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Pan-cancer and multi-omics analyses reveal the diagnostic and prognostic value of BAZ2B in cancer

Long-term preservation of bacteria in washed sterile sand: A 14-year study

Background Cryopreservation and lyophilization are standard methods for preserving microbial cultures, but they are expensive and labor-intensive, creating a barrier for resource-constrained laboratories. This study evaluated the efficacy of a simple and inexpensive alternative: long-term storage in washed and sterilized sand. Methods Fourteen bacterial strains from ten genera were preserved in sealed tubes containing washed and sterilized sand at room temperature. Viability, assessed by colony-forming units (CFU/g), was quantified at inoculation and after 7 and 14 years. Phenotypic stability was evaluated by comparing the pre- and post-storage profiles for enzyme activity and stress tolerance. Results After seven years, all 14 strains remained culturable with preserved phenotypic features. After 14 years, 13 strains (93%) were viable. The highest recovery rates were observed in spore-forming Gram-positive bacteria (e.g., Bacillus sp .), indicating taxon-specific survival. Notably, the Gram-negative strain Enterobacter hormaechei remained stable with only a approximate 1.58 log₁₀ reduction over 14 years (half-life = 2.67 years). All resuscitated strains maintained their pre-storage characteristics. The distinct survival patterns for each species indicate that contamination was not the primary driver of the outcomes. Conclusion Washed and sterile sand offers a practical, low-energy matrix for long-term preservation of a diverse range of bacteria, effectively maintaining cultivability and key phenotypic attributes for over a decade. This approach is an economical preservation strategy for resource-limited laboratories and field collections.

Modeling NRTIs and PIs class drug therapy on the dynamics of HIV infection with real patient data analysis and optimized control strategy

Exposures associated with tuberculosis presentation and healthcare delays in South West England, 2015–2020

Significant progress has been made in reducing the tuberculosis (TB) rate in England over the last decade. South West England has a low incidence of TB, but over a third of people with pulmonary TB (pTB) had a treatment delay of over four months in 2020, higher than the England average. This study aimed to identify the exposures associated with presentation and healthcare delays in receiving pTB treatment in the South West of England between 2015 and 2020. This retrospective cohort study included all confirmed persons with TB resident in South West England, receiving treatment between 2015 and 2020. Univariate and multivariable Cox proportional hazards ratios were produced for the outcome measures of presentation and healthcare delays for persons with pTB. Multivariable regression models were fitted using a forward, stepwise procedure. Sensitivity analyses excluded treatment delays over two years and the year 2020. Data were analysed using Stata 17. Between 2015 and 2020 there were 812 persons with pTB among South West residents. Median treatment delays were 35 days for presentation and 25 days for healthcare delay. Multivariable analysis identified that longer presentation delays were associated with being aged 35–50 or over 80 years old. Longer healthcare delays were associated with increasing age (hazard ratio [HR]: 0.99, 95% CI: 0.98–0.99), being employed (HR: 0.71, 95% CI: 0.52–0.97) and people currently or historically deprived of their liberty and accommodated by a prison (HR: 0.33, 95% CI: 0.20–0.54). Shorter healthcare delays were associated with sputum smear positivity (HR: 1.54, 95% CI: 1.16–2.06) and smoking (HR: 1.64, 95% CI: 1.22–2.22). Delays between symptom onset and TB treatment remain an important public health problem in the region. Factors have been identified that can be investigated to reduce presentation and healthcare delays. Detailed analyses were valuable in disaggregating key populations. Further mixed-methods research would be warranted to further understand these associations.

LDSC: enhancing lung disease diagnosis using a simple 1D-CNN

Understanding what Australians find fearful and hopeful about climate change through qualitative approaches

Future-oriented emotional appeals, such as fear or hope, may be more effective in increasing climate action when they reflect the specific fears and hopes of the target population. However, qualitative evidence on what people find uniquely fearful and uniquely hopeful about climate change remains limited. To address this gap, an online qualitative survey asked 299 Australians ( M age  = 33.09, SD age  = 12.14) to identify what they found fearful and hopeful about climate change. Through inductive thematic analysis, three themes reflected Australians’ fear: (1) ‘Change and Instability’, (2) ‘Inaction and Negligence by Government, Large Corporations, and Others’, and (3) ‘Intergenerational Impacts and Legacy’. Additionally, three themes reflected Australians’ hope: (1) ‘Changing Attitudes and Changing Pro-environmental Habits’, (2) ‘Progress, Technology, Sustainability, and Innovation’, and (3) ‘An Opportunity for Change’. While some elements of what Australians find fearful or hopeful may be unique (e.g., bushfires), others (e.g., intergenerational impacts) align with global concerns. These insights offer valuable guidance for designing interventions that aim to foster fear and hope to promote climate action.

