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This study investigates the efficacy of predicting age-related macular degeneration (AMD) activity through deep neural networks (DNN) using a cross-instrument training dataset composed of Optical coherence tomography-angiography (OCTA) images from two different manufacturers. A retrospective cross-sectional study analyzed 2D vascular en-face OCTA images from Heidelberg Spectralis (1478 samples: 1102 training, 276 validation, 100 testing) and Optovue Solix (1003 samples: 754 training, 189 validation, 60 testing). OCTA scans were labeled based on clinical diagnoses and adjacent B-scan OCT fluid information, categorizing activity into normal, dry AMD, active wet AMD, and wet AMD in remission. Experiments explored cross-instrument disease classification using separate and combined datasets for training the DNN. Testing involved 100 Heidelberg and 60 Optovue samples. Training on Heidelberg data alone yielded 73% accuracy on Heidelberg images and 60% on Optovue images. Training on Optovue data alone resulted in 34% accuracy on Heidelberg and 85% on Optovue images. Combined training data from both instruments achieved 78% accuracy on Heidelberg and 76% on Optovue test sets. Results indicate that cross-instrument classifier training demonstrates high classification prediction accuracy, making cross-instrument training viable for future clinical applications. This implies that vascular morphology in OCTA can predict disease progression.

Abstract With regard to underground hydrogen storage projects, presuming that the hydrogen storage site has served as a repository for methane, the coexistence of a blend of methane and hydrogen is anticipated during the incipient stage of hydrogen storage. Therefore, the solubility of hydrogen/methane mixtures in brine becomes imperative. On the contrary, laboratory tasks of such measurements are hard because of its extreme corrosion ability and flammability, hence modeling methodologies are highly preferred. Therefore, in this study, we seek to create accurate data-driven intelligent models based upon laboratory data using hybrid models of adaptive neuro-fuzzy inference system (ANFIS) and least squares support vector machine (LSSVM) optimized with either particle swarm optimization (PSO), genetic algorithm (GA) and coupled simulated annealing (CSA) to predict hydrogen/methane mixture solubility in brine as a function of pressure, temperature, hydrogen mole fraction in hydrogen/methane mixture and brine salt concentration. The results indicate that almost all the gathered experimental data are technically suitable for the model development. The sensitivity study shows that pressure and hydrogen mole fraction in the mixture are strongly related with the solubility data with direct and indirect effects, respectively. The analyses of evaluation indexes and graphical methods indicates that the developed LSSVM-GA and LSSVM-CSA models are the most accurate as they exhibit the lowest AARE% and MSE values and the highest R-squared values. These findings show that machine learning methods could be a useful tool for predicting hydrogen solubility in brine encountered in underground hydrogen storage projects, aiding in the advancement of intelligent, affordable, and secure hydrogen storage technologies.

Abstract Early recognition of risk factors for prolonged mechanical ventilation (PMV) could allow for early clinical interventions, prevention of secondary complications such as nosocomial infections, and effective triage of hospital resources. This study tested the hypothesis that an ensemble machine learning (ML) analysis of clinical data at time of intubation could identify patients at risk of PMV, using a COVID-19 dataset to classify patients into PMV (> 14 days) and non-PMV (≤ 14 days) groups. While several factors are known to cause PMV, including acid-base, weakness, and delirium, lesser-utilized but routinely measured parameters such as platelet count, glucose levels and fevers may also be relevant. Patient data from a single University Hospital were analyzed via the ML workflow to predict patients at risk of PMV and identify key clinical markers. Model performance was evaluated on a chronologically distinct cohort. The ML workflow identified patients at risk of PMV with AUROCTRAIN=0.960 (F1TRAIN = 0.935) and AUROCTEST=0.804 (F1TEST = 0.800). Top key features for classification included glucose, platelet count, temperature, LVEF, bicarbonate (arterial blood gas), and BMI. Data analysis at intubation time via the proposed workflow offers the potential to accurately predict patients at risk of PMV, with the goal to improve patient management and triage of hospital resources.

Abstract A novel and environmentally friendly route was developed for production of sustainable flame retardant, antibacterial and UV protective nanoparticles for polymeric films nanocomposites. For the first time, dried molokhia leaves were engineered into spherical nanoparticles with an average size of 8.5 nm via an eco-friendly, one-pot solid-state ball-milling method. The engineered nanoparticles were proved using spectroscopic and microscopic techniques. The sustainable nanoparticles were employed as an efficient and green flame retardant, antibacterial and UV protective materials for polyvinyl alcohol (PVA) nanocomposite films. The distinct compatibility between PVA chains and spherical nanoparticles afford excellent homogeneous dispersion of each nanoparticle in the polymer matrix. Compared to blank PVA film which burned at a rate of 125 mm/min, the novel nanoparticles achieved significant flame retardancy for polymer nanocomposites films recording zero rate of burning. Their outstanding charring ability and naturally doped elemental composition were attributed to their higher flame retardancy achieved. Moreover, the newly developed multifunctional nanoparticles integrated outstanding UV protection feature to developed polymer nanocomposite films recording UV protection factor superiority of more than 900% compared to nanoparticle free film. Noteworthy to note that, the nanoparticles afford excellent inhibition to bacterial growth against Escherichia coli and Staphylococcus aureus over the surface of developed polymer nanocomposite films achieving clear inhibition zone of 9 and 7.6 mm compared to zero mm for pristine polymer film, respectively. In addition, a proposed and clarified flame retardancy mechanism was presented. Additionally, an assessment was conducted regarding the economic feasibility of producing sustainable multifunctional nanoparticles on an industrial scale.

