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Perceptions of assisted reproductive technologies in wildlife conservation: Public expectations and ethical implications across three EU countries

This paper examines public perceptions of Assisted Reproductive Technologies (ART) in wildlife conservation across three European countries: Czechia, Germany, and Italy. In the context of ongoing biodiversity decline, ART can support conservation efforts by promoting population growth, facilitating genetic exchange, and enhancing genetic diversity through genome resource banks. However, the application of ART in wildlife conservation may challenge conventional views on reproduction and extinction and raise ethical considerations, for example concerning animal welfare. To assess public views and ethical concerns, we conducted a survey in three EU countries involved in the BioRescue project, a conservation initiative employing ART to prevent the extinction of the Northern white rhinoceros (Ceratotherium simum cottoni). The survey explored respondents’ attitudes toward biodiversity loss, awareness of the rhinoceros crisis, support for ART in wildlife conservation, and their primary sources of environmental information. The findings inform recommendations for improving conservation communication and fostering public acceptance of ART in wildlife conservation, while emphasizing the need for rigorous ethical oversight to ensure their responsible application.

Analysis of the correlation between vaginal microbiota and high-risk human papillomavirus infection and cervical lesions

The aim of this study was to evaluate changes in the vaginal microbiota and biomarkers among high-risk human papillomavirus (hrHPV)-positive women, those with hrHPV accompanied by mucositis, and patients with cervical intraepithelial neoplasia (CIN) and to establish a novel predictive model. Vaginal samples from 102 women were categorized into four groups: control group (n = 26), hrHPV-positive group (n = 22), hrHPV-positive with mucositis group (n = 26), and CIN group (n = 28). Microbiota analysis was performed using the PacBio platform with full-length 16S rDNA gene sequencing. The vaginal microbiota in the hrHPV-positive, hrHPV-positive with mucositis, and CIN groups showed significant differences compared with the healthy control group. The microbial richness in the hrHPV-positive group was significantly different from both the CIN group and healthy controls. Compared with the control group, the hrHPV-positive group exhibited significantly increased relative abundances of Bifidobacterium , Escherichia-Shigella , Hoylesella and nominally increased abundances of Gardnerella , Prevotella , along with a significant decrease in Lactobacillus . No statistically significant differences were retained between the hrHPV-positive group and the hrHPV-positive with mucositis group after FDR correction for the top 10 genera. Compared with the hrHPV-positive with mucositis group, the CIN group demonstrated significantly reduced levels of Pseudomonas, nominally decreased levels of Bifidobacterium and Faecalibacterium , whereas Glutamicibacter and Sporosarcina were nominally enriched. A random forest model was constructed to predict risk across groups and demonstrated good predictive performance, suggesting that vaginal microbiota may serve as valuable indicators for predicting cervical lesion risk. During hrHPV infection, significant alterations occur in the vaginal microecology, primarily characterized by an increase in pathogenic bacteria and a reduction in beneficial bacterial populations.

Magnitude, resistance profiles, and risk factors of intestinal parasites and enteric bacteria among food handlers in West Guji Zone, Ethiopia

