Profile Method Research Articles

Targeted screening and profiling of massive components of colistimethate sodium by two-dimensional-liquid chromatography-mass spectrometry based on self-constructed compound database

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics. Similarities and variations of components present significant analytical challenges. A two-dimensional (2D) liquid chromatography-mass spectrometric (LC-MS) method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium (CMS). A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated. For efficient and high-accuracy screening of CMS, a targeted method based on a self-constructed high resolution mass spectrum database of CMS components was established. The database was built based on the commercial MassHunter Personal Compound Database and Library (PCDL) software and its accuracy of the compound matching result was verified with 6 known components before being applied to genuine sample screening. On this basis, the unknown peaks in the CMS chromatograms were deduced and assigned. The molecular formula, group composition and origins of a total of 99 compounds, of which the combined area percentage accounted for more than 95% of CMS components, were deduced by this 2D-LC-MS method combined with the MassHunter PCDL. This profiling method was highly efficient and could distinguish hundreds of components within 3 h, providing reliable results for quality control of this kind of complex drugs.

A process mining-based method for attacker profiling using the MITRE ATT&CK taxonomy

Cybersecurity intelligence involves gathering and analyzing data to understand cyber adversaries’ capabilities, intentions, and behaviors to establish adequate security measures. The MITRE ATT&CK framework is valuable for gaining insight into cyber threats since it details attacker tactics, techniques, and procedures. However, to fully understand an attacker’s behavior, it is necessary to connect individual tactics. In this context, Process Mining (PM) can be used to analyze runtime events from information systems, thereby discovering causal relations between those events. This article presents a novel approach combining Process Mining with the MITRE ATT&CK framework to discover process models of different attack strategies. Our approach involves mapping low-level system events to corresponding event labels from the MITRE ATT&CK taxonomy, increasing the abstraction level for attacker profiling. We demonstrate the effectiveness of our approach using real datasets of human and automated (malware) behavior. This exploration helps to develop more efficient and adaptable security strategies to combat current cyber threats and provides valuable guidelines for future research.

Electrochemical Label-free Methods for Ultrasensitive Multiplex Protein Profiling of Infectious Diseases.

Electrochemical detection methods are the more appropriate detection methods when it comes to the sensitive and specific determination of biomarkers. Biomarkers are the biological targets for disease diagnosis and monitoring. This review focuses on recent advances in label-free detection of biomarkers for infectious disease diagnosis. The current state of the art for rapid detection of infectious diseases and their clinical applications and challenges were discussed. Label-free electroanalytical methods are probably the most promising means to achieve this. We are currently in the early stages of the emerging technology of using label-free electrochemistry of proteins to develop biosensors. To date, antibody-based biosensors have been intensively developed, although many improvements in reproducibility and sensitivity are still needed. Moreover, there is no doubt that a growing number of aptamers and hopefully label-free biosensors based on nanomaterials will soon be used for disease diagnosis and therapy monitoring. And also here in this review article, we have discussed recent developments in the diagnosis of bacterial and viral infections, as well as the current status of the use of label-free electrochemical methods for monitoring inflammatory diseases.

A chemoenzymatic method for simultaneous profiling N- and O-glycans on glycoproteins using one-pot format

Glycosylation is generally characterized and controlled as a critical quality attribute for therapeutic glycoproteins because glycans can impact protein drug-product efficacy, half-life, stability, and safety. Analytical procedures to characterize N-glycans are relatively well established, but the characterization of O-glycans is challenging due to the complex workflows and lack of enzymatic tools. Here, we present a simplified chemoenzymatic method to simultaneously profile N- and O-glycans from the same sample using a one-pot format by mass spectrometry (MS). N-glycans were first released by PNGase F, followed by O-glycopeptide generation by proteinase K, selective N-glycan reduction, and O-glycan release by β-elimination during permethylation of both N- and O-glycans. Glycan structural assignments and determination of N- to O-glycan ratio was obtained from the one-pot mass spectra. The streamlined, one-pot method is a reliable approach that will facilitate advanced characterizations for quality assessments of therapeutic glycoproteins.