Abstract Telomerase enzyme prevents telomere shortening during division, having human telomerase reverse transcriptase (hTERT) as its catalytic subunit. Favipiravir (FAV), an RNA-dependent RNA polymerases inhibitor, shared structural similarity with hTERT and thus assumed to have cytotoxic effect on cancer cells, in addition to its prophylactic effect to immunocompromised cancer patients. Nanoemulsion (NE) is a potential tumor cells targeting delivery system, thereby enhancing therapeutic efficacy at the intended site, mitigating systemic toxicity, and overcoming multidrug resistance. The objective of this study is to develop a green FAV nanoemulsion (FNE) that is environmentally friendly and safe for patients, while aiming to enhance its cytotoxic effects. The study also highlights the environmental sustainability of the developed RP-HPLC method and assesses its greenness impact. The FNE formulation underwent thermodynamic stability testing and invitro characterization. Greenness was assessed using advanced selected tools like the Analytical Eco-Scale (AES), Analytical Greenness Metric for Sample Preparation (AGREEprep), and green analytical procedure index (GAPI). The cytotoxic potential of FNE was screened against MCF-7 breast cancer and Vero normal cell lines using SRB assay. Stable and ecofriendly FNE was formulated having a particle size (PS) of 25.29 ± 0.57 nm and a zeta potential of -6.79 ± 5.52 mV. The cytotoxic effect of FNE on MCF-7 cells was more potent than FAV with lower IC50 while FNE showed non-toxic effect on VERO normal cell line. Therefore, the FAV nanoemulsion formulation showed targeted cytotoxicity on MCF-7 cells while being non-toxic on normal Vero cells.

Abstract Numerous Deep Learning (DL) scenarios have been developed for evolving new healthcare systems that leverage large datasets, distributed computing, and the Internet of Things (IoT). However, the data used in these scenarios tend to be noisy, necessitating the incorporation of robust pre-processing techniques, including data cleaning, preparation, normalization, and addressing imbalances. These steps are crucial for generating a robust dataset for training. Designing frameworks capable of handling such data without compromising efficiency is essential to ensuring robustness. This research aims to propose a novel healthcare framework that selects the best features and enhances performance. This robust deep learning framework, called (R-DLH2O), is designed for forecasting cardiovascular crises. Unlike existing methods, R-DLH2O integrates five distinct phases: robust pre-processing, feature selection, feed-forward neural network, prediction, and performance evaluation. This multi-phase approach ensures superior accuracy and efficiency in crisis prediction, offering a significant advancement in healthcare analytics. H2O is utilized in the R-DLH2O framework for processing big data. The main improvement of this paper lies in the unique form of the Whale Optimization Algorithm (WOA), specifically the Modified WOA (MWOA). The Gaussian distribution approach for random walks was employed with the diffusion strategy to choose the optimal MWOA solution during the growth phase. To validate the R-DLH2O framework, six performance tests were conducted. Surprisingly, the MWOA-2 outperformed other heuristic algorithms in speed, despite exhibiting lower accuracy and scalability. The suggested MWOA was further analyzed using benchmark functions from CEC2005, demonstrating its advantages in accuracy and robustness over WOA. These findings highlight that the framework’s processing time is 436 s, mean per-class error is 0.150125, accuracy 95.93%, precision 92.57%, and recall 93.6% across all datasets. These findings highlight the framework’s potential to produce significant and robust results, outperforming previous frameworks concerning time and accuracy.

Abstract Complement-dependent cytotoxicity (CDC) is a primary mechanism-of-action of monoclonal antibody (mAb) immunotherapies used to treat haematological cancers, including rituximab and daratumumab. However, mAb efficacy may be limited by reduced bioavailability of complement C1q – which activates the complement classical pathway following interactions with mAb-opsonised target cells. C1q is secreted by phagocytes upon recruitment to sites of muscle damage to facilitate muscular repair, hence we hypothesised that muscle damaging exercise may increase C1q ‘spill-over’ into blood. Additionally, other complement proteins (e.g., C1s) have been reported to increase following ultra-endurance and resistance exercise. Taken together, we hypothesised that muscle damaging exercise could be harnessed to enhance mAb-mediated CDC. In this study, n = 8 healthy males (28 ± 5-years) completed two 45-minute treadmill running protocols: (1) a flat running protocol at a speed 15% above anaerobic threshold, and (2) a downhill running protocol (− 10% slope) at the same speed. Blood samples were collected before, immediately after, and 1-hour, 24-hours, 2-days, and 4-days after exercise. Isolated serum was assessed for C1q by ELISA, and used to measure mAb (rituximab, daratumumab) mediated CDC against two haematological cancer cell lines (Raji, RPMI-8226) in vitro. Isolated plasma was assessed for markers of inflammation (C-reactive protein [CRP]), and muscle damage (creatine kinase [CK]) by turbidimetry. C1q and CDC activity were not different between running protocols and did not change over time (p > 0.05). Significantly greater perceived muscle soreness (p