Introduction Despite food handlers’ crucial role in pathogen transmission, current data on intestinal parasites and antimicrobial susceptibility and resistance patterns of enteric bacteria among food establishment workers in Bule Hora town are notably limited. This knowledge gap hinders effectiveness of public health interventions. Objective This study aimed to assess the prevalence and antimicrobial resistance profile of intestinal parasites, enteric bacteria, and associated factors among food handlers in Bule Hora town food and drinking establishments. Methods We employed a cross-sectional study design to assess the health status of food handlers. Data were collected utilizing both a semi-structured questionnaire to gather self-reported information and an observational checklist to assess practices and environmental factors. A total of 375 stool samples were collected from the participating food handlers. These samples underwent laboratory examination for the identification of bacterial and parasitic pathogens. To determine factors independently associated with the health status of food handlers, multivariable logistic regression analysis was performed. Adjusted odds ratio together with 95% Confidence Interval (CI) were used to measure the association and p value < 0.05 was used to declare the statistical significance. Result Overall, 147(39.2% (95% CI: 34.26, 44.14)) prevalence of intestinal parasites and 50 (13.3%) (95%CI: 9.2–19.7) prevalence of bacteria was found in this study. The most predominant parasite was Ascaris lumbricoid (51.1%) and the most frequently reported an enteric bacterium was Salmonella 39 (78%). Out of 39 Salmonella isolates, 20.5% showed multidrug resistance, while none of the 11 Shigella isolates were multidrug resistant. From multivariable binary logistic analysis, unable to read and write (AOR = 1.96, 95% CI 1.18, 3.26), not trimming fingernails (AOR = 2.52; 95% CI: 1.20, 9.55), not washing hand with soap after toilet (AOR = 2.27, 95% CI 1.17, 4.42), and eating raw food (AOR = 1.62, 95% CI 1.39, 5.00) have a significant association with the prevalence of bacteria and parasites. Conclusion Intestinal parasites and bacteria were among the leading causes of morbidity in the study area. Educational status, eating raw vegetables or fruit, hand washing after the toilet, and fingernail trimming show significant associations with the health status of food handlers.

Body fat percentage is independently associated with lower pulmonary function in Korean never-smokers: A cross-sectional analysis of 33,748 adults

Background The relationship between obesity and pulmonary function is difficult to interpret using body mass index (BMI) alone because BMI cannot distinguish adiposity from lean mass. This study evaluated whether body fat percentage (BF%) is more strongly associated with pulmonary function than BMI in Korean never-smokers. Methods We retrospectively analyzed 33,748 never-smoking adults who underwent spirometry and bioelectrical impedance analysis during health screenings between January 2007 and December 2014. Pulmonary function was assessed using forced vital capacity (FVC) and forced expiratory volume in one second (FEV₁) from pre-bronchodilator spirometry. Participants were stratified by BF% quartiles. Multivariable linear regression was used to evaluate the association between BF% and lung function after adjustment for age, BMI, waist circumference, and metabolic factors. In sensitivity analyses, lung function impairment was defined using lower limit of normal (LLN) criteria, and multivariable logistic regression was applied to evaluate restrictive and obstructive patterns. Results Higher BF% was consistently associated with lower FVC and FEV₁ in both sexes across all BMI categories (all P  < 0.001). After full adjustment, individuals in the lowest BF% quartile demonstrated significantly higher lung function than those in the highest quartile (β for FVC: + 0.65 L in men and +0.36 L in women; β for FEV₁: + 0.46 L in men and +0.28 L in women; all P  < 0.05). These associations were most pronounced in younger men and in individuals with BMI ≥ 25 kg/m². In LLN-based analyses, elevated BF% was independently associated with a markedly increased risk of restrictive impairment in both men (OR 3.31, 95% CI 2.46–4.47) and women (OR 3.19, 95% CI 2.69–3.79), whereas no independent association was observed with obstructive patterns. Conclusion BF% is independently and inversely associated with pulmonary function and is selectively linked to restrictive ventilatory impairment, offering more refined respiratory risk stratification than BMI in Korean never-smokers.

Augmented reality for advanced prosthetic training in non-amputees

Prosthetic abandonment is highly prevalent among upper extremity amputees (UEA), partly due to lack of engaging and motivating training to use their devices. Augmented reality (AR) systems can be used for rehabilitation, and are advantageous because they offer stimulating, goal-oriented experiences for participants to immerse themselves in while performing repetitive tasks to improve function. Thus, in this study, the effects of a novel AR prosthetic training game, and the transfer of skills to a functional rehabilitation performance assessment involving tasks of daily living were investigated. Thirty-two able-bodied participants, sixteen allocated to receive AR training and sixteen received no training, donned a bypass body-powered prosthetic device to engage in a functional task assessment, evaluated at two time points. The AR group used the bypass prosthesis to engage in the AR training game, ARm-Strong, on each of three training sessions. AR group participants completed a questionnaire at the end of the intervention to evaluate their feelings on the AR game. On average, individuals in the AR group were significantly more efficient at using the bypass prosthesis to complete functional tasks compared to the control group, however, the rate of improvement was similar between groups. Individuals who engaged in the AR training felt positive feelings of engagement, engrossment, and immersion towards the application although the impression of immersion was significantly less than that of engagement and engrossment. The results of this study support previous findings that AR training is an engaging and motivating experience, and motor learning can be achieved through this type of training. Future implications of the results may benefit prosthesis users by enhancing user experience during prosthetic training and ultimately lead to better rehabilitation and overall adherence to the use of the prosthetic device.