A Comparative Study of Highland Riparian Landscape Structure in Ubud, Indonesia and Banaue, Philippines

Abstract In Southeast Asia, Indonesia and the Philippines boast unique riparian areas crucial for ecological balance. These zones, nestled in mountainous terrains, act as vital links between land and water ecosystems, rich in biodiversity and cultural significance. However, they face threats from human development, causing fragmentation and altering their functions. To comprehend these changes, a study compared the landscape structure of two mountain villages in Ubud, Indonesia, and Banaue, Philippines. Using the landscape profile method, the study examined the relationship between landscape elements, highlighting Batad and Tegalalang’s distinct characteristics and challenges. While both areas featured forests, agriculture, and built-up areas, Batad exhibited less fragmentation. Terraced rice fields played critical roles in supporting water flow and biodiversity but faced risks from agrochemical use. Tegalalang faced environmental challenges like inadequate waste management and water scarcity, emphasizing the need for sustainable practices. The study’s adaptation of the landscape profile method provided valuable insights into landscape fragmentation, aiding in understanding and addressing ecological complexities in riparian zones. This research highlights the importance of preserving and managing riparian areas in mountainous regions to sustain their ecological functions amidst growing human impacts.

Single-Cell Profiling of Sarcomas from Archival Tissue Reveals Programs Associated with Resistance to Immune Checkpoint Blockade.

Sarcoma encompasses a diverse group of cancers that are typically resistant to current therapies, including immune checkpoint blockade (ICB), and underlying mechanisms are poorly understood. The contexture of sarcomas limits generation of high-quality data using cutting-edge molecular profiling methods, such as single-cell RNA-sequencing, thus hampering progress in understanding these understudied cancers. Here, we demonstrate feasibility of producing multimodal single-cell genomics and whole-genome sequencing data from frozen tissues, profiling 75,716 cell transcriptomes of five undifferentiated pleomorphic sarcoma and three intimal sarcoma samples, including paired specimens from two patients treated with ICB. We find that genomic diversity decreases in patients with response to ICB, and, in unbiased analyses, identify cancer cell programs associated with therapy resistance. Although interactions of tumor-infiltrating T lymphocytes within the tumor ecosystem increase in ICB responders, clonal expansion of CD8+ T cells alone was insufficient to predict drug responses. This study provides a framework for studying rare tumors and identifies salient and treatment-associated cancer cell intrinsic and tumor microenvironmental features in sarcomas.

The integration of dynamic value stream mapping and cost time profile method for optimizing offshore drilling logistic base operations

The research aims to analyze the integration of Dynamic Value Stream Mapping (DVMM) and Cost Time Profile (CT-profile) method for optimizing offshore drilling logistic base operations. The novelty of the research is the implementation of DVMM and CT-profile that implemented in monitoring system INTACTS (Integrated Dynamic value stream mapping and Cost time profile for shore base operation) which is directly connected to shore base material movement recording system. Each successful lift performed in JIT mode will be recorded and its characteristics studied so that it can be applied to other material lifting operations. This research uses data on the lifting operation on July - December 2020. The new method is applied in a logistic system for drilling activity. The research shows that DVSM is suitable to be applied for logistics in off shore base problems since the job and situation are very dynamics.

THE VIRTUAL POLE METHOD –AN ALTERNATIVE METHOD FOR PROFILING TOOLS WHICH GENERATE BY ENWRAPPING

In the paper is presented a method for profiling of tools that generate by enwrapping, by the rolling method, curls ordered by surfaces. By the new method is intended to eliminate one of the main disadvantages associated with the processing by generating of parts with radial symmetry, namely the difficulty related to the calculation of generating tool profile. The method allows eliminating the need to determine analytically the relative movement between the tool and the blank, which simplifies the calculation mode.

Predicting tactile sensory attributes of personal care emulsions based on instrumental characterizations: A review.