Abstract The aim of the present work was to immobilize L-arginine deiminase on suitable supports such as chitosan, alginate, and silica gel to study its stability. Additionally, the study aims to investigate the anticancer effects of the free purified enzyme on hepatocellular carcinoma (Hep-G2) and breast cancer (MCF-7) cell lines. L-arginine deiminase (ADI: EC 3.5.3.6) was immobilized on chitosan, Ca-alginate, and silica gel, with immobilization efficiencies of 89.0%, 72.8%, and 66.5%, respectively. The optimal immobilization time for the highest efficiency was 4 h. Increasing the concentration of glutaraldehyde improved the immobilization efficiency of ADI on chitosan. The chitosan-immobilized ADI retained about 45% of its activity after 8 cycles. The optimal pH values were 6 for the free purified ADI and 7 for the chitosan-immobilized ADI. The optimal temperature increased from 40 °C for the free enzyme to 45 °C after immobilization. The activation energies for the free and chitosan-immobilized enzymes were 71.335 kJ/mol and 64.011 kJ/mol, respectively. The Km values for the free and chitosan-immobilized ADI were 0.76 mM and 0.77 mM, respectively, while the Vmax values were 80.0 U/mg protein for the free ADI and 71.4 U/mg protein for the chitosan-immobilized ADI. After 30 days of storage at 4 °C, the residual activities were 40% for the free purified ADI and 84% for the chitosan-immobilized ADI. At 25 °C, the residual activities were 10% for the free ADI and 75% for the chitosan-immobilized ADI. The chitosan-immobilized ADI exhibited significantly higher stability against proteases such as pepsin and trypsin compared to the free enzyme. The purified ADI also demonstrated enhanced potential anticancer effects and significant cytotoxicity against the Hep-G2 and MCF-7 tumor cell lines compared to doxorubicin. These findings suggest that purified ADI has potential as an anticancer agent, though further in-depth studies are required.

Abstract This study investigates the efficacy of predicting age-related macular degeneration (AMD) activity through deep neural networks (DNN) using a cross-instrument training dataset composed of Optical coherence tomography-angiography (OCTA) images from two different manufacturers. A retrospective cross-sectional study analyzed 2D vascular en-face OCTA images from Heidelberg Spectralis (1478 samples: 1102 training, 276 validation, 100 testing) and Optovue Solix (1003 samples: 754 training, 189 validation, 60 testing). OCTA scans were labeled based on clinical diagnoses and adjacent B-scan OCT fluid information, categorizing activity into normal, dry AMD, active wet AMD, and wet AMD in remission. Experiments explored cross-instrument disease classification using separate and combined datasets for training the DNN. Testing involved 100 Heidelberg and 60 Optovue samples. Training on Heidelberg data alone yielded 73% accuracy on Heidelberg images and 60% on Optovue images. Training on Optovue data alone resulted in 34% accuracy on Heidelberg and 85% on Optovue images. Combined training data from both instruments achieved 78% accuracy on Heidelberg and 76% on Optovue test sets. Results indicate that cross-instrument classifier training demonstrates high classification prediction accuracy, making cross-instrument training viable for future clinical applications. This implies that vascular morphology in OCTA can predict disease progression.

Abstract Transfusion dependent β-thalassemia is a genetic blood disorder characterized by chronic anaemia. Blood transfusion is lifesaving but comes at a cost. Iron overload emerges as a prime culprit as a free radicals damage endothelial cells. Chronic anaemia further disrupts oxygen delivery, exacerbating the oxidative stress. Increased levels of met-haemoglobin and malondialdehyde compromise endothelial function. This research sheds light on the impact of met-haemoglobin and oxidative stress on endothelial function in 50 patients with transfusion dependent β-thalassemia major compared to 50 healthy individuals as control. Blood samples were collected & subjected to CBC, biochemical analysis including creatinine, ferritin, CRP, LDH, and HCV antibodies. Oxidative stress was assessed using met-haemoglobin & malondialdehyde. Endothelial dysfunction was evaluated by endothelial activation and stress index (EASIX). EASIX, met-haemoglobin and malondialdehyde were significantly increased in patients (1.44 ± 0.75, 2.07 ± 0.2, 4.8 ± 0.63; respectively) compared to the control (0.52 ± 0.24,0.88 ± 0.34,0.8 ± 0.34; respectively). Significant strong positive correlation was found between EASIX and met-haemoglobin, malondialdehyde, serum ferritin and CRP (P = 0.00, r = 0.904, P = 0.00, r = 0.948, P = 0.00, r = 0.772, P = 0.00, r = 0.971; respectively. Met-haemoglobin as well as EASIX should be routinely estimated to assess endothelial function especially before the decision of splenectomy. Antioxidant drugs should be supplemented.