Predicting carbon storage changes in coal mining regions: a remote sensing approach based on the PIM-PLUS-INVEST model

What the landscape can tell: An integrative stratigraphic prospection approach to localize a Black Death mass grave in Erfurt/Central Germany

The Black Death pandemic (1346–53 AD) caused a 30–50% population decline across Europe. For the city of Erfurt in Thuringia, substantial human losses and corresponding mass graves are well-documented in historical archives. The aim of our study is to localize these mass graves in the nearby deserted village of Neuses in order to validate the written sources and to obtain skeletal remains for future anthropological and archeogenetic analyses. Here we present our integrative approach of historical research and minimally-invasive stratigraphic and geophysical prospection. Within the area of interest, narrowed down by historical accounts and GIS implementations, we applied percussion coring and electrical resistivity tomography (ERT). Coupled geophysical and coring sections help elucidate the late Quaternary sedimentary processes as an essential natural background for more detailed geoarcheological prospections. They allow to designate two distinct soil zones with consistent stratigraphical and pedogenic sequences: (1) a Chernozem zone and (2) a Black Floodplain Soil (humic fluvisol) zone. The distribution and extent of these zones co-determined the internal structure of the former village Neuses and the positioning of the presumed associated Black Death mass graves. Our approach enables a preliminary reconstruction of the medieval subsurface architecture, despite large-scale 20 th century ground modification. We identified a belowground pit structure, visible in both, the borehole sequences and ERT sections. Recovered bones have been AMS radiocarbon-dated to the 14 th century AD. Since confirmed and precisely-dated locations of Black Death mass graves are rare in Europe and are commonly found by chance during construction works, our systematic discovery of a possible plague pit may help to advance the research on the origin, spread and evolution of the Yersinia pestis pathogen throughout this pandemic as well as on societal coping mechanisms during epidemic outbreaks. Furthermore, our combination of methods holds the potential to successfully resolve the mapping of similarly demanding sites for archeological and forensic investigations.

Transformer-assisted convolutional feature extraction with deep representation learning models for lung and colon cancer diagnosis using histopathological images

A new index for frequency stability assessment in Low-Inertia Power Systems

As grid-forming converters (GFM) and grid-following converters (GFL) continue to be integrated into low-inertia power systems in place of traditional synchronous generators, the characteristics and forms of system inertia have undergone significant transformation. This evolution poses significant challenges to conventional inertia response mechanisms and analytical methodologies. To address these challenges, this study proposes a novel grid index frequency stability margin (FSM) from the perspective of frequency stability, encompassing its definition, quantitative evaluation, and practical applications. This paper first introduces the mathematical foundations and operational definitions of the FSM. It then systematically investigates the factors influencing FSM and presents a comprehensive mathematical model specifically developed for low-inertia power systems. The FSM calculation method based on aggregated system modelling was developed, followed by the derivation of a simplified estimation approach suitable for practical engineering applications. The effectiveness of the FSM in analyzing the frequency stability of low-inertia grids was validated through case studies based on provincial-level power grid data from China and a modified IEEE 39-bus system. The findings establish a theoretical framework for optimizing the planning and development of new energy power plants, as well as for formulating grid operation control strategies. This framework offers essential guidance to ensure the secure and stable operation of low-inertia power systems.

Hybrid CFD and machine learning analysis of CO2 enhanced oil recovery in naturally fractured reservoirs

Abstract CO 2 based Enhanced Oil Recovery (EOR) in unconventional reservoirs is an emerging technology. Scientific research efforts are directed towards understanding the propagation of CO 2 front due to the complex interplay between CO 2 injection and saturation, and reservoir’s constitutive relationships. Conventional methods for characterising CO 2 -EOR rely on high-fidelity numerical solutions that often result in over or under prediction of CO 2 geosequestration. In this study, we develop a novel hybrid Computational Fluid Dynamics (CFD) and Machine Learning (ML) framework that allows for rapid CO 2 geosequestration prediction and its optimal injection. Very low or high injection rates have been shown to result in low sweep efficiency or excessive entry pressure, while an intermediate injection rate offers the best balance between the two. CFD data-driven Gaussian Process Regression (GPR) and Extreme Gradient Boosting (XGBoost) models have been developed, trained and tested for predicting CO 2 saturation in the reservoir. Comparative analysis indicates that GPR outperforms XGBoost in terms of its predictive performance and robustness. Through the analysis of layer-resolved CO 2 front displacement and development of data-driven surrogate models, this study contributes a novel framework for CO 2 -EOR predictive modelling and optimising injection strategies in naturally fractured reservoirs.