Emulsions in the form of creams, lotions, gels or foams are the most widely used personal care formulations to improve the condition and feel of the skin. Achieving an optimal balance between their performance, effectiveness and sensory profile is essential, with the sensory profile being a key factor in consumer satisfaction and the success of these products in the market. Well-established methods using highly trained and semi-trained panels (e.g. Spectrum descriptive analysis, Flash Profile method, Quantitative Descriptive Analysis method and 'Check-all-that-apply') are available and commonly used for the sensory assessment of personal care products. Nevertheless, a common drawback among all these methods is their inherent cost, both in terms of financial resources and time requirements. In recent years, research studies have emerged to address this limitation by investigating potential correlations between tactile sensory attributes and instrumental data associated with the physical characteristics of topical formulations. In other words, significant efforts have been invested in the development of robust instrumental methods specifically designed to accurately predict the sensory description that a panel of assessors could establish. These methods are not only faster, cheaper and more objective compared to traditional sensory testing, but they can also be applied to formulations that have not undergone extensive safety and toxicological testing. This review summarizes the most relevant findings, trends and current challenges in predicting tactile sensory attributes of personal care emulsions based on instrumental parameters.

Olfactory-chemical establishment using odour wheels and fingerprints to manage odor pollution for the petrochemical industry

The odor nuisance may cause major environmental issues, so identifying the odor characteristics is important for odor management and traceability in the petrochemical industry. In this study, odour wheels and fingerprints were applied to manage odor pollution in the petrochemical industry. First, the odor profile method and portable electronic nose evaluation were applied to analyze the flavour sensory profiles of five upstream and downstream petrochemical plants, in order to grasp the odor natures of plants. Second, 375 organized and unorganized samples of 5 plants were analyzed by gas chromatography-mass spectrometry (GC–MS) technology, and a total of 583 odorants were obtained, including sulfur compounds, alcohols, esters, aldehydes, ketones, acids, alkanes, alkenes, halogenated hydrocarbons, aromatic hydrocarbons, nitrogen compounds, and other compounds. Third, the key odorants were identified by gas chromatography-olfactory (GC-O) and odor activity value (OAV) analysis. Fourth, the fingerprint spectras were developed by the identification of key odorants and process sources through principal component analysis. For plant A, 21 odorants were confirmed, including naphthalene, 1-methylnaphthalene, 2-methylnaphthalene, 1-methylindene, and 2-methylindene. Methyl methacrylate, acetophenone, isobutene, 4-vinyl-1-cyclohexene, acrylonitrile, and styrene were key element for plant B. The fingerprint factor of plant C had 20 odorants, including methanol, butanol, 2-ethylhexanol, acetic acid, and ammonia. And there were 21 odorants for plant D and 14 odorants for plant E, respectively, with similar substance types, including 2-ethyl-2-hexenal, 3-methyl-4-heptanone, isobutyl butyrate, and 1,2,3,5-tetraethylbenzene. Finally, the odor wheels were established by the correlation analysis between odorants and malodor, and compounds in fingerprint spectra weaker related to malodor of plants were removed. Hence, the characteristic odorants of each plant were further clarified, and the odors were associated with compounds, achieving rapid diagnosis and traceability of odor pollution in the petrochemical park. This provided new ideas and technical methods for odor pollution monitoring and identification.

Next generation gravel road profiling – The potential of advanced UAV drone in comparison with road surface tester and rotary laser levels

Over the last decades, significant progress has been made and new approaches have been proposed for efficient collection of road condition data. Gravel roads are crucial for connecting urban and rural areas in Sweden, constituting a significant portion of the road network. Therefore, this study addresses the use of a developed Unmanned Aerial Vehicle (UAV)-based digital imaging system focusing on efficient collection of surface condition data over gravel roads.The study focuses on in-situ profile measurements of a gravel road located in Trosa, Sweden, using three different profiling methods: UAV drone with RTK technology, Road Surface Tester (RST), and Rotary Laser Level (RLL) to explore the agreement between these methods.The UAV drone, equipped with Real-Time Kinematic (RTK) technology, captures high-resolution images to produce detailed 3D surface models, overcoming the challenges posed by adverse weather conditions. Notable outcomes reveal RTK technology's stability, maintaining a steady 3D position accuracy below 2 cm. To enhance synchronization and comparison between different profiling methods, efforts should be made to standardize coordinate systems and measurement analysis software.Minimum average absolute differences of 1.1 cm, 1 cm, and 0.7 cm were recorded for all profiles (from 1 m left to 1 m right of the road centerline) in the comparisons between UAV drone – RST, UAV drone – RLL, and RST – RLL methods, respectively. This underlines the significant advancement in UAV drone technology, enabling remarkably accurate measurements of vertical offsets for profiling the tested gravel road despite the high altitude at which the UAV drone operates.