Abstract Staphylococcus aureus (S. aureus), particularly Methicillin-resistant S. aureus (MRSA), poses a significant global public health threat, necessitating advanced methodologies to enhance our understanding of this organism at the omics levels. This study introduces a refined protocol for constructing and curing high-density transposon mutant (tn-mutant) libraries in S. aureus, addressing the challenges associated with low transductant yields, and the complex genetic manipulation mechanism in Gram-positive bacteria. Our methodology employs a Himar1 transposon based on a two-plasmid system, leveraging Himar1’s high insertional efficiency in AT-rich organisms. Enhanced transduction efficiency was achieved through chloramphenicol pre-treatment and the use of modified enriched media. Complementing this, an optimized plasmid curing procedure ensured a representative and stable tn-mutant library. The protocol was successfully applied to multiple S. aureus strains, demonstrating an increase in mutant recovery and reduced post-curing impact. The method offers a robust approach for Transposon Insertion Sequencing (TIS) applications in S. aureus, enabling deeper insights into survival, resistance, and pathogenicity mechanisms. This protocol holds a significant potential for accelerating the construction of tn-mutant libraries in various S. aureus strains.

Abstract Boswellia carterii (BC) resins plants have a long historical background as a treatment for inflammation, as indicated by information originating from multiple countries. Twenty-seven diterpenoids have been identified in ethyl acetate and total methanol BC, comprising seventeen boscartins of the cembrane-type diterpenoids and ten boscartols of the prenylaromadendrane-type diterpenoids. Moreover, twenty-one known triterpenoids have also been found, encompassing nine tirucallane-type, six ursane-type, four oleanane-type, and two lupane-type. The cembrane-type diterpenoids hold a significant position in pharmaceutical chemistry and related industries due to their captivating biological characteristics and promising pharmacological potentials. Extraction of BC, creation and assessment of nano sponges loaded with either B. carterii plant extract or DEX, are the subjects of our current investigation. With the use of ultrasound-assisted synthesis, nano sponges were produced. The entrapment efficiency (EE%) of medications in nano sponges was examined using spectrophotometry. Nano sponges were characterized using a number of methods. Within nano sponges, the EE% of medicines varied between 98.52 ± 0.07 and 99.64 ± 1.40%. The nano sponges' particle sizes varied from 105.9 ± 15.9 to 166.8 ± 26.3 nm. Drugs released from nano sponges using the Korsmeyer-Peppas concept. In respiratory distressed rats, the effects of BC plant extract, DEX salt and their nano formulations (D1, D5, P1 and P1), were tested. Treatment significantly reduced ICAM-1, LTB4, and ILβ 4 levels and improved histopathologic profiles, when compared to the positive control group. Boswellia extract and its nano sponge formulation P1 showed promising therapeutic effects. The effect of P1 may be due to synergism between both the extract and the formulation. This effect was achieved by blocking both ICAM-1 and LTB4 pathways, therefore counteracting the effects of talc powder.

Abstract The BCG vaccine is given to millions of children globally but efficacy wanes over time and differences in the immune systems between infants and adults can influence vaccine efficacy. To this end, 34 rhesus macaques were vaccinated with BCG within seven days of birth and blood samples were collected over 88 weeks for quantification of blood cell populations. Overall, the composition of cell populations did not change significantly between BCG vaccinated and unvaccinated groups, and that BCG vaccination did not perturb normal development. In comparison to adult macaques, higher numbers of CD4+ T-cells, Tregs and NK cells were measured in the infant age group, suggesting a potential bias towards immunosuppressive and innate immune populations. Antigen-specific IFNγ secreting cell frequencies in infant BCG vaccinated animals were detectable in peripheral blood samples for 36 weeks after vaccination but declined following this. To evaluate the long-term impact of infant BCG vaccination on subsequent revaccination with BCG, a pilot study of three adult macaques received an aerosol BCG revaccination approximately 3 years after their initial BCG vaccination as infants. This induced an increase in PPD-specific IFNγ secreting cells, and increased secretion of the cytokines IFNγ and IL-1β, following stimulation with other microorganisms, which are signals associated with trained innate immunity.

Mosquito-borne disease remains a significant burden on global health. In the United States, the major threat posed by mosquitoes is transmission of arboviruses, including West Nile virus by mosquitoes of the Culex genus. Virus metagenomic analysis of mosquito small RNA using deep sequencing and advanced bioinformatic tools enables the rapid detection of viruses and other infecting organisms, both pathogenic and non-pathogenic to humans, without any precedent knowledge. In this study, we sequenced small RNA samples from over 60 pools of Culex mosquitoes from two major areas of Southern California from 2017 to 2019 to elucidate the virome and immune responses of Culex. Our results demonstrated that small RNAs not only allowed the detection of viruses but also revealed distinct patterns of viral infection based on location, Culex species, and time. We also identified miRNAs that are most likely involved in Culex immune responses to viruses and Wolbachia bacteria, and show the utility of using small RNA to detect antiviral immune pathways including piRNAs against some pathogens. Collectively, these findings show that deep sequencing of small RNA can be used for virus discovery and surveillance. One could also conceive that such work could be accomplished in various locations across the world and over time to better understand patterns of mosquito infection and immune response to many vector-borne diseases in field samples.