Discriminant spectrogram local descriptors for electrocardiography biometric authentication

In recent years, Electrocardiogram (ECG) biometric authentication has emerged as a hot topic in biometrics research due to its unique advantages including intrinsic aliveness characteristics and convenience for users. However, due to the non-stationary and nonlinear nature of ECG signals, there are still some challenges to be addressed for the application of ECG biometric authentication. In this paper, we propose a method that employs the short-time fourier transform (STFT) and a local binary descriptors learning method for ECG biometric authentication. Specifically, we first convert ECG heartbeats into two dimensional spectrogram images by STFT. Second, we extract pixel differential vectors (PDVs) from each point in the spectrogram images of the training ECG heartbeats. Third, we learn a projection matrix to map these PDVs into low-dimensional binary descriptors with three objectives: 1) The error between the original PDV and binary descriptor is minimized. 2) The intra-class variation of the local binary features is minimized and the inter-class variation of the local binary features is maximized. 3) The L 2,1 norm of the learned binary descriptors is minimized. Finally, we represent each spectrogram as a histogram feature by clustering and pooling these binary descriptors. Experiments on the database verify that the proposed method outperforms other existing ECG biometric authentication methods in terms of performance.

Smartwatch-based detection of loss of pulse

We present a framework and a novel dataset for detecting loss of pulse cases using a smartwatch. Our methodology for gathering data involves inducing controlled pulse loss in the forearm within a clinical setting under medical supervision. To the best of our knowledge, this is the first multimodal dataset comprising photoplethysmogram (PPG) signals, inertial measurements (IMUs) that can be obtained from a commercially available smartwatch, and continuous recordings as ground truth, collected from 20 individuals. This dataset serves as a valuable resource for the research community to advance and verify techniques for detecting pulse loss and differentiate between the non-usage of smartwatches to prevent false alarms. Our presented framework consists of extracting several features from signals and employing machine learning models designed to differentiate between the emergency loss of pulse cases with the non-usage of smartwatches. The presented framework achieves a detection accuracy of up to 97.1%, with a false detection rate of 1.0 in an hour when evaluated using leave-one-subject-out cross-validation.

Distinguishing post-COVID from long-COVID in adults: Development and validation of a biomarker signature using targeted proteomics and machine learning in a cross-sectional observational study

Background COVID-19 can have diverse clinical manifestations, ranging from asymptomatic infection to critical illness with multiorgan involvement. While many patients recover fully, others develop long-COVID, a heterogeneous condition marked by persistent symptoms beyond the acute phase. The immunological pathomechanisms between long-COVID and other post-acute recovery states remain unclear. Objective To characterize and compare clinical, pulmonary, and proteomic profiles of patients with long-COVID (LC) and those recovering from severe COVID-19 without long-COVID (post-severe-COVID, PC), and to evaluate the predictive potential of machine learning–based biomarker analysis. Methods In this monocentric, prospective observational study with a cross-sectional design, patients undergoing rehabilitation were included at admission. Clinical data, detailed symptom profiles, and lung function testing, including diffusing capacity of the lungs, were collected. Serum proteomics covering immune response and inflammation panels was performed, and a Random Forest classifier was applied to identify biomarkers differentiating LC and PC. Results LC (n = 24) patients were younger (52 years vs. 58 years in PC), predominantly female (66.7% vs. 30.0% in PC), and reported fatigue, neurocognitive symptoms, and exercise intolerance, whereas PC (n = 40) patients showed greater pulmonary impairment, as shown by reduced diffusing capacity (46% vs. 72.5% in LC p <0.001). Proteomic profiling revealed distinct immune and inflammatory signatures between groups. Applying a random forest classification algorithm, we were able to distinguish between the LC and the PC group with a high degree of accuracy of around 89%, using LAMP3 (Lysosome-associated membrane glycoprotein 3), CKAP4 (cytoskeleton associated protein 4) and KRT19 (Keratin 19). Conclusions This study introduces a novel characterization of patients recovering from severe COVID-19 without long-COVID, enabling clearer differentiation between persistent and recovering trajectories. Combining clinical data, pulmonary function, and proteomic machine learning analysis provides insight into post-acute COVID-19 biology and identifies candidate biomarkers for improved diagnosis.