Small RNA-regulated expression of efflux pump affects tigecycline resistance and heteroresistance in clinical isolates of Klebsiella pneumoniae

Tigecycline and the newly Food and Drug Administration-approved tetracyclines, including eravacycline and omadacycline, are regarded as last-resort treatments for multidrug-resistant Enterobacterales. However, tigecycline resistance in Klebsiella pneumoniae has increased, especially the underlying mechanism of heteroresistance is unclear. This study aimed to elucidate the mechanisms underlying tigecycline resistance and heteroresistance in clinical K. pneumoniae isolates. A total of 153 clinical K. pneumoniae isolates were collected, and identified 15 tigecycline-resistant and three tigecycline-heteroresistant isolates using broth microdilution and population analysis profile methods, respectively. Total RNAs from K. pneumoniae ATCC13883 and the laboratory-induced tigecycline-resistant strain were extracted and sequenced on an Illumina platform. Differentially expressed genes and regulatory small RNAs (sRNAs) were analyzed and validated in clinical isolates of K. pneumoniae using quantitative real-time PCR. RNA sequencing results showed that mdtABC efflux pump genes were significantly upregulated in the tigecycline-resistant strains. Overexpression of mdtABC was observed in a clinical K. pneumoniae isolate, which increased tigecycline minimum inhibitory concentrations (MICs) and was involved in tigecycline heteroresistance. Sequencing analysis of sRNA demonstrated that candidate sRNA-120 directly interacted with the mdtABC operon and was downregulated in tigecycline-resistant strains. We generated an sRNA-120 deletion mutation strain and a complemented strain of K. pneumoniae. The sRNA-120 deletion strain displayed increased mRNA levels of mdtA, mdtB, and mdtC and an increase in MICs of tigecycline. The complemented strain of sRNA-120 restored the mRNA levels of these genes and the susceptibility to tigecycline. RNA antisense purification and parallel reaction monitoring mass spectrometry were performed to verify the interactions between sRNA-120 and mdtABC. Collectively, our study highlights that the post-transcriptional repression of mdtABC through sRNA-120 may provide an additional layer of efflux pump gene expression control, which is important for resistance and heteroresistance in clinical K. pneumoniae isolates.

Highly sensitive two-dimensional profiling of N-linked glycans by hydrophilic interaction liquid chromatography and dual stacking capillary gel electrophoresis

BackgroundN-Glycosylation is one of the most important post-translational modifications in proteins. As the N-glycan profiles in biological samples are diverse and change according to the pathological condition, various profiling methods have been developed, such as liquid chromatography (LC), capillary electrophoresis (CE), and mass spectrometry. However, conventional analytical methods have limitations in sensitivity and/or resolution, hindering the discovery of minor but specific N-glycans that are important both in the basic glycobiology research and in the medical application as biomarkers. Therefore, a highly sensitive and high-resolution N-glycan profiling method is required. ResultsIn this study, we developed a novel two-dimensional (2D) separation system, which couples hydrophilic interaction liquid chromatography (HILIC) with capillary gel electrophoresis (CGE) via large-volume dual preconcentration by isotachophoresis and stacking (LDIS). Owing to the efficient preconcentration efficiency of LDIS, limit of detection reached 12 pM (60 amol, S/N = 3) with good calibration curve linearity (R2 > 0.999) in the 2D analysis of maltoheptaose. Finally, 2D profiling of N-glycans obtained from standard glycoproteins and cell lysates were demonstrated. High-resolution 2D profiles were successfully obtained by data alignment using triple internal standards. N-glycans were well distributed on the HILIC/CGE 2D plane based on the glycan size, number of sialic acids, linkage type, and so on. As a result, specific minor glycans were successfully identified in HepG2 and HeLa cell lysates. Significance and noveltyIn conclusion, the HILIC/CGE 2D analysis method showed sufficient sensitivity and resolution for identifying minor but specific N-glycans from complicated cellular samples, indicating the potential as a next-generation N-glycomics tool. Our novel approach for coupling LC and CE can also dramatically improve the sensitivity in other separation modes, which can be a new standard of 2D bioanalysis applicable not only to glycans, but also to other diverse biomolecules such as metabolites, proteins, and nucleic acids.