Abstract The aim of the study was to assess healthy tissue metabolism (HTM) using 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) during chemotherapy in Hodgkin lymphoma (HL) and the association of HTM with baseline metabolic tumour volume (MTV), haematological parameters, adverse events (AEs), early response and progression-free survival (PFS). We retrospectively identified 200 patients with advanced HL from the RATHL trial with [18F]FDG-PET/CT before (PET0) and following 2 cycles of chemotherapy (PET2). [18F]FDG-uptake was measured in bone marrow (BM), spleen, liver and mediastinal blood pool (MBP). Deauville score (DS) 1–3 was used to classify responders and DS 4–5, non-responders. [18F]FDG-uptake decreased significantly in BM and spleen and increased in liver and MBP at PET2 (all p

Abstract Hydatidosis causes a serious health hazard to humans and animals leading to significant economic and veterinary and public health concern worldwide. The present study aimed to evaluate the in vitro and ex vivo protoscolicidal effects of synthesized poly(amidoamine), PAMAM, nanoemulsion. In this study, PAMAM was characterized through dynamic light scattering technique to investigate the particle size and zeta potential of nanoemulsified polymer. For the in vitro and ex vivo assays, we used eosin dye exclusion test and scanning electron microscope (SEM) to evaluate the effects of the prepared and characterized PAMAM nanoemulsion against protoscoleces from Echinococcus granulosus sensu lato G6 (GenBank: OQ443068.1) isolated from livers of naturally infected camels. Various concentrations (0.5, 1, 1.5 and 2 mg/mL) of PAMAM nanoemulsion at different exposure times (5, 10, 20 and 30 min) were tested against protoscolices. Our findings showed that PAMAM nanoemulsion had considerable concentration- and time-dependent protoscolicidal effect at both in vitro and ex vivo experiments. Regarding in vitro assay, PAMAM nanoemulsion had a potent protoscolicidal effect when compared with the control group with a highest protoscolicidal activity observed at the concentration of 2 mg/mL at all exposure times, such that 100% of protoscolices were killed after 20 min of exposure. Also, the mortality of protoscolices was 100% after 30 min of exposure to 1 and 1.5 mg/mL of PAMAM nanoemulsion, in vitro. Concerning ex vivo assay PAMAM nanoemulsion recorded the highest mortality rates at the concentration of 2 mg/mL (55, 99.4 and 100% at 10, 20, 30 min, respectively). Ultrastructure examination of examined protoscolices after 20 min of exposure to PAMAM nanoemulsion showed a complete loss of rostellar hooks, disruption of suckers with disorganization of hooks with partial or complete loss of them, and damage of protoscolices tegument with loss of their integrity in the form of holes and contraction of the soma region were observed in 1.5 and 2 mg/mL of PAMAM, in vitro and ex vivo, showing more damage in the in vitro conditions. It can be concluded that PAMAM nanoemulsion is a promising protoscolicidal agent offering a high protoscolicidal effect at a short exposure time. Further in vivo studies and preclinical animal trials are required to evaluate its efficacy and clinical applications against hydatid cysts.

Abstract The rail industry in Australia screens workers for probable obstructive sleep apnea (OSA) due to known safety risks. However, existing criteria to trigger screening only identify a small proportion of workers with OSA. The current study sought to examine the relationship between OSA risk and rail incidents in real-world data from Australian train drivers, and conducted a proof of concept analysis to determine whether more conservative screening criteria are justified. Health assessment (2016–2018) and subsequent rail incident data (2016–2020) were collected from two passenger rail service providers. Predictors included OSA status (confirmed no OSA with a sleep study, controlled OSA, unknown OSA [no recorded sleep assessment data] and confirmed OSA with no indication of treatment); OSA risk according to the current Standard, and OSA risk according to more conservative clinical markers (BMI threshold and cardiometabolic burden). Coded rail safety incidents involving the train driver were included. Data were analysed using zero-inflated negative binomial models to account for over-dispersion with high 0 counts, and rail safety incidents are reported using Incidence Risk Ratios (IRRs). A total of 751 train drivers, typically middle-aged, overweight to obese and mostly men, were included in analyses. There were 43 (5.7%) drivers with confirmed OSA, 62 (8.2%) with controlled OSA, 13 (1.7%) with confirmed no OSA and 633 (84.4%) drivers with unknown OSA. Of the 633 train drivers with unknown OSA status, 21 (3.3%) met ‘at risk’ criteria for OSA according to the Standard, and incidents were 61% greater (IRR: 1.61, 95% Confidence Interval (CI) 1.02–2.56) in the years following their health assessment compared to drivers who did not meet ‘at risk’ criteria. A more conservative OSA risk status using lower BMI threshold and cardiometabolic burden identified an additional 30 ‘at risk’ train drivers who had 46% greater incidents compared to drivers who did not meet risk criteria (IRR (95% CI) 1.46 (1.00–2.13)). Our more conservative OSA risk criteria identified more workers, with greater prospective incidents. These findings suggest that existing validated tools could be considered in future iterations of the Standard in order to more sensitively screen for OSA.

Abstract Redox is a unique, programmable modality capable of bridging communication between biology and electronics. Previous studies have shown that the E. coli redox-responsive OxyRS regulon can be re-wired to accept electrochemically generated hydrogen peroxide (H2O2) as an inducer of gene expression. Here we report that the redox-active phenolic plant signaling molecule acetosyringone (AS) can also induce gene expression from the OxyRS regulon. AS must be oxidized, however, as the reduced state present under normal conditions cannot induce gene expression. Thus, AS serves as a “pro-signaling molecule” that can be activated by its oxidation—in our case by application of oxidizing potential to an electrode. We show that the OxyRS regulon is not induced electrochemically if the imposed electrode potential is in the mid-physiological range. Electronically sliding the applied potential to either oxidative or reductive extremes induces this regulon but through different mechanisms: reduction of O2 to form H2O2 or oxidation of AS. Fundamentally, this work reinforces the emerging concept that redox signaling depends more on molecular activities than molecular structure. From an applications perspective, the creation of an electronically programmed “pro-signal” dramatically expands the toolbox for electronic control of biological responses in microbes, including in complex environments, cell-based materials, and biomanufacturing.

