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Cytotoxicity evaluation and metabolomic profiling of Spheciospongia vagabunda-associated fungi corroborated by in silico studies
Abstract Cancer incidence continues to increase every year. Scientists strive to search for new anticancer compounds to combat this disease. Appealingly, marine environmental niches are still an untapped scaffold for natural products with chemical and biomedical diversity. Hence, fungi isolated from the Red Sea sponge Spheciospongia vagabunda were explored. Two strains were purified from the sponge and identified, depending on 18 S rRNA gene sequence, as Aspergillus sp. (UR1) and Penicillium sp. (UR2). The obtained fungal extracts were submitted to LC-HR-ESI-MS metabolomics evaluation, which showed notable variation in the chemical profiles of both extracts. The cytotoxic activity was assessed against three cancer cell lines: HepG2 (hepatocellular carcinoma human), MCF7 (breast cancer) and CaCo-2 (human colon carcinoma), via MTT assay. UR1 extract displayed higher antiproliferative activity with IC50 values 2.61 ± 0.12, 3.23 ± 0.21 and 3.41 ± 0.18 µg/ml against HepG2, CaCo-2 and MCF7, respectively. Whereas UR2 extract exhibited a less potent effect with IC50 values of 17.65 ± 0.28, 18.38 ± 0.19, and 22.45 ± 0.27 µg/ml. Additionally, molecular docking was conducted. Most identified compounds established strong binding affinity with the PPARG gene. Compounds 6 and 16 showed binding energy with S values − 9.13 and − 8.38 kcal/mol, respectively. The findings suggested the importance of Spheciospongia vagabunda-derived fungi in the production of cytotoxic natural compounds that could be used for cancer management.
A comparative analysis between NAT and chemiluminescence in detection of transfusion transmitted viruses in two main university blood transfusion centers
Abstract Nucleic acid amplification Testing (NAT) is expected to minimize the potential risk of transfusion transmitted infections (TTIs) which escaped the detection by serologic screening. Therefore, the aim was to assess the seroprevalence of TTIs (HCV, HBV and HIV) in voluntary blood donors and to verify the accuracy of chemiluminescence (CLIA) test versus NAT as confirmatory test for more safe blood donations in two main university (Mansoura and Assiut) blood transfusion centers in Egypt. A retrospective analysis was done for 87,620 specimens from healthy voluntary blood donors by NAT and CLIA techniques in Mansoura (12,464) and Assiut (75,156) blood transfusion centers. The prevalence of viral reactivity by CLIA was 2.49% (0.77%, 1.69% and 0.03% for HBV, HCV and HIV respectively) and by NAT was 2.25% (HBV 0.71%, HCV 1.52% and HIV 0.02%). The CLIA seroreactivity for HBV was found in 676 samples versus 621 by NAT (589 true positive, 87 false positive and 32 false negative). HCV reactivity was detected in 1477 by CLIA versus 1328 by NAT (1305 true positive, 172 false positive and 23 false negative). HIV results showed (CLIA/NAT) 22 versus 19 reactive samples (19 true positive, 3 false positive and 0.0 false negative). Comparison of CLIA and NAT results as regards the accuracy revealed 99.86% ,99.78%, and 100% for HBV, HCV, and HIV respectively. The CLIA and NAT techniques showed perfect agreement for detection of HCV (kappa = 0.929), HBV detection (kappa = 0.907) and HIV detection (kappa = 0.900). NAT implementation with CLIA increased blood transfusion safety with the advantage of direct sequence specific detection of virus genome. Therefore, it is a critical role to adopt NAT technology in all blood transfusion centers in Egypt.
Effective workflow from multimodal MRI data to model-based prediction
Abstract Predicting human behavior from neuroimaging data remains a complex challenge in neuroscience. To address this, we propose a systematic and multi-faceted framework that incorporates a model-based workflow using dynamical brain models. This approach utilizes multi-modal MRI data for brain modeling and applies the optimized modeling outcome to machine learning. We demonstrate the performance of such an approach through several examples such as sex classification and prediction of cognition or personality traits. We in particular show that incorporating the simulated data into machine learning can significantly improve the prediction performance compared to using empirical features alone. These results suggest considering the output of the dynamical brain models as an additional neuroimaging data modality that complements empirical data by capturing brain features that are difficult to measure directly. The discussed model-based workflow can offer a promising avenue for investigating and understanding inter-individual variability in brain-behavior relationships and enhancing prediction performance in neuroimaging research.
