Standard Methods Research Articles

Phytochemical and Nutritional Profile of Ficus Capensis Stem Collected from Agbani, Enugu, South East Nigeria

Ficus capensis commonly called bush fig tree belongs to the family Moraceae and have been used for different medicinal purposes. This study aimed at determining the Proximate, Phytochemical, Vitamin and Mineral Compositions of Ficus capensis stem. The analyses were done using standard biochemical methods. The results of Proximate composition showed that the stem contained moisture (21.94 ± 0.10 %), Crude Fat (2.45 ± 0.21 %), Crude protein (15.24 ± 0.05%), Crude Fiber (32.55 ± 0.06 %), Carbohydrate (18.79 ± 0.34 %) and Ash (9.04 ± 0.12 %). The Total energy value was 158 KCal/100g. The phytochemical analysis revealed the presence of Tannin (1.32 ± 0.01 mg/g), Alkaloid (0.55 ± 0.00 mg/g), Saponin (2.17 ± 0.00 mg/g), Glycoside (1.13 ± 0.00 mg/g), Terpenoids (0.10 ± 0.00 mg/g), Flavonoids (2.42 ± 0.02 mg/g), Steroids (0.54 ± 0.00 mg/) and Phenol (0.97 ± 0.00 mg/g). The result also revealed that the stem contained vitamins A (0.57 ± 0.02 mg/g), β-carotene (1.27 ± 0.02 mg/g), B1 (0.89 ± 0.02 mg/g), B2 (1.14 ± 0.01 mg/g), B3 (0.96 ± 0.01 mg/g), B6 (0.85 ± 0.01 mg/g) and B9 (1.28 ± 0.04 mg/g), C (0.81 ± 0.01 mg/g), D (0.26 ± 0.01 mg/g), E (0.85 ± 0.02 mg/g) and K (1.10 ± 0.02 mg/g). The Mineral composition include Calcium (34.01 mg/kg), Phosphorus (0.57 mg/kg), Chloride (2.56 mg/kg), Potassium (21.40 mg/kg), Sulphur (0.26 mg/kg), Iron (0.89 mg/kg), Manganese (0.07 mg/kg), Copper (0.28 mg/kg), Zinc (0.07 mg/kg), Cobalt (0.02 mg/kg) and Selenium (0.52 mg/kg). These results have shown that stem of Ficus capensis is a potential source of nutrients and bioactive compounds which are found useful in nutrition and therapy.

Reporting of somatic variants in clinical cancer care: recommendations of the Swiss Society of Molecular Pathology.

Somatic variant testing through next-generation sequencing (NGS) is well integrated into Swiss molecular pathology laboratories and has become a standard diagnostic method for numerous indications in cancer patient care. Currently, there is a wide variation in reporting practices within our country, and as patients move between different hospitals, it is increasingly necessary to standardize NGS reports to ease their reinterpretation. Additionally, as many different stakeholders-oncologists, hematologists, geneticists, pathologists, and patients-have access to the NGS report, it needs to contain comprehensive and detailed information in order to answer the questions of experts and avoid misinterpretation by non-experts. In 2017, the Swiss Institute of Bioinformatics conducted a survey to assess the differences in NGS reporting practices across ten pathology institutes in Switzerland. The survey examined 68 reporting items and identified 48 discrepancies. Based on these findings, the Swiss Society of Molecular Pathology initiated a Delphi method to reach a consensus on a set of recommendations for NGS reporting. Reports should include clinical information about the patient and the diagnosis, technical details about the sample and the test performed, and a list of all clinically relevant variants and variants of uncertain significance. In the absence of a consensus on an actionability scheme, the five-class pathogenicity scheme proposed by the ACMG/AMP guideline must be included in the reports. The Swiss Society of Molecular Pathology recognizes the importance of including clinical actionability in the report and calls on the European community of molecular pathologists and oncologists to reach a consensus on this issue.

The postbiotic potential of Aspergillus oryzae - a narrative review.

The filamentous fungus Aspergillus oryzae has a long tradition in East Asian food processing. It is therefore not surprising that in recent years fermentation products of A. oryzae have attracted attention in the emerging field of postbiotics. This review aims to provide a comprehensive summary of the potential postbiotic effects of fermentation products from A. oryzae, by discussing possible mechanisms of action against the background of the molecular composition determined so far. In particular, cell wall constituents, enzymes, extracellular polymeric substances, and various metabolites found in A. oryzae fermentation preparations are described in detail. With reference to the generally assumed key targets of postbiotics, their putative beneficial bioactivities in modulating the microbiota, improving epithelial barrier function, influencing immune responses, metabolic reactions and signaling through the nervous system are assessed. Drawing on existing literature and case studies, we highlight A. oryzae as a promising source of postbiotics, particularly in the context of animal health and nutrition. Challenges and opportunities in quality control are also addressed, with a focus on the necessity for standardized methods to fully harness the potential of fungal-based postbiotics. Overall, this article sheds light on the emerging field of A. oryzae-derived postbiotics and emphasizes the need for further research to fully realize their therapeutic potential.