Ethnopharmocological study of medicinal plants used for treatment of skin diseases by herbalists in Northwestern region of Algeria

Background Skin disease is a major public health concern worldwide, particularly in developing countries. Despite the rich diversity of medicinal plants and strong traditional healing practices in Algeria, the dependence on imported pharmaceuticals remains high. This study documents and analyzes traditional herbal knowledge related to the treatment of skin diseases in Northwestern Algeria (Mascara, Saïda, and Sidi Bel Abbès) with the aim to preserve and scientifically validate this ethnomedicinal heritage. Methods A total of 117 herbalists (110 men and seven women) were interviewed using semi-structured questionnaires between September 2023 and July 2024. Data were analyzed using quantitative ethnobotanical indices, including the Relative Frequency of Citations (RFC) and Plant Part Value (PPV), to assess the cultural significance and usage frequency of medicinal species. Results A total of 73 plant species belonging to 29 families have been reported for the treatment of various skin ailments. The most abundant families were Lamiaceae , Asteraceae , Cucurbitaceae , Liliaceae , Cupressaceae , and Fabaceae . Allium sativum L. and Thymus vulgaris L. showed the highest RFC values (0.175 and 0.124, respectively). Leaves were the most frequently used plant parts (PPV = 0.48; 47.6%), followed by fruits (PPV = 0.12; 11.6%), and seeds (PPV = 0.09; 8.9%). Most of the remedies were prepared from dried plants (65.31%), powders (39.9%), and decoctions (22.55%) being the main preparation methods. Topical application (35.2%), poultices (30%), and rinsing (25%) were the most common modes of administration. The most frequently treated skin conditions were eczema, psoriasis, and acne. Conclusions This study highlights the remarkable ethnopharmacological knowledge preserved among herbalists in Northwestern Algeria, including women’s traditional roles in medicinal practices. The documentation of these findings not only assists preserve valuable cultural heritage but also provides a foundation for future pharmacological research and the sustainable use of the rich medicinal flora of Algeria.

Point cloud generation adversarial network based on self-attention and curvature

As a mainstream form of 3D data, point clouds are widely used in computer vision for tasks such as segmentation, classification, and target detection due to their simple representation method and high stability and accuracy. Considering the issues of noise points and uneven point distribution in current generation models, we propose a novel adversarial network model, SAC-GAN, which incorporates both a self-attention mechanism and a curvature learning mechanism. Firstly, the feature enhancement module and the pre-processing module, which are based on the ShapeNetCore open dataset, are designed on the generator to enhance the authenticity of local geometric details in the generated point cloud. Secondly, the loss function of the discriminator is adjusted to combine the traditional Wasserstein distance with the normal vector of key points to guide the generation of subtle features of point clouds and improve the quality and consistency of generated point clouds; Finally, to enhance the discriminator’s capacity to extract both local and global features, a self-attention mechanism is introduced. This enhances the discriminator’s capacity to discern the details of the generated point cloud and offers superior feedback to the generator. Experimental results indicate that the proposed point cloud generation model outperforms existing methods, including TreeGAN, SP-GAN, PDGN, and WarpingGAN, in terms of generation quality. Specifically, the model achieves a reduction in JSD by 4.24, a decrease in MMD by 0.8, and an increase in COV by 1.25%. It can be proven that the point cloud generated by SAC-GAN model has a good performance in shape integrity and authenticity.

