143174 research outputs found
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Subcellular-resolution molecular pathology by laser ablation-rapid evaporative ionization mass spectrometry
No full textThis work demonstrates the combination of ambient laser ablation (LA) with in-source surface-induced declustering, originally developed for rapid evaporative ionization mass spectrometry (REIMS). This combination, termed laser ablation REIMS (LA-REIMS), provides sensitivity, spatial resolution, and chemical coverage comparable to matrix-assisted laser desoprtion ionization (MALDI) but without the requirement for matrix deposition. The atmospheric pressure interface setup was subjected to detailed characterization with regard to geometric and thermal parameters augmented by in-silico flow modeling. The resulting platform was tested using aerosol formed by the infrared laser ablation of tissues. Three different laser systems were successfully employed for ambient mass spectrometric imaging: a carbon dioxide laser (λ = 10.6 μm, τL = ∼100 μs), an optical parametric oscillator (OPO; λ = 2.94 μm, τL = 8 ns), and an optical parametric amplifier (OPA; λ = 3.0 μm, τL = ∼30 ps). Single-cell imaging was achieved using the high-resolving capabilities of the OPA systems, and metabolites and lipids ranging from amino acids through carbohydrates and nuclear bases to complex glycolipids were successfully detected. The technique was also tested as a platform for MS-guided surgery, raising the possibility of using a single technique for generating histological and in vivo data
Computational modelling of diffusion tensor cardiovascular magnetic resonance: effects of membrane permeability, perfusion and strain
No full textDiffusion Tensor Cardiovascular Magnetic Resonance (DT-CMR) is a histology-validated, non-invasive imaging technique that assesses the average microstructure of the myocardium within a specific voxel region (usually around 2 × 2 × 8 mm³) by analyzing the direction and magnitude of the self-diffusion of water molecules (Brownian motion). However, due to motion artifacts, confounding factors, and complex tissue microstructure, the sensitivity of DT-CMR tensor parameters to the microstructural characteristics—as well as the link between the tensor parameters and such characteristics—remains poorly understood. Numerical phantoms offer a controlled framework to elucidate this link by allowing the independent manipulation of variables in a physically well-defined model. This thesis aims to enhance DT-CMR simulations by integrating several key biophysical processes, thereby improving the understanding of tensor sensitivity across in-vivo sequences of clinical relevance. Specifically, this work introduces several key methodological advances for Monte Carlo Random Walk (MCRW) simulations of DT-CMR: the implementation of a hybrid transit model that accurately and efficiently simulates membrane permeability; an enhanced perfusion model incorporating both temporal variations in capillary flow and inter-capillary velocity dispersion; and a validated strain implementation. Additionally, a sheetlet packer framework is developed and validated against histology data, enabling the efficient generation of realistic cardiac microstructure.Open Acces
Does Stochastic Gradient really succeed for bandits?
No full textRecent works of Mei et al. [1, 2] have deepened the theoretical understanding of the Stochastic Gradient Bandit (SGB) policy, showing that using a constant learning rate guarantees asymptotic convergence to the optimal policy, and that sufficiently small learning rates can yield logarithmic regret. However, whether logarithmic regret holds beyond small learning rates remains unclear. In this work, we take a step towards characterizing the regret regimes of SGB as a function of its learning rate. For two–armed bandits, we identify a sharp threshold, scaling with the sub-optimality gap ∆, below which SGB achieves logarithmic regret on all instances, and above which it can incur polynomial regret on some instances. This result highlights the necessity of knowing (or estimating) ∆ to ensure logarithmic regret with a constant learning rate. For general K-armed bandits, we further show the learning rate must additionally scale inversely with K to avoid polynomial regret. We introduce novel techniques to derive regret upper bounds for SGB, laying the groundwork for future advances in the theory of gradient-based bandit algorithms
Fungal-microbial interactions impacting the physico-chemical and structural integrity of concrete
No full textFilamentous fungi are prevalent in concrete environments, impacting its physico-chemical properties and leading to either fungal-induced deterioration (FID) or self-healing. These opposing effects are facilitated by the unique mycelial structure of fungi, which penetrate the concrete matrix to acquire and transport organic resources and nutrients, as well as their ability to secrete organic acids. Preventing FID and enhancing self-healing are crucial for reducing maintenance costs and promoting sustainable construction materials. This study examined the effects of three common fungal strains in building environment — Aspergillus niger, Cladosporium sphaerospermum, Fusarium oxysporum, and environmental isolates of A. niger and F. oxysporum, on the microstructural properties of mortar, and the chemical (focussing on oxalic acid) and physical mechanisms influencing FID and self-healing of different mortar types and under different environmental conditions.
