Search Results (89)

Background/Objectives: In response to the COVID-19 pandemic, we developed a vaccine candidate against SARS-CoV-2. Spike Ferritin Nanoparticle (SpFN) comprises 24 identical prefusion-stabilized spike proteins anchored to a self-assembled nanoparticle. Organized along the three-fold axis of the ferritin particle, eight SARS-CoV-2 spike trimers are presented per nanoparticle. Methods: Here, we describe the CGMP processes for manufacturing SpFN using transient transfection of Expi293F cells. Results: The final yield of SpFN was ~10 mg per liter of media supernatant. The resulting protein is stable in cold storage for two years at −20 °C, as well as for a month at room temperature, and can withstand multiple freeze/thaw cycles. SpFN material produced using the CGMP protocols adjuvanted with Army Liposomal Formulation-QS-21 (ALFQ) elicited potent neutralizing antibodies against WA-1, Alpha, Beta, and Delta variants in mice as measured by a pseudovirus neutralization assay. Conclusions: This work demonstrates rapid development and scaled-up production of clinical-grade SARS-CoV-2 vaccine protein material, allowing permissive storage and transport conditions, and serves as a framework for recombinant protein production for future emergent pathogens. Full article

Background: Colon capsule endoscopy (CCE) has seen increased adoption since the COVID-19 pandemic, offering a non-invasive alternative for lower gastrointestinal investigations. However, inadequate bowel preparation remains a key limitation, often leading to higher conversion rates to colonoscopy. Manual assessment of bowel cleanliness is inherently subjective and marked by high interobserver variability. Recent advances in artificial intelligence (AI) have enabled automated cleansing scores that not only standardise assessment and reduce variability but also align with the emerging semi-automated AI reading workflow, which highlights only clinically significant frames. As full video review becomes less routine, reliable, and consistent, cleansing evaluation is essential, positioning bowel preparation AI as a critical enabler of diagnostic accuracy and scalable CCE deployment. Objective: This CESCAIL sub-study aimed to (1) evaluate interobserver agreement in CCE bowel cleansing assessment using two established scoring systems, and (2) determine the impact of AI-assisted scoring, specifically a TransUNet-based segmentation model with a custom Patch Loss function, on both interobserver and intraobserver agreement compared to manual assessment. Methods: As part of the CESCAIL study, twenty-five CCE videos were randomly selected from 673 participants. Nine readers with varying CCE experience scored bowel cleanliness using the Leighton–Rex and CC-CLEAR scales. After a minimum 8-week washout, the same readers reassessed the videos using AI-assisted CC-CLEAR scores. Interobserver variability was evaluated using bootstrapped intraclass correlation coefficients (ICC) and Fleiss’ Kappa; intraobserver variability was assessed with weighted Cohen’s Kappa, paired t-tests, and Two One-Sided Tests (TOSTs). Results: Leighton–Rex showed poor to fair agreement (Fleiss = 0.14; ICC = 0.55), while CC-CLEAR demonstrated fair to excellent agreement (Fleiss = 0.27; ICC = 0.90). AI-assisted CC-CLEAR achieved only moderate agreement overall (Fleiss = 0.27; ICC = 0.69), with weaker performance among less experienced readers (Fleiss = 0.15; ICC = 0.56). Intraobserver agreement was excellent (ICC > 0.75) for experienced readers but variable in others (ICC 0.03–0.80). AI-assisted scores were significantly lower than manual reads by 1.46 points (p < 0.001), potentially increasing conversion to colonoscopy. Conclusions: AI-assisted scoring did not improve interobserver agreement and may even reduce consistency amongst less experienced readers. The maintained agreement observed in experienced readers highlights its current value in experienced hands only. Further refinement, including spatial analysis integration, is needed for robust overall AI implementation in CCE. Full article