MRI differentiation of usual type endocervical adenocarcinoma and cervical squamous cell carcinoma

Objectives To evaluate the magnetic resonance imaging (MRI) features that may help differentiate usual-type endocervical adenocarcinoma (UEA) from cervical squamous cell carcinoma (SCC), with particular emphasis on diffusion-weighted imaging–derived apparent diffusion coefficient (ADC) values and tumor growth patterns. Methods This retrospective study included 26 patients with histopathologically confirmed UEA and 50 patients with SCC who underwent preoperative pelvic MRI. Quantitative MRI parameters—including tumor size, tumor-to-muscle signal intensity ratios (SIRs) on T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), contrast-enhanced T1-weighted imaging (CE-T1WI), and mean ADC values—were analyzed. Qualitative imaging features such as tumor growth pattern, location, uterine corpus invasion, intratumoral cyst formation, hydrometra/hematometra, and lymphadenopathy were also assessed. Receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic performance of ADC values. Multivariable logistic regression analysis was used to identify independent predictors of UEA. Interobserver agreement was assessed using intraclass correlation coefficients (ICC) and Cohen’s kappa statistics. Results Mean ADC values were significantly higher in the UEA group than in the SCC group (0.901 × 10 ⁻ ³ mm²/s vs. 0.825 × 10 ⁻ ³ mm²/s, p = 0.008). ROC analysis showed a statistically significant but moderate discriminatory performance of mean ADC for differentiating UEA from SCC (AUC = 0.659; 95% CI: 0.527–0.790; p = 0.024). Using the Youden index, an optimal ADC cut-off value of 0.837 × 10 ⁻ ³ mm²/s yielded a sensitivity of 65.4% and a specificity of 62.0% for identifying UEA. Endophytic growth was more frequently observed in UEA, whereas mixed growth was more common in SCC (p = 0.023). Intratumoral cyst formation was observed exclusively in UEA (p = 0.004). In multivariable analysis, mean ADC value and tumor growth pattern were independent predictors of UEA. Interobserver agreement for quantitative and qualitative MRI assessments was excellent. Conclusion Higher ADC values, an endophytic growth pattern, and the presence of intratumoral cysts are useful MRI features for differentiating usual-type endocervical adenocarcinoma from cervical squamous cell carcinoma. These imaging characteristics may contribute to improved preoperative diagnostic accuracy and treatment planning.

Serum BDNF levels as a potential prognostic marker for functional recovery in stroke: Preliminary findings from a prospective observational study

Brain-derived neurotrophic factor (BDNF) crosses the blood-brain barrier and may serve as a marker of neuroplasticity. This study evaluated whether serum levels of mature BDNF, proBDNF, and matrix metalloproteinase-9 (MMP-9) can predict functional recovery after stroke. In this prospective observational study, 93 patients with unilateral stroke and motor impairment were recruited. Clinical, and demographic data, as well as serum levels of mature BDNF, proBDNF, and MMP-9 were collected. Functional assessments measuring stroke severity, cognition, motor function, balance, and mood were conducted at three timepoints: after acute care (T0), 2 weeks post-rehabilitation (T1), and 3 months post-onset (T2). Mature BDNF significantly decreased from T0 to T2 (p = 0.003), while proBDNF remained stable. MMP-9 declined consistently across timepoints (p < 0.001). MMP-9 levels at baseline differed by BDNF genotype (p < 0.05). However, none of the biomarkers independently predicted functional recovery. Functional outcomes improved significantly over time (p < 0.001), with baseline functional scores being the strongest predictors at T1 and T2. Although these biomarkers were not independent predictors of recovery, their longitudinal trajectories may reflect underlying neurobiological recovery mechanisms during rehabilitation, although their prognostic utility remains inconclusive.

Does the regulatory quality matter in the relationship between climate finance and inclusive growth in Africa?

