collaboration with avian researchers, a diverse dataset of poultry vocalizations representing a range of health and environmental conditions was created to train and validate the algorithms. Digital Signal Processing (DSP) blocks of the Edge Impulse platform were used to generate spectral features for studying fowl vocalization. A one-dimensional Convolutional Neural Network (CNN) model was employed for classification. The study emphasizes accurately identifying and categorizing different chicken noises associated with emotional states such as discomfort, hunger, and satisfaction. To improve accuracy and reduce background noise, noise-robust Tiny ML algorithms were developed. Before the removal of background noise, our average accuracy and F1 scores were 91.6% and 0.92, respectively. After the removal, they improved to 96.6% and 0.95.

Perceived stress across population segments characterized by differing stressor profiles—A latent class analysis

Objective We aimed to 1) identify distinct segments within the general population characterized by various combinations of stressors (stressor profiles) and to 2) examine the socio-demographic composition of these segments and their associations with perceived stress levels. Methods Segmentation was carried out by latent class analysis of nine self-reported stressors in a representative sample of Danish adults (N = 32,417) aged 16+ years. Perceived stress level was measured by the Perceived Stress Scale (PSS). Results Seven classes were identified: Class 1 was labeled Low Stressor Burden (64% of the population) and the remaining six classes, which had different stressor combinations, were labeled: 2) Burdened by Financial, Work, and Housing Stressors (10%); 3) Burdened by Disease and Death among Close Relatives (9%); 4) Burdened by Poor Social Support and Strained Relationships (8%); 5) Burdened by Own Disease (6%); 6) Complex Stressor Burden Involving Financial, Work, and Housing Stressors (2%); and 7) Complex Stressor Burden Involving Own Disease and Disease and Death among Close Relatives (2%). Being female notably increased the likelihood of belonging to Classes 2, 3, 5, and 7. Higher age increased the likelihood of belonging to Class 3. Low educational attainment increased the likelihood of belonging to Classes 5 and 6. A significant difference was observed in perceived stress levels between the seven latent classes. Average PSS varied from 9.0 in Class 1 to 24.2 in Class 7 and 25.0 in Class 6. Conclusion Latent class analysis allowed us to identify seven population segments with various stressor combinations. Six of the segments had elevated perceived stress levels but differed in terms of socioeconomic composition and stressor combinations. These insights may inform a strategy aimed at improving mental health in the general population by targeting efforts to particular population segments, notably segments experiencing challenging life situations.