The role of HAT-PCR (High A/T or High Annealing Temperature–PCR) in the quantification of minimal residual disease (MRD) was investigated in chronic lymphocytic leukemia (CLL) and myeloma. The IGH gene sequence was determined by next-generation sequencing (NGS), either by the Lymphotrack kit or by preparing libraries using an in-house two-round PCR protocol which enabled successful sequencing in 37/37 CLL marrow samples and 34/35 myeloma marrow samples. MRD was quantified by HAT-PCR in 125 CLL marrow or blood samples from 36 patients, with 2 results being less than 10⁻⁶ and in 63 myeloma marrow samples from 35 patients, with 10 results being less than 10⁻⁶. Measurement of MRD in 113 pairs of CLL samples and 51 pairs of myeloma samples showed that HAT-PCR was significantly more sensitive than flow. Compared to marrow MRD, blood MRD was relatively high in CLL but very low or undetectable in myeloma. Flow-positive HAT-PCR negative samples were not seen in myeloma, although the literature review suggested that flow-positive NGS-negative myeloma samples are sometimes observed. The ability of HAT-PCR to quantify down to and below 10⁻⁶ and the practical advantages of PCR suggest that HAT-PCR could be used widely for the quantification of MRD in lymphoid malignancy. Full article

ComPair, a prototype of the All-sky Medium Energy Gamma-ray Observatory (AMEGO), completed a short-duration high-altitude balloon campaign on 27 August 2023 from Fort Sumner, New Mexico, USA. The goal of the balloon flight was to demonstrate ComPair as both a Compton and Pair telescope in flight, reject the charged particle background, and measure the background $\gamma$-ray spectrum. This analysis compares measurements from the balloon flight with Monte Carlo simulations to benchmark the instrument. The comparison finds good agreement between the measurements and simulations and supports the conclusion that ComPair accomplished its goals for the balloon campaign. Additionally, two charged particle background rejection schemes are discussed: a soft ACD veto that records a higher charged particle event rate but with less risk of event loss, and a hard ACD veto that limits the charged particle event rate on board. There was little difference in the measured spectra from the soft and hard ACD veto schemes, indicating that the hard ACD veto could be used for future flights. The successes of ComPair’s engineering flight will inform the development of the next generation of ComPair with upgraded detector technology and larger active area. Full article

Output from a machine learning tool that assigns a probability that a severe thunderstorm wind report was caused by severe intensity wind was evaluated to understand counterintuitive cases where reports that had a high (low) wind speed received a low (high) diagnosed probability. Meteorological data for these cases was compared to that for valid cases where the machine learning probability seemed consistent with the observed severity of the winds. The comparison revealed that the cases with high winds but low probabilities occurred in less conducive environments for severe wind production (less instability, greater low-level relative humidity, weaker lapse rates) than in the cases where high winds occurred with high probabilities. Cases with a low speed but a high probability had environmental characteristics that were more conducive to producing severe wind. These results suggest that the machine learning model is assigning probabilities based on storm modes that more often have measured severe wind speeds (i.e., clusters of cells and bow echoes), and counterintuitive values may reflect events where storm interactions or other smaller-scale features play a bigger role. In addition, some evidence suggests improper reporting may be common for some of these counterintuitive cases. Full article

The phytochemical screening of extracts of Tacca leontopetaloides tubers has afforded the isolation of two novel chalcones, tarkalynins A and B, along with taccalonolide A and its 12-propanoate. The screening of Zanthoxylum zanthoxyloides stem bark yielded taraxerol acetate, dihydrochelerythrin and fagaramide. These compounds were obtained through column and thin-layer chromatography and identified using NMR and LC-HRMS. The compounds were tested against Trypanosoma brucei brucei s427 and its multi-drug-resistant clone B48, against Trypanosoma evansi, Trypanosoma equiperdum and Trypanosoma congolense, and against Leishmania mexicana. Cytotoxicity was tested against the human HEK293 cell line. The highest activities were observed with dihydrochelerythrin and fagaramide against T. b. brucei s427 and B48, T. evansi, and L. mexicana, with EC₅₀ values of 1.37, 2.559, 1.09, and 5.44 µM and 17.8, 10.9, 10.9, and 13.3 µM, respectively. In addition, tarkalynin A and taraxerol acetate displayed promising activity against T. equiperdum (EC₅₀ = 21.4 and 21.3 µM, respectively). None of these compounds showed significant cross-resistance with existing trypanocides (RF ≈ 1; p > 0.05). The compounds displayed low toxicity to human cells, with most exhibiting no growth inhibition at concentrations of 100, or even 300 µM. This report provides further evidence of the potential use of natural products for combating parasitic diseases. Full article