Development of Sourdough Bread Made with Probiotic Lactiplantibacillus plantarum Bacteria Addition

Bread is a staple in the diet of people around the world. A new solution is the addition of selected strains of bacteria to the sourdough to increase the quality of the obtained bread. In the presented research, seven bread samples were baked and analysed, which differed by the selected strain of bacteria of the Lactiplantibacillus plantarum species used in sourdough preparation. The bread was subjected to a 3-day ageing test. The structure of the products was analysed using the texture profile analysis (TPA) method on days 1 and 3 of storage. It was observed that the samples with the addition of selected L. plantarum bacterial strains underwent the process of staling much slower than the control sample. The analysis of the viability of lactic acid bacteria (LAB) in products after 1 and 3 days of storage was also performed. The obtained results indicate the highest survival rate of LAB in the control sample, i.e., the native microflora of baker’s starters, which was at 3.07 log CFU after one-day storage after baking. In the case of other samples, the viability of the bacteria was below 2.74 log CFU, which confirms a certain degree of thermostability of selected bacterial strains. The belonging of the isolated bacteria to the species L. plantarum was proven via genetic identification using the PCR method. A sensory analysis using the quantitative descriptive profile (QDP) method was also performed on the bread immediately after it was baked and cooled down. The analysis showed that the use of L. plantarum strains as starters did not significantly affect the aromatic and taste profiles of the samples compared to the control sample. The overall quality of the bread samples was high, above 6 units, with the control sample having the highest sensory quality of 7.5 units (on a scale of 0–10 units). The presented research suggests that it is possible to produce bread with bacteria that have health-promoting properties and good sensory quality, which enhances the textural features of the final product. Future research will focus on attempting to microencapsulate selected thermostable probiotic bacteria.

Epidemiology of cryptococcal meningitis and fluconazole heteroresistance in Cryptococcus neoformans isolates from a teaching hospital in southwestern China.

Cryptococcal meningitis (CM), a common and serious opportunistic infection mostly caused by Cryptococcus neoformans, is primarily treated with fluconazole. Nevertheless, Cryptococcus neoformans strains that undergo repeated exposure to azoles can gradually acquire heteroresistance to fluconazole. The management of this specific CM infection poses a substantial challenge. Determining a globally accepted definition for fluconazole heteroresistance and developing effective and prompt methods for identifying heteroresistance is of utmost importance. We collected data on the clinical and epidemiological characteristics of patients diagnosed with CM. All the available Cryptococcus neoformans strains isolated from these patients were collected and subjected to antifungal susceptibility testing and evaluation of fluconazole heteroresistance. AIDS was present in 40.5% of the patients, whereas 24.1% did not have any underlying diseases. Patients with chronic diseases or impaired immune systems are susceptible to infection by Cryptococcus neoformans, a fungus that frequently (39.6%, 19/48) shows heteroresistance to fluconazole, as confirmed by population analysis profile (PAP).IMPORTANCEFluconazole heteroresistance poses a significant threat to the efficacy of fluconazole in treating cryptococcal meningitis (CM). Unfortunately, the standard broth microdilution method often misses the subtle percentages of subpopulations exhibiting heteroresistance. While the population analysis profile (PAP) method is esteemed as the gold standard, its time-consuming and labor-intensive nature makes it impractical for routine clinical use. In contrast, the Kirby-Bauer (KB) disk diffusion method offers a simple and effective screening solution. Our study highlights the value of KB over PAP and minimum inhibitory concentration (MIC) by demonstrating that when adjusting the inoculum concentration to 1.0 McFarland and subjecting samples to a 72-hour incubation period at 35°C, the KB method closely mirrors the outcomes of the PAP approach in detecting fluconazole heteroresistance. This optimization of the KB method not only enhances assay efficiency but also provides a blueprint for developing a timely and effective strategy for identifying heteroresistance.