This study scrutinizes the effect of climate finance on inclusive growth in Africa. It further explores how regulatory quality dynamics impact the connection between climate finance and Africa’s inclusive growth. Grounded on panel macroeconomic data straddling 54 African states from 2013 to 2023 and employing the two-step system generalized method of moments (2SYS-GMM) econometric estimation technique, the subsequent outcomes appeared. First, climate finance encourages inclusive growth in Africa, while the interactive terms of climate finance and regulatory quality have a shrinking effect. Before interacting with the regulatory quality, a 1% in increase in climate finance heightened Africa’s inclusive growth by 0.3607% in the long run, while it was accompanying with a 0.1561% upsurge in the inclusive growth in the short run, all other factors remaining constant. Contrarily, the system GMM model publicized that in the long run, a one percent increase in the interactive terms of climate finance and regulatory quality of Africa signposts to a 0.775 percent diminution in inclusive growth, while it marks a 0.753 percent lessening in the short run, on average, and other things remaining constant. The study concludes that the feeble regulatory quality of Africa is harmful in both the long run and the short run. This suggests that negative regulatory quality dynamics completely shrink the positive effect of climate finance on the inclusive growth of Africa over the periods under this study. Further, the anticipated benefits of climate finance in fostering Africa’s inclusive growth may persist elusive unless noteworthy progresses are made to Africa’s currently existing regulatory frameworks.

Three-dimensional evaluation of soft tissue contour changes after premolar extraction with and without alveolar ridge preservation: A prospective observational study

Background This prospective observational study evaluated three-dimensional soft tissue contour changes over a 90-day healing period following bilateral premolar extractions, with and without alveolar ridge preservation (ARP), using intraoral scanning and 3D digital analysis. Methods Eighteen orthodontic patients requiring bilateral premolar extractions were enrolled. In each patient, the extraction socket with relatively lower buccal bone height was assigned to alveolar ridge preservation (ARP), while the contralateral site was left to heal spontaneously. Intraoral scans were obtained immediately before extraction and at 30 days and 90 days post-extraction. Linear horizontal soft tissue changes were measured at 2 mm (H2) and 4 mm (H4) below the gingival margin, while vertical changes were assessed at the central aspect of the extraction socket. Surface displacement was analyzed using root mean square (RMS) distance, and volumetric changes were quantified using region-of-interest segmentation. Results Significant time-dependent changes in soft tissue contours were observed (p < .001), with greater horizontal reduction at H2 than H4, and more pronounced buccal changes (p < .05). At day 90, mean horizontal reduction at H2 buccal was 1.84 ± 0.69 mm (ARP) and 1.72 ± 0.68 mm (control); corresponding H2 lingual reductions were 1.34 ± 0.89 mm and 1.16 ± 0.29 mm. Vertical reduction peaked at 30 days with partial recovery by day 90. RMS-based displacement was greater buccally. Volumetric reduction was approximately 17% in both groups. No statistically significant differences were found between groups. Conclusions Intraoral scanning combined with digital superimposition proved effective for evaluating soft tissue changes after extraction. While ARP remains a valuable approach for alveolar bone preservation, its additional impact on soft tissue contour was limited in sites with favorable baseline conditions. Trial registration Clinical Research Information Service (CRIS), KCT0010923. Registered 19 August 2025. Retrospectively registered.

Factors accelerating time to death among persons with Tuberculosis in Western India: Evidence from a community-based retrospective death audit

Introduction Tuberculosis (TB) remains a leading cause of death globally. India aims to eliminate TB by 2025; however, persistently high mortality rates suggest critical failures in early intervention, particularly among vulnerable populations. This study examined the clinical, social, and system factors associated with accelerated mortality among notified persons with TB (PwTB) in Western India. Methods A cross-sectional study was conducted in six districts of Gujarat, India, during 2023–2024 using Community-Based Verbal Autopsy (CBVA) among relatives of 149 deceased PwTB. Sociodemographic, clinical, and TB care cascade data were collected, and a retrospective time-to-event analysis was performed. A Cox proportional hazards model was used to assess the factors associated with a shorter time from diagnosis to death. Results Majority of deceased belonged to 26–50 years age group (40%), with a high male predominance (81.9%). Nearly half (48.3%) had comorbidities, and 65.8% had a history of addiction. A substantial median delay of approximately five weeks was observed between symptom onset and treatment initiation. Following a confirmed diagnosis, the majority of deaths (nearly 80%) occurred within the first 16 weeks. A comparable trend was noted after the start of treatment, with about 78% of fatalities occurring within 15 weeks. In the adjusted Cox regression model, key population status (HR = 1.5, p = 0.01), presence of comorbidities (HR = 2.0, p < 0.001), and drug-resistant tuberculosis (HR = 1.7, p = 0.003) were independently associated with a shorter time from diagnosis to death. Discussion The findings highlighted the convergence of clinical complexity, social vulnerability, and persistent system constraints that shorten survival, even after treatment initiation. Strengthening early case diagnosis, integrating comorbidity management, improving health system responsiveness, and implementing targeted strategies for vulnerable populations are critical. A systematic TB Death Surveillance and Response System (TBDSR), integrating facility-, community-based reviews, and digital reporting, would provide actionable insights to inform timely intervention and support progress towards TB elimination in India and other high-burden settings.