Tryptophan hydroxylase 2 (TPH2) hydroxylates L-tryptophan to L-5-hydroxy tryptophan—the key step of 5-HT synthesis in the mammalian brain. Some mutations in the human hTPH2 gene are associated with psychopathologies and resistance to antidepressant therapy. The C1473G polymorphism in the mouse Tph2 gene decreases the TPH2 activity in the mouse brain. In the present paper, B6-1473C and B6-1473G congenic mice that were different only in the C > G substitution were used. The molecular mechanism of decrease in the mutant enzyme activity and some physiological and behavioral traits affected by this mutation were revealed for the first time. Analysis of thermal denaturation curves in vitro revealed that the C > G substitution reduces the free energy of denaturation, stability and lifetime of mutant TPH2. Later, we evaluated the effect of the 1473G allele on the hierarchical state, competition for a sexual partner in adult mice, mouse embryos, hind legs dystonia and the response to LPS treatment in young mice. No effect of this mutation on the hierarchical state and competition for a female was observed in adult males. The C > G substitution does not affect survival, body mass or the TPH activity in the brain of 19-day-old mouse embryos. At the same time, we found that the 1473G allele causes hind legs dystonia in juvenile (3 weeks old) mice, which can affect their escape capability in threatening situations. Moreover, a significant increase in the vulnerability to LPS in juvenile B6-1473G males was shown: a single ip LPS administration killed about 40% of young mutant mice, but not wild-type ones. The body mass of mutant males was lower compared to wild-type ones, which also can indirectly decrease their concurrent and reproductive success. Full article

In 2022, 26–31% of young adults reported using e-cigarettes in the previous 30 days. Research supports the effectiveness of mass media health campaigns in changing targeted attitudes and behaviors regarding nicotine use. However, the effect of social media campaigns and the pathway through which they change attitudes and behaviors require more research. This randomized controlled experiment examines the pathway through which exposure to an e-cigarette prevention social media campaign influences intentions to quit e-cigarettes among young adults who currently use e-cigarettes. Participants (n = 160) aged 18 to 24 years old were recruited through Virtual Lab in Facebook and Instagram. Structural equation modeling (SEM) was used to examine the pathway from campaign exposure, to changes in targeted attitudes, and finally to intentions to quit e-cigarettes in the next year. Ad exposure was significantly associated with stronger anti-industry attitudes, independence from e-cigarettes, and risk perceptions. These campaign-targeted attitudes were significantly associated with greater intentions to quit e-cigarettes (anti-industry attitudes (OR = 1.43), independence (OR = 1.50), and risk perception (OR = 1.71)). The findings suggest that exposure to an e-cigarette prevention social media campaign can affect targeted attitudes, which in turn improve intentions to quit. Future research should examine behavior changes and compare the effects between those currently using e-cigarettes and those not using them. Full article