Aspergillus niger produced oxalic acid, forming a large quantities of bipyramidal calcium oxalate dihydrate (COD) crystals and their large size of aggregates that expand and, coupled with hyphal penetration, cause progressive FID of the mortar outer layers. In contrast, FID induced by C. sphaerospermum is milder, mainly discoloration from melanin release and minor surface spalling due to oxalic or citric acid production. In contrast, F. oxysporum generated tubular-like precipitates and bipyramidal-prism crystals of COD, which, combined with fungal hyphae, filled mortar pores and cracks, promoting self-healing by increasing the mortar mass and reducing mortar porosity. Among all mortar and environmental condition treatments, reducing the water/cement ratio limited FID and increased self-healing processes to the greatest extent, while, the soil environment promoted the most aggressive FID and inhibited self-healing.
This study is the first to identify aggregates of bipyramidal COD and singular bipyramidal-prism COD crystals in mortar samples due to the microstructural effects of filamentous fungi, and the contrasting roles of oxalic acid in FID and self-healing of concrete is first reported.Open Acces
Programmable cell–cell adhesion in synthetic yeast communities for improved bioproduction
No full textIn multicellular systems, engineering-controlled cell–cell adhesion and metabolic interdependence are vital for developing complex functionalities. This study introduces a yeast synthetic toolbox for modular cell–cell adhesion and cocultures, aiming to overcome the limitations of existing approaches that lack genetic specificity and control. First, a model yeast strain 007Δ is created with seven main flocculation and agglutination genes removed, providing a clean background for synthetic adhesion systems. Then, three distinct adhesion pair systems—Strategy 1, Strategy 2.1 and Strategy 2.2—are established involving yeast flocculation and agglutination proteins and yeast surface display systems. In addition, a quantitative assessment is conducted on the adhesive specificity and strength, alongside the capability of synthetic adhesion to generate patterns. Finally, we successfully demonstrate enhanced bioproduction of the high-value food antioxidant, resveratrol, utilizing synthetic cocultures coupled with cell adhesion systems. We anticipate that this toolkit will emerge as a valuable resource for diverse applications in synthetic biology and biomanufacturing
Magnetically retrievable platinum nanoreporters for efficient lateral flow immunoassay in complex bio-samples
No full textLateral flow immunoassays (LFIAs) are widely used for point-of-care diagnostics, but their development is challenged by the complexity and variability of patient samples. In particular, LFIAs often exhibit reduced sensitivity and specificity when used with patient samples, compared to their performance with analyte-spiked idealized matrices. Patient samples are inherently complex, with variations in physical and biochemical properties between patients. This complexity has consequences for the performance of LFIAs, and can result in non-specific binding on the test line, discoloration of the nitrocellulose membrane, and incomplete sample flow along the test strip. To address these challenges, a magnetically retrievable platinum nanoreporter (termed Pt@Fe3O4) is developed for LFIAs. Leveraging the magnetic properties of the Fe3O4 core, magnetic separation is utilized to enable the purification and concentration of target antigens from complex human matrices, including serum, saliva, and even stool samples. This also eliminates assay inconsistencies caused by inter-sample variability. Further, the suitability of Pt@Fe3O4 nanoreporters has been explored for use as detection probes in LFIAs. Signal enhancement is demonstrated by the utilization of the magnetic and enzyme-mimicking activity of the nanoreporter, resulting in a marked improvement in sensitivity, as evidenced by a 2- to 4-fold decrease in the visual limit of detection
Usage patterns, knowledge, and attitudes of healthcare providers regarding e-cigarettes: a cross-sectional study in Saudi Arabia
No full textIntroduction:
As electronic cigarettes (e-cigarettes) gain global popularity, healthcare providers (HCPs) play a critical role in shaping public health responses. In Saudi Arabia, little is known about HCPs’ perspectives on e-cigarettes. Hence, this study aimed to evaluate HCPs’ knowledge and attitudes toward e-cigarette use and examine differences based on their personal usage patterns.
Methods:
This is an observational, cross-sectional study. An online questionnaire was distributed from February to May 2024 among HCPs in Saudi Arabia. The survey, which was previously validated, collected data on sociodemographic, smoking characteristics, and 17 items designed to assess HCPs’ knowledge and attitudes about e-cigarette use.
