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Optimizing cryptographic protocols against side channel attacks using WGAN-GP and genetic algorithms
Longitudinal host transcriptional responses to SARS-CoV-2 infection in adults with extremely high viral load
Current understanding of viral dynamics of SARS-CoV-2 and host responses driving the pathogenic mechanisms in COVID-19 is rapidly evolving. Here, we conducted a longitudinal study to investigate gene expression patterns during acute SARS-CoV-2 illness. Cases included SARS-CoV-2 infected individuals with extremely high viral loads early in their illness, individuals having low SARS-CoV-2 viral loads early in their infection, and individuals testing negative for SARS-CoV-2. We could identify widespread transcriptional host responses to SARS-CoV-2 infection that were initially most strongly manifested in patients with extremely high initial viral loads, then attenuating within the patient over time as viral loads decreased. Genes correlated with SARS-CoV-2 viral load over time were similarly differentially expressed across independent datasets of SARS-CoV-2 infected lung and upper airway cells, from both in vitro systems and patient samples. We also generated expression data on the human nose organoid model during SARS-CoV-2 infection. The human nose organoid-generated host transcriptional response captured many aspects of responses observed in the above patient samples, while suggesting the existence of distinct host responses to SARS-CoV-2 depending on the cellular context, involving both epithelial and cellular immune responses. Our findings provide a catalog of SARS-CoV-2 host response genes changing over time and magnitude of these host responses were significantly correlated to viral load.
Heavy metals impact environmental capacity of oasis soils in Qinghai-Tibet Plateau dry zone
Optimization of surface roughness for titanium alloy based on multi-strategy fusion snake algorithm
Titanium alloy is known for its low thermal conductivity, small elastic modulus, and propensity for work hardening, posing challenges in predicting surface quality post high-speed milling. Since surface quality significantly influences wear resistance, fatigue strength, and corrosion resistance of parts, optimizing milling parameters becomes crucial for enhancing service performance. This paper proposes a milling parameter optimization method utilizing the snake algorithm with multi-strategy fusion to improve surface quality. The optimization objective is surface roughness. Initially, a prediction model for titanium alloy milling surface roughness is established using the response surface method to ensure continuous prediction. Subsequently, the snake algorithm with multi-strategy fusion is introduced. Population initialization employs an orthogonal matrix strategy, enhancing population diversity and distribution. A dynamic adaptive mechanism replaces the original static mechanism for optimizing food quantity and temperature, accelerating convergence. Joint reverse strategy aids in selecting and generating individuals with higher fitness, fortifying the algorithm against local optima. Experimental results across five benchmarks employing various optimization algorithms demonstrate the superiority of the MSSO algorithm in convergence speed and accuracy. Finally, the multi-strategy snake algorithm optimizes the objective equation, with milling parameter experiments revealing a 55.7 percent increase in surface roughness of Ti64 compared to pre-optimization levels. This highlights the effectiveness of the proposed method in enhancing surface quality.
Identification of a metabolic brain network characterizing essential tremor
Abstract The neuronal correlate of tremor genesis and cognitive function in essential tremor (ET) and its modulation by deep brain stimulation (DBS) are poorly understood. To explore the underlying metabolic topography of motor and cognitive symptoms, sixteen ET patients (age 63.6 ± 49.1 years) and 18 healthy controls (HC) (61.1 ± 6.3 years) underwent tremor and cognitive assessments and18F-fluorodeoxyglucose PET of the brain. Multivariate spatial covariance analysis was applied for identifying ET related metabolic brain networks. For network validation and to explore DBS effects, 8 additional ET patients (68.1 ± 8.2 years) treated with DBS were assessed in both the ON and OFF state, respectively. The ET related metabolic spatial covariance pattern (ETRP) was characterized by relatively increased metabolism in the cerebellum, brainstem, and temporo-occipital cortices, accompanied by relative metabolic decreases mainly in fronto-temporal and motor cortices. Network expression showed inverse correlations with tremor severity and disease duration and positive correlations with cognitive dysfunction. DBS substantially alleviated tremor, but had only marginal effects on cognitive performance. There were no significant DBS effects on ETRP expression at the group level, but all but one subject showed higher scores in the ON state. Our findings suggest ET is characterized by an abnormal brain network associated with disease phenotype.