Abstract In urban areas, diverse and complex habitats for biodiversity are often lacking. This lack of diversity not only compromises essential ecological processes, such as pollination and nutrient cycling, but also diminishes the resilience of urban ecosystems to pests and diseases. To enhance urban biodiversity, a possible solution is to integrate shrubs alongside trees, thereby increasing the overall amount of vegetation, structural complexity and the associated resource diversity. Here, using a common garden experiment involving a variety of trees and shrubs planted alone and in combination, we evaluate how canopy-associated invertebrate assemblages are influenced by vegetation type. In particular, we test whether the presence of shrubs, alone or with trees, results in increased abundance and taxonomic richness of invertebrates, compared to trees on their own. We found that the overall abundance of invertebrates, and that of specific functional groups (e.g., herbivores, pollinators, detritivores), was higher on shrubs, compared to trees, and when trees and shrubs were planted in combination (relative to trees on their own). Our results suggest that planting shrub and tree species with wide and dense crowns can increase the associated abundance and taxonomic and functional group richness of invertebrate communities. Overall, our findings indicate that urban planning would benefit from incorporating shrubs alongside urban trees to maximise invertebrate abundance, diversity and function in urban landscapes.

This study aimed to understand the profile of hydroxychloroquine-treated patients, referral patterns, and dosing and to assess the adherence of eye care providers to the latest 2016 screening guidelines provided by the American Academy of Ophthalmology. Patients were identified using electronic health records (EHR) taking hydroxychloroquine and were seen by optometrists, retinal specialists, and non-retinal ophthalmologists. Review of EHR data includes demographic characteristics, indications, and dosing profile of hydroxychloroquine use, eye care provider managing the patient, and imaging modalities performed. A total of 166 patients were included in the study. The most common indications for screening were systemic lupus erythematosus and discoid lupus (52.4%) followed by rheumatoid arthritis (18.7%) and Sjögren's syndrome (9.6%). Ninety-two (55.4%) patients were on a higher-than-recommended dose of > 5 mg/kg/day. Patients who weighed less (mean 63.9 kg) were taking a higher-than-recommended dose (vs. 81.5 kg, p

Representations of the changing global carbon cycle under climatic and environmental perturbations require highly detailed accounting of all atmosphere and biosphere exchange. These fluxes remain unsatisfactory, as a consequence of only having data with limited spatiotemporal coverage and precision, which restrict accurate assessments. Through the nature of intimate coupling of global carbon and oxygen cycles via O2 and CO2 and their unique triple oxygen isotope compositions in the biosphere and atmosphere, greater insight is available. We report analysis of their isotopic compositions with the widest geographical and temporal coverage (123 new measurements for CO2) and constrain, on an annual basis, the global CO2 recycling time (1.5 ± 0.2 year) and gross primary productivities of terrestrial (~ 170-200 PgC/year) and oceanic (~ 90-120 PgC/year) biospheres. Observed inter-annual variations in CO2 triple oxygen isotopic compositions were observed at a magnitude close to the largest contrast set by the terrestrial and oceanic biospheres. The seasonal cycles between the east and west Pacific Ocean were found to be drastically different. This intra-annual variability implies that the entire atmospheric CO2 turnover time is not much longer than the tropospheric mixing time (less than ~ 5 months), verifying the derived recycling time. The new measurements, analyses, and incorporation of other global data sets allow development of an independent approach, providing a strong constraint to biogeochemical models.

This cross-sectional study aimed to investigate the hypothesis that permanent capillary damage may underlie the long-term COVID-19 sequela by quantifying the retinal vessel integrity. Participants were divided into three subgroups; Normal controls who had not been affected by COVID-19, mild COVID-19 cases who received out-patient care, and severe COVID-19 cases requiring intensive care unit (ICU) admission and respiratory support. Patients with systemic conditions that may affect the retinal vasculature before the diagnosis of COVID-19 infection were excluded. Participants underwent comprehensive ophthalmologic examination and retinal imaging obtained from Spectral-Domain Optical Coherence Tomography (SD-OCT), and vessel density using OCT Angiography. Sixty-one eyes from 31 individuals were studied. Retinal volume was significantly decreased in the outer 3 mm of the macula in the severe COVID-19 group (p = 0.02). Total retinal vessel density was significantly lower in the severe COVID-19 group compared to the normal and mild COVID-19 groups (p = 0.004 and 0.0057, respectively). The intermediate and deep capillary plexuses in the severe COVID-19 group were significantly lower compared to other groups (p

