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Multi attribute predictions of volume of shale and porosity from seismic data over Akaso Field, Niger Delta using machine learning regression analysis
No full textAbstract Predicting volume of shale and porosity in structurally complex deltaic environments like the Niger Delta remains challenging for conventional inversion techniques. This study applies machine learning regression models to integrate multi-attribute 3D seismic data and well logs for improved prediction of reservoir properties in the Akaso Field, eastern Niger Delta. Petrophysical evaluation of Sand Unit C from six wells yielded porosity values of 0.11–0.34, shale volume of 1–11%, and water saturation of 4–30%. Ten seismic attributes including Acoustic Impedance, Reflection Strength, Instantaneous Frequency, and Dominant Frequency were extracted, normalized, and screened using Variance Inflation Factor. Porosity was computed from density–neutron crossplots, while volume of shale index was derived using k-means clustering. Six regression algorithms (Linear, Ridge, Lasso, SVR, Random Forest, and XGBoost) were trained using 80:20 train–test split and 10-fold stratified cross-validation with hyperparameter optimization and SHAP-based feature importance analysis. XGBoost achieved the highest accuracy with R² = 0.91 for porosity and R² = 0.83 for volume of shale, significantly outperforming SVR and Random Forest. SHAP analysis identified Reflection Strength, Acoustic Impedance, and Instantaneous Frequency as strongest porosity predictors, while Dominant Frequency, Hilbert Transform, and Instantaneous Phase best predicted volume of shale. Predicted porosity and volume of shale maps accurately delineated hydrocarbon-bearing sand bodies and aligned with well observations. This study demonstrates that integrating multi-attribute seismic data with optimized ML regression significantly improves volume of shale and porosity prediction in faulted deltaic settings. The combined use of accuracy metrics and SHAP-based interpretability provides a transferable framework for reducing subsurface uncertainty and supporting data-driven reservoir characterization in the Niger Delta
Adherence to dietary recommendations according to the General Dietary Behavior Inventory (GDBI) and its association with bioelectrical impedance analysis (BIA) parameters among young, healthy and normal weight women
No full textAbstract Background The General Dietary Behavior Inventory (GDBI) is a low effort instrument with only 16 items to assess the general dietary behavior based on the dietary recommendations of the World Health Organization and the German Nutrition Society. In an online survey with a convenience sample, higher total GDBI scores indicating healthier dietary behavior were associated with a lower body mass index (BMI). Aim Since mean value of the self-reported BMI in that sample was in the overweight range, the aim of the current study was to examine the adherence to dietary recommendations using the GDBI in a sample of young and healthy women at the lower normal BMI range. Methods In total, 63 women aged 22.2 ± 2.2 years with a mean BMI of 20.4 ± 1.0 kg/m2 were included in this study. Body composition was determined using bioelectrical impedance analysis (BIA). GDBI sum score and single item scores were compared with those of the validation study. Spearman correlations were calculated between the GDBI sum score and age, BMI, waist circumference (WC), and BIA parameters. Results The mean GDBI score of 55.76 ± 6.46 in this sample was similar to that of the validation study. Regarding single items, the most pronounced difference compared with the validation study was found for the scores of item 2 indicating lower consumption of animal products in the current study. However, this item was not concordant with all further items. The GDBI sum score correlated with age, but neither with BMI nor WC nor any BIA parameter. Conclusion In conclusion, other than expected we did not find a higher GDBI score compared with that of the validation study. Moreover, in this homogenous, healthy sample of young women at the lower normal BMI range, healthier dietary behavior as indicated by higher GDBI scores does not explain differences in BMI or body composition. Trial registration The study is registered at the German Clinical Trials Register (DRKS-ID: DRKS00030472). Date of registration: October 10th, 2022, retrospectively registered
From Amphiphiles to mRNA platforms: emerging vaccination strategies for pancreatic cancer