This paper considers a decentralized and autonomous wireless network of low SWaP (size, weight, and power) fixed-wing UAVs (unmanned aerial vehicles) used for remote exploration and monitoring of targets in an inaccessible area lacking communication infrastructure. Here, the UAVs collaborate to find target(s) and use routing protocols to forward the sensed data of target(s) to an aerial base station (BS) in real-time through multihop communication, which can then transmit the data to a control center. However, the unpredictability of target locations and the highly dynamic nature of autonomous, decentralized UAV networks result in frequent route breaks or traffic disruptions. Traditional routing schemes cannot quickly adapt to dynamic UAV networks and can incur large control overhead and delays. In addition, their performance suffers from poor network connectivity in sparse networks with multiple objectives (exploration and monitoring of targets), which results in frequent route unavailability. To address these challenges, we propose two routing schemes: Pipe routing and TC-Pipe routing. Pipe routing is a mobility-, congestion-, and energy-aware scheme that discovers routes to the BS on-demand and proactively switches to alternate high-quality routes within a limited region around the routes (referred to as the “pipe”) when needed. TC-Pipe routing extends this approach by incorporating a decentralized topology control mechanism to help maintain robust connectivity in the pipe region around the routes, resulting in improved route stability and availability. The proposed schemes adopt a novel approach by integrating the topology control with routing protocol and mobility model, and rely only on local information in a distributed manner. Comprehensive evaluations under diverse network and traffic conditions—including UAV density and speed, number of targets, and fault tolerance—show that the proposed schemes improve throughput by reducing flow interruptions and packet drops caused by mobility, congestion, and node failures. At the same time, the impact on coverage performance (measured in terms of coverage and coverage fairness) is minimal, even with multiple targets. Additionally, the performance of both schemes degrades gracefully as the percentage of UAV failures in the network increases. Compared to schemes that use dedicated UAVs as relay nodes to establish a route to the BS when the UAV density is low, Pipe and TC-Pipe routing offer better coverage and connectivity trade-offs, with the TC-Pipe providing the best trade-off. Full article

The objective of this study was to evaluate the effectiveness of utilizing radiomic features from radiation planning computed tomography (CT) scans in predicting tumor progression among patients with cervical cancers. A retrospective analysis was conducted on individuals who underwent radiotherapy for cervical cancer between 2015 and 2020, utilizing an institutional database. Radiomic features, encompassing first-order statistical, morphological, Gray-Level Co-Occurrence Matrix (GLCM), Gray-Level Run Length Matrix (GLRLM), and Gray-Level Dependence Matrix (GLDM) features, were extracted from the primary cervical tumor on the CT scans. The study encompassed 112 CT scans from patients with varying stages of cervical cancer ((FIGO Staging of Cervical Cancer 2018): 24% at stage I, 47% at stage II, 21% at stage III, and 10% at stage IV). Of these, 31% (n = 35/112) exhibited tumor progression. Univariate feature analysis identified three morphological features that displayed statistically significant differences (p < 0.05) between patients with and without progression. Combining these features enabled a classification model to be developed with a mean sensitivity, specificity, accuracy, and AUC of 76.1% (CI 1.5%), 70.4% (CI 4.1%), 73.6% (CI 2.1%), and 0.794 (CI 0.029), respectively, employing nested ten-fold cross-validation. This research highlights the potential of CT radiomic models in predicting post-radiotherapy tumor progression, offering a promising approach for tailoring personalized treatment decisions in cervical cancer. Full article

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is an enzymopathy that affects approximately 500 million people worldwide. A great number of mutations in the G6PD gene have been described. However, three class A G6PD variants known as G6PD Tomah (C385R), G6PD Kangnam (C385G), and G6PD Madrid (C385W) have been reported to be clinically important due to their associations with severe clinical manifestations such as hemolytic anemia. Therefore, this work aimed to perform, for the first time, biochemical and functional characterizations of these variants. The G6PD variants were cloned and purified for this purpose, followed by analyses of their kinetic parameters and thermal stability, as well as in silico studies. The results showed that the mutations induced changes in the proteins. Regarding the kinetic parameters, it was observed that the three variants showed lower affinities for G6P and NADP⁺, as well as lower thermal stability compared to WT-G6PD. Molecular dynamics simulations showed that C385 mutations induced changes around neighboring amino acids. Metadynamics simulations showed that most remarkable changes account for the binding pocket volumes, particularly in the structural NADP⁺ binding site, with a concomitant loss of affinity for catalytic processes. Full article