Discovery of a potential open ocean nursery for the endangered shortfin mako shark in a global fishing hotspot
Populations of large pelagic sharks are declining worldwide due to overfishing. Determining the overlap between shark populations and fishing activities is important to inform conservation measures. However, for many threatened sharks the whereabouts of particularly vulnerable life-history stages – such as pregnant females and juveniles – are poorly known. Here, we investigated the spatial distribution of size classes, energy transfer and reproductive states of pregnant females of the endangered shortfin mako, Isurus oxyrinchus, using spatially resolved catch data from a Spanish surface longline vessel (1996 − 2009) in the South-east Pacific Ocean. Our results suggest a general eastward gradient of occurrence of pregnant females of thousands of kilometers from western oceanic feeding grounds towards the eastern Pacific, where we observed an aggregation area of small juveniles. Moreover, the potential nursery likely overlapped a longline fishing hotspot, increasing the vulnerability of juveniles from fisheries. Our results suggest that limiting fishing pressure in this area could reduce mortality of early life stages and contribute to the conservation of this endangered shark species.
Author Correction: Exploring northeast India’s culturable soil Actinomycetia for potent antibacterial agents against gram-positive bacterial pathogens of clinical importance
Human embryo editing against disease is unsafe and unproven — despite rosy predictions
Loss of Kat2b impairs intraflagellar transport and the Hedgehog signaling pathway in primary cilia
Advanced KNN-based cost-efficient algorithm for precision localization and energy optimization in dynamic underwater sensor networks
Knowledge, attitudes, and use of the Mediterranean diet in practice among dietitians in the United Arab Emirates: a cross-sectional study
Mapping neutron biological effectiveness for DNA damage induction as a function of incident energy and depth in a human sized phantom
Comparative analysis of deep learning models for crack detection in buildings
Sulfide-rich continental roots at cratonic margins formed by carbonated melts
Effects of nitrogen fertilizer application rate on lodging resistance for rice (Oryza sativa L.) stem
In-silico screening and analysis of missense SNPs in human CYP3A4/5 affecting drug-enzyme interactions of FDA-approved COVID-19 antiviral drugs
Abstract Single nucleotide polymorphisms (SNPs) represent the prevailing form of genetic variations observed in the human population. Such variations could alter the encoded enzymes’ activities. CYP3A4/5 enzymes are involved in metabolizing drugs, notably antivirals against SARS-CoV-2. In this work, we computationally investigated antiviral-enzyme interactions of CYP3A4/5 genetic variants. We also examined the deleterious impact of 751 missense single nucleotide polymorphisms (SNPs) within the CYP3A4/5 genes. An ensemble of bioinformatics tools, [SIFT, PolyPhen-2, cadd, revel, metaLr, mutation assessor, Panther, SNP&GO, PhD-SNP, SNAP, Meta-SNP, FATHMM, I-Mutant, MuPro, INPS, CONSURF, GPS 5.0, MusiteDeep and NetPhos], identified a total of 94 variants (47 SNPs in CYP3A4, 47 SNPs in CYP3A5) to potentially impact the structural integrity as well as the activity of the CYP3A4/5 enzymes. Molecular docking was done to recognize the structural stability and binding properties of the CYP3A4/5 protein isoforms with 3 FDA-approved antiviral drugs. Our findings indicated that the CYP3A4 gene variants; R418T, I335T and R130P and the CYP3A5 gene variants; I335T, L133P and R130Q are considered the most deleterious missense SNPs. These mutants potentially affect drug-enzyme binding and hence may alter therapeutic response. Cataloguing deleterious SNPs is essential for personalized gene-based pharmacotherapy.
3D modelling and simulation of thermal effects and dispersion of particles carrying infectious respiratory agents in a railway transport coach
Synthesis and evaluation of amino acid ionic liquid for enhanced oil recovery: experimental and modeling simulation studies
Abstract Recovering the remaining oil after primary and secondary extraction methods poses a significant challenge. Enhanced oil recovery (EOR) techniques, which involve injecting fluids into reservoirs, aim to increase recovery rates. Ionic liquids, known for their adaptability, are emerging as promising agents in EOR, improving oil displacement by reshaping fluid properties and interacting with reservoir rocks. This study investigates the eco-friendly amino acid ionic liquid, AAIL [G0.5 C12][Pro], for EOR applications, focusing on its characterization and performance. Using pre-prepared quaternary ammonium salt PAMAM G0.5 C12 and proline, AAIL [G0.5 C12][Pro] was synthesized and confirmed via FTIR and 1H-NMR analyses. Rheological analysis identified 7 g of AAIL [G0.5 C12][Pro] as the optimal concentration for peak performance. Laboratory sand-pack displacement experiments demonstrated an 11% increase in oil recovery at this concentration. Further, a 3D reservoir model simulation validated the enhanced oil recovery potential of AAIL [G0.5 C12][Pro]. The study introduces the novel amino acid ionic liquid [G0.5 C12][Pro], which demonstrates superior effectiveness in enhancing oil recovery through significant wettability modification and interfacial tension reduction, underscoring its potential as an effective and environmentally friendly EOR agent compared to other ionic liquids and conventional methods.