Correction: Global burden of cardiovascular disease mortality attributable to secondhand smoke, 1990–2019: Systematic analysis of the Global Burden of Disease Study 2019

Using virtual reality hypnosis during stem cell transplant for patients in hematology: A protocol for a feasibility randomized study

Background Stem cell transplantation is a highly stressful treatment for hematological cancer patients, negatively impacting their quality of life. Hypnosis has proven effective in managing symptoms like pain, fatigue, and anxiety, and improving quality of life. Virtual reality (VR) is used in cancer treatments to distract from pain, and combining VR with hypnosis (VRH) could enhance the hypnotic experience. However, methodological limitations in current studies prevent clear evaluation of its effectiveness, particularly for individualized care and psychosocial interventions. Aims 1) To evaluate the preliminary effects of VRH in reducing anxiety, pain, and fatigue during stem cell transplant, improving quality of life post-intervention. 2) To assess intervention feasibility, including patients’ experiences, satisfaction levels, and recommendations for improving the VRH tool. Methods This study will involve 60 hematology patients divided into two groups: VRH and waiting list. Anxiodepressive symptoms, pain, quality of life, fatigue, absorption, dissociation, and amusement will be assessed before, immediately after the intervention, and at one- and three-month follow-ups using validated psychological scales and numeric rating scales (0–10). Semi-structured interviews will capture patient expectations, satisfaction, and feedback. Data will be analyzed using MANOVA (or non-parametric alternatives) and thematic analysis. Discussion The study’s primary goal is to assess VRH’s effectiveness compared to standard care in a feasibility randomized controlled trial (RCT). It will also provide data for improving the VRH tool (version 2.0) and assess its usability. In the long term, findings will help integrate VRH into oncology clinics, offering an innovative intervention to support patients throughout treatment. ClinicalTrial registration ClinicalTrials.gov NCT06817759 .

Building bridges for empowerment and informed decision-making: A qualitative study of midwives’ reflections on how to optimise contraceptive counselling for immigrant women in Sweden

Background Sweden’s National Strategy for Sexual and Reproductive Health and Rights (SRHR) emphasises equitable access to contraception and abortion services. Despite this, immigrant women in Sweden experience lower contraceptive use and higher rates of unintended pregnancies and abortions compared with native-born women. Midwives, as primary providers of contraceptive counselling and prescribing, play a central role in promoting reproductive autonomy and informed choice. Aim To explore midwives’ reflections on how to optimise contraceptive counselling for immigrant women in Sweden. Methods Eleven focus group discussions were conducted with 50 midwives from public and private midwifery clinics in Malmö, where one-third of residents are foreign-born. Data were analysed using qualitative content analysis. Findings The overarching theme, “Building bridges for empowerment and informed decision-making,” captured midwives’ commitment to promoting women’s autonomy while navigating systemic and cultural challenges. Five sub-themes emerged: overcoming the discrepancy between mission and reality; addressing organisational weaknesses in the care chain; enhancing knowledge and capabilities; reinforcing competence and trust in communication; and involving men without undermining women’s autonomy. Midwives highlighted structural barriers, limited resources, and time constraints that hindered person-centred and culturally sensitive care. Conclusion Optimising counselling for immigrant women requires systemic changes, including revised funding structures, expanded multilingual resources and strengthened professional development. Addressing these barriers will enhance women's capabilities and support their reproductive autonomy, aligning with Nussbaum’s Capabilities Approach and promoting gender equality.