No full textAbstract Pancreatic ductal adenocarcinoma (PDAC) remains among the deadliest cancers, with limited surgical eligibility, modest chemotherapy benefit, and resistance to immune checkpoint blockade. Two recent vaccine platforms have shown encouraging results. Wainberg et al. demonstrated that the amphiphile vaccine ELI-002 efficiently traffics to lymph nodes via albumin binding and induced KRAS-specific T-cell responses in most patients, correlating with survival. In parallel, Sethna et al. reported that an individualized uridine-modified mRNA vaccine elicited durable, polyfunctional CD8⁺ T cells with long-term persistence, especially when combined with PD-1 blockade. Amphiphiles provide rapid and efficient priming, whereas mRNA vaccines broaden and sustain clonotypic diversity. A hybrid prime–boost strategy may synergize these complementary mechanisms, while advances in multi-omics and AI-driven neoantigen prediction pave the way for personalized designs. Together, these developments suggest that PDAC, long regarded as immunologically “cold,” may become tractable to vaccination strategies. Importantly, these findings are based on early-phase clinical studies with limited patient numbers and should therefore be interpreted as preliminary clinical evidence requiring further studies
Can ChatGPT compete with emergency medicine specialists? A two-stage assessment of ECG interpretation supported by clinical information
No full textAbstract Background The increasing integration of AI-powered large language models into clinical workflows has created new opportunities for augmenting diagnostic decision-making in emergency care. This study evaluated whether the customized ECG Reader-GPT model could serve as a supportive tool—rather than a substitute for expert judgment—during ECG interpretation in the emergency department (ED). Methods This single-center diagnostic accuracy study analyzed 72 real patient ECGs obtained in a tertiary ED. An expert panel assigned the ECGs to diagnostic subgroups and classified them as easy or difficult based on clinical complexity. Ten emergency medicine specialists (EMSs) interpreted each ECG in two stages: first without clinical information, then with the patient’s history. The same ECG set was assessed by a customized GPT model (ECG Reader-GPT) using standardized English prompts across 10 independent sessions to evaluate performance stability. Two cardiologists, blinded to group assignments, scored all responses using a predefined key. Results EMSs demonstrated markedly higher diagnostic accuracy than ECG Reader-GPT in both stages. In Stage 1, specialists correctly interpreted 77% of ECGs, whereas ECG Reader-GPT achieved 24%. With clinical information provided (Stage 2), accuracy increased to 79% and 27%, respectively. The performance of both groups was reduced with difficult ECGs (p < 0.05). Across all diagnostic subgroups, the specialists outperformed the AI model, and both groups scored higher when clinical context was available. Intraclass correlation demonstrated strong within-group consistency (p < 0.001). Conclusion EMSs consistently outperformed ECG Reader-GPT under all conditions, indicating that the model is currently insufficient for real-world ECG interpretation. Although it may offer limited supportive value, its use requires caution, and rigorous external validation is essential before any clinical application
Bridging the digital divide: increasing response rates to electronic pain questionnaires in outpatient neurosurgery
No full textAbstract Purpose Pain questionnaires are widely used in healthcare; however, response rates—particularly for electronic surveys—are often low and difficult to improve without significant resources. This study aimed to analyze and identify strategies to boost response rates to electronic pain questionnaires distributed prior to first-time consultations for patients with low-back pathologies. Methods Between June 2023 and June 2024, referred patients were invited to complete an electronic low-back pain questionnaire before their first neurosurgical consultation. Implementation occurred in three stages: email-only (period 1), with an added notice in the appointment letter (period 2), and with a supplementary informational flyer (period 3). Non-respondents were offered the option to complete the questionnaire at the day of the consultation on a hospital-provided tablet-computer or on paper. Patient demographics, response timing and mode, age-related differences, and potential language barriers were assessed. Results Of 1017 patients contacted, 665 responses were eligible for analysis. The overall at-home response rate was 54% (n = 359), increasing significantly from 43% in period 1 to 56% in period 3 (p = 0.027). Of the remaining 306 patients, 226 (40%) were willing to answer the questionnaires by providing a tablet-computer at the day of consultation. Response patterns differed significantly across age groups (p 76 years) and patients with a migration background were less likely to complete the questionnaire. Conclusion At-home electronic questionnaire response rates can be significantly boosted for pre-consultation pain assessments when supported by targeted interventions. Response rates are affected by age, migration status, language proficiency, and digital access. With a hospital provided tablet-computer based backup, 40% of patients who initially did not respond at home were able to complete the questionnaire at the hospital prior to consultation
Impact of gut microbiota on atypical endometrial hyperplasia and endometrial cancer: a comprehensive analysis of microbial composition and metabolomic profiling
No full textAbstract Background Endometrial cancer (EC) is one of the most common malignant tumors in women, and in recent years, the role of gut microbiota in tumorigenesis has gradually gained attention. Previous studies have shown that the gut microbiome is closely related to the occurrence of various cancers, but the specific mechanisms through which gut microbiota contribute to the development of endometrial cancer (EC) remain unclear. This study aims to analyze the gut microbiome characteristics of atypical endometrial hyperplasia (AEH) and EC, and to explore key gut microbial species and metabolites, providing evidence for the etiological research and early screening of EC and AEH. Methods This study selected 24 AEH or EC patients from the Gynecology Department of Gansu Provincial Maternity and Child Care Hospital between February 2023 and October 2023. The patients were divided into the AEH group (n=7) and the EC group (n=17), with 24 healthy women selected as a control group. Fecal and serum samples were collected, and 16S rRNA gene sequencing was performed using the Illumina MiSeq platform. Serum metabolomics analysis was conducted using LC-MS technology. Spearman correlation analysis was used to explore the associations between gut microbiota and metabolites, and potential gut microbial biomarkers were evaluated using ROC analysis. Results The study found that as AEH progressed to EC, significant changes occurred in the composition of the gut microbiota, particularly in Klebsiella, whose abundance increased from 0.264% in the control group to 0.809% in the AEH group and 6.092% in the EC group, with significant differences (P<0.001, FDR=0.026). LEfSe analysis identified Megamonas, Klebsiella, Escherichia, and Akkermansia as potential biomarkers. ROC analysis showed that the AUCs of Megamonas/Klebsiella for EC were 0.864/0.838, and the AUCs of Escherichia/Akkermansia for AEH were 0.744/0.920. Metabolomics analysis revealed significant enrichment of glycerophospholipid metabolism in both the EC and AEH groups, with significant differences in lipid metabolism in the EC group. Correlation analysis indicated significant positive correlations between Enterococcus and hypoxanthine, inosine in the EC group (r=0.686, 0.637, P<0.05). Conclusion This study reveals the dynamic changes in the gut microbiome during the development of endometrial lesions, especially the increasing abundance of Klebsiella as AEH progresses to EC, suggesting that it may play a key role in the occurrence and progression of EC. Furthermore, significant changes in lipid metabolism further support the role of gut microbiota in regulating lipid metabolism in EC pathogenesis. This study provides new insights into the role of gut microbiota in endometrial cancer and offers a theoretical basis for early diagnosis and personalized treatment strategies based on gut microbiota
Short-term high-altitude exposure protects working memory by balancing intestinal microbiota
No full textAbstract Background High-altitude environments (> 2500 m) with low oxygen, low pressure, variable climate, large diurnal temperature differences, and high solar and ultraviolet radiation are risky to human health. Mice’s intestinal microbiota changes at high altitude may affect cognition via the gut–brain axis. Short-term high-altitude exposure may have positive effects on organisms. This study explores if short-term high-altitude exposure can protect working memory from restraint stress (RS) and the role of intestinal microbiota in this process. Methods Forty-eight C57BL/6 mice aged eight weeks were divided into four groups: the Control group, RS group (S group), high altitude exposed group (HA group), and high-altitude exposed with RS group (HA-S group). High altitude was simulated via exposure to a low-pressure