Correction: Influence of palliative care policy on place of death for people with different cancer types: A nationwide’ register study

Effect of sewage sludge and mineral fertilization on ethanol production from Jerusalem artichoke and optimization of the bioconversion process

Health system responsiveness and its associated factors for delivery care in public health facilities of West Arsi Zone, Oromia, Ethiopia

Background Health System Responsiveness is defined as how well the health system meets the legitimate expectations of the population for the non-health enhancing aspects of the health system. As Ethiopia approaches the conclusion of the Health Sector Transformation Plan-II (HSTP-II), generating evidence on health system responsiveness is critical for evaluating progress and guiding future strategies. However, there remains a scarcity of empirical evidence on health system responsiveness, particularly in the context of delivery care services. Objective The primary aim of this study was to assess the health system responsiveness and its associated factors for delivery care in public health facilities of West Arsi Zone, Oromia, Ethiopia. Methods A health facility-based cross-sectional study was conducted among 617 mothers who gave birth in the selected public health facilities of West Arsi Zone, Oromia Region. Data were collected from 24/02/2025–26/04/2025. Systematic random sampling technique was used to approach study participants. Health system responsiveness was measured using eight domains namely dignity, autonomy, confidentiality, communication, prompt attention, social support, choice and basic amenities each item rated on 1–5 scale. Mothers with median score ≥112 were categorized as having good responsiveness performance for delivery care whereas <112 were considered as poor responsiveness for delivery care. Data was entered and analyzed using SPSS version 25. Both bi-variable and multivariable logistic regression analysis were done to identify association between dependent and independent variables. Crude and adjusted odds ratios with respective 95% confidence intervals were computed and statistical significance was declared at p-value <0.05. Result The overall level of good health system responsiveness for delivery care was found to be 51.4% (95% CI 47.4–55.4). The highest and least performance score was reported in the social support domain (62.9%) and choice domain (51.7%) respectively. Adverse neonatal outcome (AOR = 0.50, 95% Cl (0.31, 0.82), obstetrics complications (AOR = 0.47, 95% Cl (0.26, 0.85), history of admission during current pregnancy (AOR = 0.58, 95% Cl (0.35, 0.96) were factors significantly associated with health system responsiveness. Conclusions More than half of the respondents reported that the overall level of health system responsiveness during delivery was good. Adverse neonatal outcome, obstetrics complications and history of admission during current pregnancy had shown statistically significant association with health system responsiveness for delivery care. Enhancing health system responsiveness during delivery needs targeted investments in infrastructure, continuous training for healthcare providers, and tailored support for women who experience adverse neonatal outcomes or obstetric complications. Strengthening these areas is essential for ensuring respectful, timely, and women centered maternity care.

An intelligent hybrid deep learning-machine learning model for monthly groundwater level prediction

Extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella pneumoniae from human carriage, the human-polluted environment, and food: Molecular epidemiology of two prospective cohorts in five European metropolitan areas

Objectives For 475 ESBL-producing Escherichia coli (ESBL-Ec), and 171 ESBL-producing Klebsiella pneumoniae (ESBL-Kp) collected from human carriers, the human-polluted (hp)-environment, and food: (i) to compare the antimicrobial resistance gene (ARG) content, and (ii) to assess clonal relationships between human and non-human isolates. Materials and methods Two prospective multicenter cohorts were assessed: colonized hospitalized index-subjects and household contacts, and long-term care facility (LTCF) residents. Additionally, linked hp-environment and food samples were collected. Presence of ARGs were assessed using pairwise comparisons and proportional similarity index (PSI). Clonal relationships were assessed using cgMLST distance visualizations and maximum likelihood phylogeny. Results ESBL-Ec and ESBL-Kp co-occurred in 14/65 households, 3/6 LTCFs, and in 33/202 of ESBL-positive participants. Thirty-nine percent of detected ARG types were found in both species (36/93). Frequencies of beta-lactamase, ESBL, aminoglycoside, and sulfonamide ARG types from human ESBL-Ec and ESBL-Kp overlapped considerably: PSIs 0.59–0.75, and were equal or higher compared to the overlap between ESBL-Ec from humans and food isolates: PSIs 0.33–0.72. Isolates from humans and the hp-environment were frequently clonally related, indicating human contamination of the environment. Links with food isolates were observed less frequently. For ESBL-Ec both interregional and regional clonal dissemination were observed, while for ESBL-Kp clonal dissemination was mainly regional. Conclusions ESBL-Ec and ESBL-Kp from human carriage showed considerable overlap in ARG content. Furthermore, clonal links were observed frequently between humans and hp-environment, and with lower frequency between humans and food. These findings are consistent with human-to-human transmission as an important driver of ARG spread in humans.