Forensic Stylistics: Exploring Style and Variations Across Different Writing Positions
Background: Handwriting is a complex task as it involves neuromuscular efforts. It is a written language through any mark, drawing, or symbol to convey a meaningful message. Hence, handwriting is a medium of communication, even a single stroke can be a whole message between the communicators. Handwriting is an acquired skill inÁuenced by many factors such as different bodypositions, different writing instruments, writing content, writing techniques (copy, dictated, or after recall), etc. Aim and Objective: This paper presents a study of the style markers and variation across the written sample, when writing is executed by a person in different body positions. Material: To achieve this study, 125 writing samples were collected from 25 participants aged 19-45 years. Each of the participants has written the sample in four different positions after lling out the basic questionnaire. The percentage istribution of variations in the handwriting characteristics and style markers associated with it was studied. Result: During the analysis, it has been observed that copying similar content in different body positions results in variations in the general characteristics of the person’s writing, including style pattern and which further draws into the range of variations in the handwriting characteristics and Individual’s stylistic pattern during different writing positions. Conclusion: This study will be helpful for forensic document examiners to lead to more accurate opinions. These observations might justify the examination of writings from different body positions as proof in a court of law when a similar condition of writing is in dispute.
Sinusoidal exponential distribution for modeling elevated creatinine kinase level as the initial presentation of Covid-19
Split spiral broadband double channel NMR detector facilitated by LTCC technology
Abstract In the field of nuclear magnetic resonance (NMR), planar spiral detector coils have been exploited for their ease of fabrication with a high tolerance for accommodating flat samples and for the ability to be integrated with microfluidic systems. Additionally, recent studies demonstrated the feasibility of designing such micro planar spirals for broadband operation 1,2 . Here we explore a novel embodiment of the planar spiral with a third contact added at an intermediary position of the spiral track, which thereby acts as a double-channel NMR detector. The spiral geometry was optimized through simulation so that the inner loop and the full loop correspond to two frequency bands of interest. With the combined microfluidic and NMR devices fabricated for the first time in low-temperature co-fired ceramic (LTCC) technology, we demonstrate untuned broadband operation by presenting 1D NMR spectra of 4 isotopes from 125 MHz to 500 MHz, as well as 2D $${^{1}\hbox {H}}-{^{13}\hbox {C}}$$ HSQC measurements. The design is easy to use and shows high robustness, demonstrating potential for NMR studies of flow systems with multiple nuclei.
Sulfur microenvironments as hotspots for biogenic pyrite formation
Abstract Pyrite (FeS2) is the end-product of bacterial sulfur cycling in reduced sedimentary environments. Sulfate-reducing bacteria (SRB) are mostly considered for biogenic pyrite formation due to their significant contribution to sulfide production at ambient temperatures. However, most experiments using SRB for biogenic pyrite formation resulted in the formation of only metastable iron sulfide minerals such as mackinawite (FeS). In this study, we investigated the roles of elemental sulfur (S0) and microbial sulfur reduction for pyrite formation. To this end, we cultivated the Fe(III)- and sulfur-reducing bacterium Geobacter sulfurreducens in the presence of the Fe(III) (oxyhydr)oxide mineral ferrihydrite and elemental sulfur at two different Fe/S ratios (4:1 and 1:4). While only mackinawite formed in Fe/S: 4:1 experiments, sulfidic conditions in the Fe/S: 1:4 experiments favored greigite (Fe3S4) and pyrite formation via the polysulfide pathway. Morphological observations demonstrated that spherulitic pyrite particles formed at the surface of elemental sulfur, with clusters forming that preserved the original morphology of sulfur particles. Our results showed that sulfur-reducing bacteria could replace the role of SRB as a sulfide source and further showed that sulfur particles are likely hotspots for biogenic pyrite formation by creating polysulfide-rich microenvironments and by acting as templates for spatially heterogeneous pyrite precipitation in nature.