Abstract Acne vulgaris is one of the most common skin diseases worldwide and causes great distress to patients. In addition, most acne patients suffer from low self-esteem and social withdrawal. This study aimed to assess the prevalence of acne and its impact on quality of life among medical students. It also evaluates the patterns of self-treatment use. The study population consisted of all medical students from An-Najah National University (ANU) and the hospital. The questionnaire consists of three parts, and the first part consists of questions regarding demographic information. The second part consisted of questions to measure the severity of acne using the acne severity scale as well as the Cardiff Disability Index, which assesses the quality of life concerning acne in medical students. Finally, the third part consisted of questions exploring and assessing acne self-treatment. The mean age of our study sample was 21.3 ± 1.9 years, with a female predominance of 72.3%. The prevalence of acne among medical students was 80.9%, and 36.6% practiced self-medication. Acne was strongly associated with female sex (p

Abstract Nowadays, breast cancer is considered one of the most upsetting malignancies among females. Encapsulation of celecoxib (CXB) and prodigiosin (PDG) into zein/sodium caseinate nanoparticles (NPs) produce homogenous and spherical nanoparticles with good encapsulation efficiencies (EE %) and bioavailability. In vitro cytotoxicity study conducted on human breast cancer MDA-MB-231 cell lines revealed that there was a significant decline in the IC50 for encapsulated drugs when compared to each drug alone or their free combination. In addition, results demonstrated that there is a synergism between CXB and PDG as their combination indices were 0.62251 and 0.15493, respectively. Moreover, results of scratch wound healing assay revealed enhanced antimigratory effect of free drugs and fabricated NPs in comparison to untreated cells. Furthermore, In vitro results manifested that formulated nanoparticles exhibited induction of apoptosis associated with reduced angiogenesis, proliferation, and inflammation. In conclusion, nanoencapsulation of multiple drugs into nanoparticles might be a promising approach to develop new therapies for the managing of triple negative breast cancer.

Abstract The production of oil palm (Elaeis guineensis) in Southeast Asia is vital to the economies of Indonesia and Malaysia. Both fertilisers and pesticides used in palm production can contain elevated concentrations of Trace Elements (TEs) which may accumulate in soils and leaf tissues of plants. We hypothesised that leaves from oil palms may be deficient in essential elements, while containing elevated concentrations of non-essential TEs commonly found in agrichemicals. Samples of plant materials (leaves and fruitlets) were collected from active and former plantations in Sumatra, Indonesia, and analysed for essential and non-essential elements. Indonesian palm oil samples were sourced in New Zealand and their elemental concentrations determined. Leaf materials from both active and abandoned production sites were deficient in N, K, S and Mo, while leaf materials from abandoned sites were deficient in P. These deficiencies may have been a contributing factor to the abandonment of production at these sites. Concentrations of non-essential elements were below or comparable to average plant concentrations and no evidence of contamination was found in plant tissues. Palm oil contained low concentrations of TEs, which did not pose any toxicity risks. However, Na and Al were present in concentrations of 1198 and 159 mg kg−1 respectively, which were higher than have been previously reported. Tropical oil palm production could benefit from the determination of bioaccumulation factors for fertiliser contaminants in E. guineensis, to limit the transfer of contaminants to plants and products if increased fertiliser applications were used to correct nutrient deficiencies.

Abstract Tamoxifen (TAM) is one of the most successful treatments for breast cancer; however, TAM resistance continues to be a significant barrier. TAM resistance has been reported to be associated with increased expression of human telomerase reverse transcriptase (hTERT). This enzyme shares structural similarity with RNA-dependent RNA polymerase (RdRp) enzyme of RNA viruses, suggesting that RdRp inhibitors may also inhibit hTERT. Favipiravir (FAV) is an antiviral drug that inhibits RdRp of RNA viruses. Thus, we propose that FAV may also elicit an antitumor effect by suppressing hTERT. This study aimed to investigate the effect of FAV and TAM on TAM-resistant breast cancer (TAMR-1). The cell viabilities were determined. The levels of CDK1/ hTERT, in addition to regulators of hTERT-targeted signaling pathways were measured. Apoptosis, migration, and cell cycle distribution were also determined. Our data revealed that the combination of TAM and FAV suppressed cell proliferation synergistically (CI

Abstract Traditional methods for assessing plant health often lack the necessary attributes for continuous and non-destructive monitoring. In this pilot study, we present a novel technique utilizing a customized fiber optic probe based on attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) with a contact force control unit for non-invasive and continuous plant health monitoring. We also developed a normalized difference mid-infrared reflectance index through statistical analysis of spectral features, enabling differentiation of drought and age conditions in plants. Our research aims to characterize phytochemicals and plant endogenous status optically, addressing the need for improved analytical measurement methods for in situ plant health assessment. The probe configuration was optimized with a triple-loop tip and a 3 N contact force, allowing sensitive measurements while minimizing leaf damage. By combining polycrystalline and chalcogenide fiber probes, a comprehensive wavenumber range analysis (4000–900 cm−1) was achieved. Results revealed significant variations in phytochemical composition among plant species, for example, red spinach with the highest polyphenolic content and green kale with the highest lignin content. Petioles displayed higher lignin and cellulose absorbance values compared to veins. The technique effectively monitored drought stress on potted green bok choy plants in situ, facilitating the quantification of changes in water content, antioxidant activity, lignin, and cellulose levels. This research represents the first demonstration of the potential of fiber optic ATR-FTIR probes for non-invasive and rapid plant health measurements, providing insights into plant health and advancements in quantitative monitoring for indoor farming practices, bioanalytical chemistry, and environmental sciences.