Restoration of deuterium marker for multi-isotope mapping of cellular metabolic activity

Abstract Investigation of cellular metabolic activity with stable-isotope probing (SIP) implies the admittance of an isotope tracer into the metabolic pathway. Incubation with several isotope-markers (multi-isotope tracing) is required to trace nutrient metabolization and elucidate inter-cellular interactions in complex hosts and environmental communities. To cope with the lability of cell nutrition, deuterium in heavy 2 H 2 16 O water is employed as a substrate-independent general tracer of metabolic activity. However, the spatially-resolved deuterium tracing is hampered by detection limits due to its relatively low ionization yield and mass-interference issues. In the present work, we comprehensively assess the quantitation of deuterium incorporation into biomass employing the outstanding capabilities of nanoscale Secondary Ion Mass Spectrometry facilitating quantitative analysis of metabolic activity with single-cell or subcellular resolution. The effect of ion-probe-induced material relocation on the acquired pattern in 2 H enrichment has been considered. Analytical expressions are suggested for the restoration of the deuterium fraction from the unresolved C 2 2 H–C 2 1 H 2 mass-interference. Application of the suggested principle of equal relative assimilation and the multi-isotope tracing with the 2 H-marker on a phototrophic symbiotic consortium paves the way to sensing the metabolic interplay among cells, recognition of homeostatic and shifted nutrition, checking for completeness of isotope-labelling and elucidation of nonlabelled substrate contribution.

A distributed framework for zero-day malware detection using federated ensemble models

Classification and detection of zero-day attacks remain a significant challenge within the domain of cybersecurity. Due to the vast types of malware families and the presence of an imbalanced dataset, real-time detection and classification become increasingly complex and inaccurate. Thus, there’s an urgent need to develop an intelligent and adaptive defense mechanism capable of identifying and classifying such attacks with improved precision and robustness. This paper proposed a stacked ensemble federated learning model with an accuracy-aware node weighting scheme to address the challenges posed by inter- and intra-class similarities among different types of malwares. In the initial phase, malware Portable Executable (PE) files are collected from multiple online repositories and validated by three different antivirus programs through VirusTotal to ensure reliability. These validated files are then converted into image form and categorized into 28 families to facilitate feature extraction. In the second phase, deep feature representations are extracted through a transfer learning-based fine-tuned ResNet-50 model, which captures both low-level and high-level patterns that are relevant to malware classification. After feature extraction from multiple distributed nodes, architecture is fed into the novel proposed Ensemble Stacked Federated Model for enhanced generalization and robust classification. The model is tested on both private and publicly available datasets. The experimental results demonstrate that the proposed method outperforms existing baseline approaches in terms of accuracy and computational efficiency. This improvement is achieved because it performs independent training at each federated node separately and then stacks their outputs with a central ensemble model, which enhances the learning rate and reduces overfitting. The code used for the experiments is available here.

AI driven hybrid convolutional and transformer based deep learning architecture for precise lung nodule classification

Diets and environments of late pleistocene pygmy and Columbian mammoths: Isotopic evidence from Southern California

Pygmy mammoths ( Mammuthus exilis ) and Columbian mammoths ( Mammuthus columbi ) coexisted on the island of Santarosae (now the Northern Channel Islands of California) until the Late Pleistocene megafaunal extinctions, but the ecology of these mammoths is not yet well explored. In this study, we reconstructed the diets and environments of Late Pleistocene pygmy and Columbian mammoths using stable isotopes in tooth enamel samples from the Northern Channel Islands and Rancho La Brea. The enamel δ 13 C values indicate that these mammoths primarily consumed C 3 vegetation. However, a few individuals consumed significant amounts of C 4 plants, CAM plants, or water-stressed woody C 3 plants. The mean diet-δ 13 C value for mainland mammoths (−24.2 ± 1.4‰) is about 2‰ higher than that of island mammoths (−26.4 ± 1.9‰), suggesting that most mainland mammoths consumed either water-stressed C 3 vegetation, or some C 4 and/or CAM plants. Reconstructed δ 18 O values of paleo-water from the mainland are generally lower than the mean δ 18 O values of modern precipitation in Southern California, suggesting conditions were wetter and/or cooler than today. Reconstructed δ 18 O values of paleo-water from the islands are more similar to modern precipitation. δ 13 C-based estimates of mean annual precipitation range from 159 to 1407 mm/yr on the islands and from 28 to 387 mm/yr on the mainland. However, consumption of small amounts of C 4 and/or CAM plants may have resulted in an underestimation of precipitation for the mainland. Radiometric dating of additional fossils from both localities will help clarify the links between climate change and mammoth evolution and extinction in the region.