oxygen chamber at a simulated altitude of 3500–4000 m for 14 days. RS was simulated from days 22–29 and followed by the novel object recognition test to assess working memory. Blood for serum, prefrontal cortex, ileal sections for molecular analysis, and intestinal contents for 16S rRNA sequencing were collected. Results Compared to control mice that were not exposed to high altitude and did not experience RS, mice that were also exposed to high altitude and experienced restraint stress had significantly greater working memory deficits, whereas mice exposed only to high altitude did not show significant differences in working memory performance. Different gut microbial community structures were observed in these groups, with high altitude-exposed mice exhibiting higher α-diversity. In addition, the difference in β-diversity between restraint stress and high altitude exposed mice was significantly higher, indicating significant differences in microbial community composition. The major bacterial phyla identified were Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria, with Lactobacillus being more abundant in the restraint stress group, while Bifidobacterium and Muribaculum were relatively more abundant in the high-altitude exposed with restraint stress group, but the relative abundance of Lactobacillus was lower. Conclusions Short-term high-altitude exposure might possibly protect working memory function by modulating intestinal function through the microbiota–gut–brain axis, with Lactobacillus perhaps contributing to alleviate working memory dysfunction induced by stress. This study may enhance our understanding of the microbiota-gut-brain axis in high-altitude environments and could offer new preventive and therapeutic insights for high-altitude-related health issues, possibly benefiting workers and explorers in such environments
Asynchronous seasonal dynamics of nycteribiid bat flies and Bartonella spp. in Australian flying foxes (Pteropus spp.)
No full textAbstract Background Bat flies are ubiquitous ectoparasites of bats, recognised as potential vectors for viral and bacterial transmission between individual bats within a roost. Despite this, little is known about the seasonal dynamics of bat flies. Here, we present the results of a longitudinal study that compares seasonal prevalence and host risk factors for bat fly (Diptera: Nycteribiidae) parasitism with that of Bartonella and Borrelia spp. detected in Pteropus alecto and P. poliocephalus in eastern Australia. Methods Flying foxes were sampled at nine different roosts in south-east Queensland and northern New South Wales between February 2018 and September 2022 using mist nets. Host and ectoparasite data were recorded, and bat fly specimens were collected for identification. Blood samples collected from the flying foxes were screened for the presence of Bartonella and Borrelia DNA using polymerase chain reaction (PCR). Results Ectoparasite data were recorded from 2235 flying foxes and 840 had blood samples screened for Bartonella and Borrelia DNA. Cyclopodia albertisii was the predominate nycteribiid species identified, with few detections of C. australis. Nycteribiid prevalence had a consistent annual cycle (ranging from 8.6% to 100%) that depended on local climatic factors, increasing with increased temperature and humidity during summer and decreasing in winter. Bartonella spp. prevalence exhibited less variation seasonally (ranging from 50% to 100%) with a peak in winter that was driven by host age, with juvenile bats having a reduced probability of infection compared with subadults and adults. Borrelia spp. were rare and showed no clear seasonality. Conclusions This study reports the longitudinal occurrence of the blood-borne bacteria Bartonella spp. and their likely ectoparasite vectors in Australian flying foxes. The findings contribute to knowledge of nycteribiid ecology critical for understanding their vector potential within flying fox roosts and provide direction for future research into nycteribiid-mediated transmission dynamics. Graphical Abstrac
Optimal exercise prescription for depression and anxiety in children and adolescents: a Bayesian dose–response network meta-analysis protocol