Design and Experiment of Ordinary Tea Profiling Harvesting Device Based on Light Detection and Ranging Perception

Due to the complex shape of the tea tree canopy and the large undulation of a tea garden terrain, the quality of fresh tea leaves harvested by existing tea harvesting machines is poor. This study proposed a tea canopy surface profiling method based on 2D LiDAR perception and investigated the extraction and fitting methods of canopy point clouds. Meanwhile, a tea profiling harvester prototype was developed and field tests were conducted. The tea profiling harvesting device adopted a scheme of sectional arrangement of multiple groups of profiling tea harvesting units, and each unit sensed the height information of its own bottom canopy area through 2D LiDAR. A cross-platform communication network was established, enabling point cloud fitting of tea plant surfaces and accurate estimation of cutter profiling height through the RANSAC algorithm. Additionally, a sensing control system with multiple execution units was developed using rapid control prototype technology. The results of field tests showed that the bud leaf integrity rate was 84.64%, the impurity rate was 5.94%, the missing collection rate was 0.30%, and the missing harvesting rate was 0.68%. Furthermore, 89.57% of the harvested tea could be processed into commercial tea, with 88.34% consisting of young tea shoots with one bud and three leaves or fewer. All of these results demonstrated that the proposed device effectively meets the technical standards for machine-harvested tea and the requirements of standard tea processing techniques. Moreover, compared to other commercial tea harvesters, the proposed tea profiling harvesting device demonstrated improved performance in harvesting fresh tea leaves.

Enhancing Aerodynamic Performance of a Non-Axisymmetric Endwall Contoured Cascade Through Section Profiling Method

Abstract Endwall contouring and 3D blade configurations are effective techniques for enhancing turbomachinery performance. The integration of these technologies is an important area of investigation. To continue the numerical and experimental validations of the non-axisymmetric endwall contoured cascade (Du et al., 2024, “Endwall Contouring for Improving Aerodynamic Performance in a High-Pressure Turbine Cascade,” ASME J. Turbomach., 146(10), p. 101001), the present study redesigns the cascade via section profiling using optimization methods to maximize performance gains. To improve the control effect of endwall contouring, blade section parameters are strategically adjusted during optimization. The experimental flow field traverses at cascade exits demonstrate the control of the cascade flow field by the optimized design. The redesigned cascade exhibits decreased overturning near the shroud and reduced underturning near the hub, as well as reduced profile loss in the mainstream, compared to the endwall contoured cascade. The modification of section parameters enhances the control of losses and the secondary flow intensity. Computational fluid dynamics is used to provide a detailed analysis of the flow field, providing insights into how flow structures vary when the blade profile is modified. The numerical results further elucidate the effect of blade section profiling on both the performance characteristics of the cascade and the configuration of the secondary flows.

Rapid Microbial Profiling through Multimodal Biosensors for Transversal Analysis.