Yttrium oxide nanoparticles induce selective cytotoxicity, genomic instability and ROS mitochondrial P53 mediated apoptosis in human pancreatic cancer cells
Abstract Pancreatic cancer is a hard-to-treat tumor with a poor prognosis. While traditional pancreatic cancer therapies can be effective, issues like cytotoxicity, low selectivity, and drug resistance still pose major challenges. Nanotechnology has shown promise in improving cancer diagnosis and treatment. Yttrium oxide nanoparticles (Y2O3-NPs), for example, have demonstrated potent selective cytotoxicity against triple negative breast cancer cells; but their effects on pancreatic cancer cells have not been explored. This study aimed to explore the impact of Y2O3-NPs on cell proliferation, DNA integrity, and oxidative stress in pancreatic cancer (PANC-1) and human skin fibroblast (HSF) cells. The cytotoxicity of Y2O3-NPs after 72 h were estimated using Sulforhodamine (SRB) cytotoxicity assay, while alkaline Comet assay was done to study genomic DNA integrity. Generation level of reactive oxygen species (ROS) and integrity of mitochondrial membrane potential were also analyzed. Apoptosis induction was investigated using Flow Cytometry and expression level of apoptotic (p53), anti-apoptotic (Bcl2) and mitochondrial (ND3) genes was measured using quantitative RTPCR. Our findings exhibited that Y2O3-NPs had strong selective cytotoxicity against PANC-1 cells with an IC50 value of 31.06 µg/ml, while having minimal effect on normal HSF cells (IC50 = 319.21 µg/ml). Treatment of PANC-1 cells with Y2O3-NPs at the IC50 concentration for 72 h significantly increased intracellular ROS levels and DNA damage, along with a notable reduction in mitochondrial membrane potential. Additionally, a significant rise in necrotic, early, and late apoptotic cells was observed, accompanied by downregulation of the anti-apoptotic Bcl2 gene and upregulation of the apoptotic p53 and mitochondrial ND3 genes. These findings highlight the selective toxicity of Y2O3-NPs towards cancerous PANC-1 cells, with minimal impact on normal cells. Y2O3-NPs appear to induce apoptosis in cancer cells by increasing ROS generation, damaging DNA, disrupting mitochondrial function, and triggering cell death. This study suggests that Y2O3-NPs may be a promising candidate for pancreatic cancer treatment. Further research is needed to fully explore their therapeutic potential.
How the brain separates real images from those it imagines
How axolotl cells ‘remember’ development to rebuild a lost limb
Under the microscope: DNA damage tracked through cell generations
Sequence diversity lost in early pregnancy
Lipid nanoparticle delivery of the CRISPR/Cas9 system directly into the mitochondria of cells carrying m.7778G>T mutation in MtDNA (mt-Atp8)
Selective inhibition of stromal mechanosensing suppresses cardiac fibrosis
Correction: Evaluating a novel reproduction number estimation method: a comparative analysis
Developing and comparing a new BMI inclusive energy expenditure algorithm on wrist-worn wearables
Abstract Estimating energy expenditure (EE) in real-world settings is crucial for studying human behavior and energy balance. Despite advances in wrist-worn inertial measurement units (IMU), actigraphy remains the most accepted measure for estimating EE, despite known Errors in accuracy, particularly in people with obesity. We developed an algorithm estimating EE from commercial smartwatch sensor data, and validated it against actigraphy-based energy estimates in people with obesity. In an in-lab study, 27 participants wore a Fossil Sport smartwatch and ActiGraph wGT3X+ while performing activities of varying intensities. Another 25 participants wore the smartwatch for 2 days in a free-living study. We built a machine learning model to estimate metabolic equivalent of task (MET) values/minute using smartwatch accelerometer and gyroscope data. Analysis included 2,189 minutes of in-lab and 14,045 minutes of free-living data. Compared to the metabolic cart, our model achieved lower root mean square error (0.28–0.32) across various sliding windows. In the free-living study, our algorithm’s estimates fell within $$\pm 1.96$$ SD of the best actigraphy-based estimates for 95.03% of minutes. Our proposed method accurately estimated METs compared to 11 algorithms primarily validated in non-obese populations, suggesting that commercial wrist-worn devices can provide more inclusive and reliable EE measures using our algorithm.