No full textAbstract Background Depression and anxiety are among the most common mental health problems affecting children and adolescents worldwide. Exercise is a widely used and potentially cost-effective non-pharmacological approach that may improve mood and mental health. However, the optimal exercise modalities and doses for alleviating depressive and anxiety symptoms in children and adolescents remain uncertain. Previous evidence has primarily relied on pairwise meta-analyses or conventional network meta-analyses: the former are unable to compare multiple exercise formats simultaneously, while the latter, although capable of integrating different interventions, have not quantified dose characteristics such as intensity, frequency, and duration. Consequently, systematic dose–response evidence regarding depressive and anxiety symptoms in children and adolescents is lacking. This study aims to examine the quantitative relationship between exercise dose and changes in depressive and anxiety symptoms. Methods This protocol outlines a systematic review and Bayesian model-based dose–response network meta-analysis. A systematic search will be conducted of PubMed, Embase, Web of Science, the Cochrane Library, Scopus, PsycINFO, SPORTDiscus, and the China National Knowledge Infrastructure databases through May 2026. Randomized controlled trials enrolling children and adolescents aged 6–18 years with depressive or anxiety symptoms and comparing different types and doses of exercise training will be eligible for inclusion. Study quality will be appraised using the Cochrane Risk of Bias 2.0 tool. Exercise interventions will be categorized by type (e.g., aerobic, resistance, mind–body, and combined exercise-only) prior to dose–response modeling. A Bayesian model-based dose–response network meta-analysis will be performed, with exercise dose quantified as weekly metabolic equivalent of task (MET) minutes (MET-min/week) by integrating intensity, session duration, and frequency. Nonlinear dose–response curves will be fitted for distinct exercise modalities. Meta-classification and regression tree (meta-CART) analysis will be employed to identify potential effect modifiers. Discussion This study will systematically evaluate the nonlinear dose–response relationships between exercise dose and changes in depressive and anxiety symptoms in children and adolescents, and estimate dose ranges associated with symptom change across exercise modalities. The findings may help inform future evidence-based recommendations and provide methodological guidance for dose–response research in child and adolescent mental health. Systematic review registration This protocol has been registered with the International Prospective Register of Systematic Reviews (PROSPERO), registration number CRD420251174947
Microbiological findings and antibiotic treatment in community-acquired pneumonia: a retrospective cohort study
No full textAbstract Background National and regional guidelines are regularly updated to ensure the correct diagnosis and treatment of pneumonia while minimizing unnecessary antibiotic use. However, recent microbiological studies have raised concerns about the recommendations in Danish guidelines. This study aimed to describe the aetiology, empirical antibiotic treatment, and adherence to guidelines in the management of hospitalised patients with community-acquired pneumonia (CAP). Methods This retrospective cohort study included all adults hospitalised with CAP at the Emergency Department of Aalborg University Hospital, Denmark, over a one-year period from November 2021 to October 2022. Hospital records were reviewed, and the microbiological data and the antibiotic therapy were analysed. Results A total of 366 patients were included in the study. The most frequently identified pathogen was Haemophilus influenzae (25%), followed by influenza A (22%), Staphylococcus aureus (9%), respiratory syncytial virus (9%) and Streptococcus pneumoniae (8%). H. influenzae was the dominant bacterial pathogen in both patients with COPD and without COPD. S. aureus was among the most commonly detected pathogens in patients with a CURB-65 score of 3–5 (22%). Regarding antibiotic treatment, 41% of the patients did not receive the recommended therapy. Non-adherence to the guidelines was primarily driven by the overuse of broad-spectrum antibiotics. At admission time, the most commonly prescribed empirical antibiotics were amoxicillin/clavulanic acid (33%), piperacillin/tazobactam monotherapy (23%) and penicillin monotherapy (21%), respectively. Conclusion Our study found that H. influenzae was the most frequently detected bacterial pathogen identified in both patients with and without COPD hospitalised with CAP. These findings highlight the need to reconsider the empirical treatment recommendations in the Danish guidelines. Amoxicillin/clavulanic acid was the most commonly prescribed empirical antibiotic. However, a substantial proportion of patients did not receive guideline-adherent treatment. Broad-spectrum antibiotic overuse was the main issue
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