Skin cancer is the most common type of cancer in the United States and is estimated to affect one in five Americans. Recent advances have demonstrated strong performance on skin cancer detection, as exemplified by state of the art performance in the SIIM-ISIC Melanoma Classification Challenge; however, these solutions leverage ensembles of complex deep neural architectures requiring immense storage and computation costs, and therefore may not be tractable. A recent movement for TinyML applications is integrating Double-Condensing Attention Condensers (DC-AC) into a self-attention neural network backbone architecture to allow for faster and more efficient computation. This paper explores leveraging an efficient self-attention structure to detect skin cancer in skin lesion images and introduces a deep neural network design with DC-AC customized for skin cancer detection from skin lesion images. We demonstrate that our approach with only 1.6 million parameters and 0.32 GFLOPs achieves better performance compared to traditional architecture designs as it obtains an area under the ROC curve of 0.90 on the public ISIC 2020 test set and 0.89 on the private ISIC test set, over 0.13 above the best Cancer-Net SCa network architecture design. The final model is publicly available as a part of a global open-source initiative dedicated to accelerating advancement in machine learning to aid clinicians in the fight against cancer. Future work of this research includes iterating on the design of the selected network architecture and refining the approach to generalize to other forms of cancer. Full article

Background: Moderate to severe (M2S) atopic dermatitis (AD) is a chronic condition impacting individuals, society, and healthcare systems. Considering the changing M2S-AD treatment landscape, this study assesses the M2S-AD burden in patients reaching referral centers in Greece. Methods: This was a multicenter, cross-sectional study. Patients aged 12 years or older with clinically diagnosed M2S-AD were enrolled. Data collected included clinical practice assessments and the following validated patient-reported instruments: Dermatology Life Quality Index (DLQI); EuroQol-5 Dimensions-3 Level scale (EQ-5D-3L); Patient Oriented Eczema Measure (POEM); Peak Pruritus Numerical Rating Scale (PP-NRS); and Work Productivity and Activity Impairment: General Health (WPAI:GH). A pain frequency/intensity/cause questionnaire and a sleep disturbance scale were also used. Results: Outcomes of 184 adults (51.1% female) with M2S-AD based on the Eczema Area and Severity Index (EASI) are presented (n = 117 moderate; n = 67 severe). Among the patients, 14.8% were obese, 59.2% had allergic comorbidities, and 88.0% were receiving AD-specific therapy (systemic: 38.6%). The median age, disease duration, body surface area, and total EASI scores were 38.8 years, 11.8 years, 30.0%, and 16.9, respectively. The median DLQI score was 12.0, with ‘symptoms/feelings’ being the most affected domain. EQ-5D dimensions ‘anxiety/depression’ and ‘pain/discomfort’ were also affected (65.2% and 64.1% reporting problems, respectively). The median POEM score was 17.0. Pain, severe pruritus (PP-NRS ≥ 7), and sleep disturbance were reported by 80.4%, 62.0%, and 88.5%, respectively. The median WPAI:GH ‘work productivity loss’ and ‘activity impairment’ scores were 23.8% and 30.0%, respectively. Conclusions: Both moderate and severe AD patients reaching Greek specialized centers experience significant symptom burden and impairments in quality of life, sleep, work, and daily activities. Full article

Climate change (CC) represents an increasing threat to mangroves worldwide and can amplify impacts caused by local anthropogenic activities. The direct effects of CC on mangrove forests have been extensively discussed, but indirect impacts such as the alteration of ecological processes driven by specific functional groups of the biota are poorly investigated. Ecological roles of key functional groups (FGs) in mangroves from the Atlantic–Caribbean–East Pacific (ACEP) and Indo-West Pacific (IWP) regions are reviewed, and impacts from CC mediated by these FGs are explored. Disruption by CC of ecological processes, driven by key FGs, can reinforce direct effects and amplify the loss of ecological functionality and further degradation of mangrove forests. Biogeochemistry mediator microbiotas of the soil, bioturbators, especially semiterrestrial crabs (Ocypodoids and Grapsoids) and herbivores (crustaceans and Insects), would be the most affected FG in both regions. Effects of climate change can vary regionally in the function of the combination of direct and indirect drivers, further eroding biodiversity and mangrove resilience, and impairing the predictability of ecosystem behaviour. This means that public policies to manage and conserve mangroves, as well as rehabilitation/restoration programs, should take into consideration the pressures of CC in specific regions and the response of key FGs to these pressures. Full article