The intricate interactions between host and microbial communities hold significant implications for biology and medicine. However, traditional microbial profiling methods face limitations in processing time, measurement of absolute abundance, detection of low biomass, discrimination between live and dead cells, and functional analysis. This study introduces a rapid multimodal microbial characterization platform, Multimodal Biosensors for Transversal Analysis (MBioTA), for capturing the taxonomy, viability, and functional genes of the microbiota. The platform incorporates single cell biosensors, scalable microwell arrays, and automated image processing for rapid transversal analysis in as few as 2 h. The multimodal biosensors simultaneously characterize the taxon, viability, and functional gene expression of individual cells. By automating the image processing workflow, the single cell analysis techniques enable the quantification of bacteria with sensitivity down to 0.0075%, showcasing its capability in detecting low biomass samples. We illustrate the applicability of the MBioTA platform through the transversal analysis of the gut microbiota composition, viability, and functionality in a familial Alzheimer's disease mouse model. The effectiveness, rapid turnaround, and scalability of the MBioTA platform will facilitate its application from basic research to clinical diagnostics, potentially revolutionizing our understanding and management of diseases associated with microbe-host interactions.

Memory-bound k -mer selection for large and evolutionary diverse reference libraries.

Using k -mers to find sequence matches is increasingly used in many bioinformatic applications, including metagenomic sequence classification. The accuracy of these down-stream applications relies on the density of the reference databases, which, luckily, are rapidly growing. While the increased density provides hope for dramatic improvements in accuracy, scalability is a concern. Reference k -mers are kept in the memory during the query time, and saving all k -mers of these ever-expanding databases is fast becoming impractical. Several strategies for subsampling have been proposed, including minimizers and finding taxon-specific k -mers. However, we contend that these strategies are inadequate, especially when reference sets are taxonomically imbalanced, as are most microbial libraries. In this paper, we explore approaches for selecting a fixed-size subset of k -mers present in an ultra-large dataset to include in a library such that the classification of reads suffers the least. Our experiments demonstrate the limitations of existing approaches, especially for novel and poorly sampled groups. We propose a library construction algorithm called KRANK (K-mer RANKer) that combines several components, including a hierarchical selection strategy with adaptive size restrictions and an equitable coverage strategy. We implement KRANK in highly optimized code and combine it with the locality-sensitive-hashing classifier CONSULT-II to build a taxonomic classification and profiling method. On several benchmarks, KRANK k -mer selection dramatically reduces memory consumption with minimal loss in classification accuracy. We show in extensive analyses based on CAMI benchmarks that KRANK outperforms k -mer-based alternatives in terms of taxonomic profiling and comes close to the best marker-based methods in terms of accuracy.

Distinct profile of antiviral drugs effects in aortic and pulmonary endothelial cells revealed by high-content microscopy and cell painting assays

Antiretroviral therapy have significantly improved the treatment of viral infections and reduced the associated mortality and morbidity rates. However, highly effective antiretroviral therapy (HAART) may lead to an increased risk of cardiovascular diseases, which could be related to endothelial toxicity. Here, seven antiviral drugs (remdesivir, PF-00835231, ritonavir, lopinavir, efavirenz, zidovudine and abacavir) were characterized against aortic (HAEC) and pulmonary (hLMVEC) endothelial cells, using high-content microscopy.The colourimetric study (MTS test) revealed similar toxicity profiles of all antiviral drugs tested in the concentration range of 1 nM–50 μM in aortic and pulmonary endothelial cells. Conversely, the drugs' effects on morphological parameters were more pronounced in HAECs as compared with hLMVECs. Based on the antiviral drugs' effects on the cytoplasmic and nuclei architecture (analyzed by multiple pre-defined parameters including SER texture and STAR morphology), the studied compounds were classified into five distinct morphological subgroups, each linked to a specific cellular response profile. In relation to morphological subgroup classification, antiviral drugs induced a loss of mitochondrial membrane potential, elevated ROS, changed lipid droplets/lysosomal content, decreased von Willebrand factor expression and micronuclei formation or dysregulated cellular autophagy.In conclusion, based on specific changes in endothelial cytoplasm, nuclei and subcellular morphology, the distinct endothelial response was identified for remdesivir, ritonavir, lopinavir, efavirenz, zidovudine and abacavir treatments. The effects detected in aortic endothelial cells were not detected in pulmonary endothelial cells. Taken together, high-content microscopy has proven to be a robust and informative method for endothelial drug profiling that may prove useful in predicting the organ-specific endothelial toxicity of various drugs.