Results:
A total of 301 HCPs participated in the study. Among the participants, 19.3% were nurses, 18.9% were PharmDs, 13.2% were dentists, 24.3% were respiratory therapists (RTs), and 24.3% were medical doctors (MDs). Approximately 64% of the respondents were male, and the median age was 32 years (IQR: 22– 55). E-cigarette users comprised 22.9% of the respondents. The prevalence of e-cigarette use was highest among dentists (20.0%), with lower rates observed among respiratory therapists (11.0%), nurses (8.6%), pharmacists (7.0%), and medical doctors (6.8%). The majority of respondents (68.1%) recognized that e-cigarettes contain nicotine, 64.5% believed that e-cigarettes are addictive, and 48.9% were unsure whether e-cigarettes are FDA-approved products. Additionally, 33.3% of HCPs relied primarily on social media for information about e-cigarettes. HCPs strongly agreed [median score: 5 (IQR: 4–5)] that HCPs should be educated about e-cigarettes. HCPs who used e-cigarettes exhibited significantly more favorable attitudes toward e-cigarettes compared to non-users, based on the total score (p=0.020).
Conclusions:
HCPs’ knowledge and attitudes regarding e-cigarettes vary widely in Saudi Arabia. Specific, targeted, and regularly updated educational initiatives are needed to ensure that healthcare professionals are confident and well informed regarding the use, risks, and guidelines related to e-cigarettes
Ultrasonic signal decomposition through gradient descent assisted successive parameter estimation
No full textAccurate decomposition of ultrasonic signals into simple pulses is valuable both for data compression purposes, as well as various medical and engineering applications. This work proposes a matching pursuit (MP) based algorithm that deploys a traditional successive parameter estimation approach, to express ultrasonic signals as sums of Gaussian pulses or chirplets. However, here the MP algorithm is aided by mathematical optimisation (gradient descent), which allows for significantly more precise parameter estimation. Our method is validated on simple input signals, and following its validation, its performance is assessed against cases of increasing complexity. The results not only suggest the accuracy and robustness of our approach, but also show how the proposed method performs well with signals containing strongly overlapping pulses, a challenge for existing methods. Results are also obtained from realistic signals generated through finite element modelling or experimental measurements. Finally, beyond the reconstruction results, we discuss and demonstrate how even complicated signals are well described through only a few parameters, eliminating the need for storing full time traces, allowing for effective ultrasonic data compression
Transitioning to da Vinci Xi for colorectal cancer surgery: a prospective cohort study of 102 cases from a UK centre with a structured robotic programme
No full textThis study evaluated short-term outcomes and learning curves following the introduction of the Intuitive© da Vinci Xi robotic platform for elective colorectal cancer resections at West Hertfordshire Teaching Hospital NHS Trust (WHTH). A smooth transition was enabled by prior experience with the CMR Surgical© Versius platform, with outcomes benchmarked against national data. A prospective cohort study included consecutive patients undergoing elective colorectal resections between April 2024 and March 2025. Data included demographics, diagnosis, operative details, complications, length of stay (LOS), and oncological outcomes. Results were compared with historical laparoscopic data from the National Bowel Cancer Audit (NBOCA, 2019–2022) and Model Health System (MHS, 2024). Learning curves for operative time were assessed using cumulative sum (CUSUM) analysis across three procedures: right hemicolectomy (RH), anterior resection (AR), and abdominoperineal resection (APR).
A total of 102 patients were included, with a median age of 69 years (IQR = 60–75), and 54.9% (n = 56) were male. All colonic resections (n = 72) achieved a lymph node yield ≥ 12, significantly higher than the 88.1% in NBOCA (p = 0.001). Among rectal resections (n = 30), 96.7% had negative margins versus 90.1% in NBOCA (p = 0.10). Conversion to open surgery was 3% (n = 3), the anastomotic leak rate was 1% (n = 1), and 4% (n = 4) required a return to theatre. MHS data showed that 13% of all colorectal patients at WHTH had a LOS ≥ 9 days, compared to 29% nationally (p = 0.0001), decreasing to 7.1% in the robotic cohort. CUSUM analysis showed stabilisation after ~ 12 right hemicolectomies and 20 low pelvic resections, with variability among surgeons. Surgeons with prior robotic experience achieved faster proficiency and generated time savings. The successful introduction of the da Vinci Xi platform at WHTH, supported by prior Versius experience, led to excellent oncological outcomes, shorter hospital stays, and low complication rates. These findings highlight the value of structured robotic implementation in advancing colorectal cancer care within the NHS