Abstract Artesunate is a derivative of artemisinin, an active compound isolated from Artemisia annua which has been used in Traditional Chinese Medicine and to treat malaria worldwide. Artemisinin derivatives have exhibited anti-cancer activity against both solid tumors and leukemia. The direct target(s) of artesunate are controversial; although, heme-bound proteins in the mitochondria have been implicated. We utilized computational modeling to calculate the predicted binding score of artesunate with heme-bound mitochondrial proteins and identified cytochrome c as potential artesunate target. UV–visible spectroscopy showed changes in the absorbance spectrum, and thus protein structure, when cytochrome c was incubated with artesunate. Artesunate induces apoptosis, disrupts mitochondrial membrane potential, and is antagonized by methazolamide in pediatric AML cells indicating a probable mechanism of action involving cytochrome c. We utilized a multi-disciplinary approach to show that artesunate can interact with and is dependent on cytochrome c release to induce cell death in pediatric AML cell lines.

Abstract Human milk feeding can support premature infants to thrive. Yet those with premature infants can be challenged in human milk production. Considering this, and the use of potentially harmful human milk enhancers, the present study was conducted with the aim of determining the effect of orally consumed Lactuca sativa (L. sativa) syrup (lettuce extract) on human milk volume and subsequent weight gain in the preterm infant. Extracts from lettuce and other plants such as silymarin are already evidenced to be safe for use during lactation and have other therapeutic effects in humans. Yet this is the first study of its kind. This parallel randomized clinical trial included lactating participants with their preterm infants who were born at

Abstract There has been no previous systematic, epidemiological study of the reproductive risk factors for uterine fibroids (UF) in African populations despite African women having the highest burden of UF in the world. Improved knowledge of the associations between UF and reproductive factors would contribute to better understanding of the etiology of UF and may suggest novel opportunities for prevention and therapeutic interventions. We used nurse administered questionnaires to survey the demographic and reproductive risk factors of UF among 484 women who are members of the African Collaborative Center for Microbiome and Genomics Research (ACCME) Study Cohort in central Nigeria, and who had transvaginal ultrasound diagnosis (TVUS). We used logistic regression models to the evaluate associations between reproductive risk factors and UF, adjusted for significant covariates. In our multivariable logistic regression models, we found inverse associations with number of children (OR = 0.83, 95%CI = 0.74–0.93, p-value = 0.002), parity (OR = 0.41, 95%CI = 0.24–0.73, p-value = 0.002), history of any type of abortion (OR = 0.53, 95%CI = 0.35–0.82, p-value = 0.004), duration of use of Depot Medroxyprogesterone Acetate (DMPA) (p-value for trend = 0.02), menopausal status (OR = 0.48, 95%CI = 0.27–0.84, p-value = 0.01), and a non-linear positive association with age (OR = 1.04, 95%CI = 1.01–1.07, p-value = 0.003). Other reproductive risk factors that have been reported in other populations (age at menarche and menopause, and oral contraceptives) were not associated with UF in this study. Our study confirms some of the reproductive risk factors for UF that have been found in other populations and shows that some of them are stronger in the Nigerian population. The associations we found with DMPA suggest opportunities for further research to understand the mechanisms of action of progesterone and its analogues in the etiology of UF, their potential use for prevention and treatment of UF.

Abstract The utilization of mechanical ventilation is of utmost importance in the management of individuals afflicted with severe pulmonary conditions. During periods of a pandemic, it becomes imperative to build ventilators that possess the capability to autonomously adapt parameters over the course of treatment. In order to fulfil this requirement, a research investigation was undertaken with the aim of forecasting the magnitude of pressure applied on the patient by the ventilator. The aforementioned forecast was derived from a comprehensive analysis of many variables, including the ventilator's characteristics and the patient's medical state. This analysis was conducted utilizing a sophisticated computational model referred to as Long Short-Term Memory (LSTM). To enhance the predictive accuracy of the LSTM model, the researchers utilized the Chimp Optimization method (ChoA) method. The integration of LSTM and ChoA led to the development of the LSTM-ChoA model, which successfully tackled the issue of hyperparameter selection for the LSTM model. The experimental results revealed that the LSTM-ChoA model exhibited superior performance compared to alternative optimization algorithms, namely whale grey wolf optimizer (GWO), optimization algorithm (WOA), and particle swarm optimization (PSO). Additionally, the LSTM-ChoA model outperformed regression models, including K-nearest neighbor (KNN) Regressor, Random and Forest (RF) Regressor, and Support Vector Machine (SVM) Regressor, in accurately predicting ventilator pressure. The findings indicate that the suggested predictive model, LSTM-ChoA, demonstrates a reduced mean square error (MSE) value. Specifically, when comparing ChoA with GWO, the MSE fell by around 14.8%. Furthermore, when comparing ChoA with PSO and WOA, the MSE decreased by approximately 60%. Additionally, the analysis of variance (ANOVA) findings revealed that the p-value for the LSTM-ChoA model was 0.000, which is less than the predetermined significance level of 0.05. This indicates that the results of the LSTM-ChoA model are statistically significant.