Protective effect of cannabinoid type II receptor ligand on bleomycin-induced pulmonary fibrosis in mice

This study aimed to investigate the protective effects of the CB2R ligand compound COCA (N-(3-chloro-2-methylphenyl)-5-(4-hydroxyphenyl)-1,2-oxazole-3-carboxamide) against bleomycin (BLM)-induced pulmonary fibrosis in mice. Compound COCA was identified via AI-driven virtual screening from the ChEMBL database. Forty male C57BL/6J mice were randomly divided into five groups: control, model (BLM), low-dose COCA, high-dose COCA, and pirfenidone. Pulmonary fibrosis was induced by intratracheal BLM administration in the model and treatment groups. Pathological evaluation, ELISA, immunofluorescence, and Western blot were conducted.The results showed that COCA significantly alleviated BLM-induced inflammation and fibrosis. ELISA demonstrated decreased serum levels of TNF-α and IL-6 in the treated groups compared to the BLM group ( P  < 0.01). Immunofluorescence indicated reduced expression of Col-I and Col-III in the treated groups ( P  < 0.01). Western blot analysis revealed an upregulation of CB2R in the BLM group, and enhanced expressions of Nrf2 and Smad7 in the treated groups ( P  < 0.01).In conclusion, AI-driven virtual screening enabled the identification of the CB2R ligand COCA, which binds to CB2R, activates the Nrf2/Smad7 pathway, downregulates related cytokines, and plays a therapeutic and protective role in pulmonary fibrosis.

Dapagliflozin mitigates myocardial inflammation and metabolic stress in heart failure through STAT1 inhibition: Evidence from multi-omics analyses and experimental exploration

Background Heart failure (HF) is a global health challenge with high morbidity and mortality. While dapagliflozin (DAPA), a sodium–glucose cotransporter 2 inhibitor, has proven clinical benefits in HF, its molecular mechanisms remain unclear. Methods We integrated bulk and single-cell transcriptomic analyses with experimental validation to investigate the role of STAT1 in HF and its modulation by DAPA. Bulk RNA sequencing data from the GSE57345 dataset were analyzed for differential expression, enrichment, and weighted gene co-expression network analysis (WGCNA) to identify hub regulators. Single-cell RNA sequencing data (GSE145154) included normal controls (n = 4), dilated cardiomyopathy (DCM, n = 8), ischemic cardiomyopathy infarct regions (ICM_MI, n = 6), and non-infarct regions (ICM_NMI, n = 6), and were processed with Seurat and Harmony for integration, clustering, myeloid subcluster profiling, and AUCell pathway scoring. For in vivo validation, a rat model of myocardial infarction–induced HF was established and divided into control, HF, and HF+DAPA groups (6 mg/kg/day for 4 weeks). Histological examination, Western blotting, ELISA, flow cytometry, and serum bile acid assays were conducted. For in vitro assays, STAT1-overexpressing H9C2 cardiomyocytes were generated by lentiviral transduction. Cell viability (CCK‑8), STAT1 expression (qPCR and Western blot), and apoptosis (Annexin V/PI flow cytometry) were assessed with or without DAPA treatment. Results Transcriptomic analyses revealed widespread activation of bile acid, amino acid, and lipoic acid metabolic pathways in HF, coupled with immune remodeling dominated by increased M1 and reduced M2 macrophages. STAT1 emerged as a central hub gene linking metabolic stress and immune imbalance. Single-cell analysis confirmed aberrant STAT1 expression particularly in M1 and proliferating myeloid clusters. In vivo, DAPA suppressed myocardial STAT1 expression, alleviated inflammation, normalized macrophage polarization, and reduced cytokine and bile acid abnormalities. In vitro, DAPA rescued STAT1-overexpressing cardiomyocytes by restoring viability and reducing apoptosis. Conclusions STAT1 acts as a pivotal mediator bridging metabolic disturbances and immune dysregulation in HF. DAPA alleviates HF by inhibiting STAT1 signaling, thereby restoring immunometabolic balance and protecting cardiac tissue. These findings provide mechanistic insight into the cardioprotective effects of DAPA and position STAT1 as a promising biomarker and potential therapeutic candidate for HF management.