The effect of reference material crystallinity on absolute quantitative phase analysis using the internal standard method

Equations are given which allow an analyst to obtain a correct absolute quantitative phase analysis via the internal standard method when a reference material with a known crystallinity of less than 100% is used. Comparisons are made with previous equations, and a numerical example is given.

Multimass Analysis of Adeno-Associated Virus Vectors by Orbitrap-Based Charge Detection Mass Spectrometry.

Adeno-associated virus (AAV) vectors have attracted significant attention as the main platform for gene therapy. To ensure the safety and efficacy of AAV vectors when used as gene therapy drugs, it is essential to assess their critical quality attributes (CQAs). These CQAs include the genome packaging status, the size of the genome encapsidated within the AAV capsid, and the stoichiometry of viral proteins (VPs) that constitute the AAV capsids. Analytical methods have been established for evaluating CQAs, such as analytical ultracentrifugation, capillary gel electrophoresis with laser-induced fluorescence detection, and capillary gel electrophoresis using sodium dodecyl sulfate with UV detection. Here, we present a multimass analysis of AAV vectors using orbitrap-based charge detection mass spectrometry (CDMS), a single-ion mass spectrometry. Orbitrap-based CDMS facilitates the quantitative evaluation of the genome packaging status based on the mass distribution of empty and full particles. Additionally, we established a novel method to analyze the encapsidated genome directly without pretreatment, such as protein digestion or heat treatment, and to estimate the stoichiometric variation of VP for the capsid based on the mass distribution constituted by the single peak corresponding to AAV particles. Orbitrap-based CDMS is a distinctive method that allows multiple mass characterizations of AAV vectors with a small sample volume of 20 μL for 1013 cp/mL in a short time (30 min), and it holds the potential to become a new standard method in the assessment of CQAs for AAV vectors.

Neural Vector Fields for Implicit Surface Representation and Inference

AbstractNeural implicit fields have recently shown increasing success in representing, learning and analysis of 3D shapes. Signed distance fields and occupancy fields are still the preferred choice of implicit representations with well-studied properties, despite their restriction to closed surfaces. With neural networks, unsigned distance fields as well as several other variations and training principles have been proposed with the goal to represent all classes of shapes. In this paper, we develop a novel and yet a fundamental representation considering unit vectors in 3D space and call it Vector Field (VF). At each point in $$\mathbb {R}^3$$ R 3 , VF is directed to the closest point on the surface. We theoretically demonstrate that VF can be easily transformed to surface density by computing the flux density. Unlike other standard representations, VF directly encodes an important physical property of the surface, its normal. We further show the advantages of VF representation, in learning open, closed, or multi-layered surfaces. We show that, thanks to the continuity property of the neural optimization with VF, a separate distance field becomes unnecessary for extracting surfaces from the implicit field via Marching Cubes. We compare our method on several datasets including ShapeNet where the proposed new neural implicit field shows superior accuracy in representing any type of shape, outperforming other standard methods. Codes are available at https://github.com/edomel/ImplicitVF.

Evolution of Reactive Organic Compounds and Their Potential Health Risk in Wildfire Smoke.

Wildfires are an increasing source of emissions into the air, with health effects modulated by the abundance and toxicity of individual species. In this work, we estimate reactive organic compounds (ROC) in western U.S. wildland forest fire smoke using a combination of observations from the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign and predictions from the Community Multiscale Air Quality (CMAQ) model. Standard emission inventory methods capture 40-45% of the estimated ROC mass emitted, with estimates of primary organic aerosol particularly low (5-8×). Downwind, gas-phase species abundances in molar units reflect the production of fragmentation products such as formaldehyde and methanol. Mass-based units emphasize larger compounds, which tend to be unidentified at an individual species level, are less volatile, and are typically not measured in the gas phase. Fire emissions are estimated to total 1250 ± 60 g·C of ROC per kg·C of CO, implying as much carbon is emitted as ROC as is emitted as CO. Particulate ROC has the potential to dominate the cancer and noncancer risk of long-term exposure to inhaled smoke, and better constraining these estimates will require information on the toxicity of particulate ROC from forest fires.

The effect of drugs and guns on life expectancy in the United States, 2000–2020

ObjectivesThis study estimated the effect of changing trends in drug- and firearm-related mortality on life expectancy in the U.S. over the last two decades. Study designRetrospective cross-sectional study. MethodsWe used national vital registration data from CDC WONDER, stratified by sex, to estimate the mortality rate due to accidental and intentional poisoning (ICD Codes X40-X49, X60-X69, Y10-Y19 and X85), and firearm deaths (ICD codes W32-W34, X72-X74, X93-X95, Y22-Y24) for the period 2000–2020. We applied standard life table methods to all cause mortality rates with and without these mortality causes to estimate the life expectancy at each age over this period. ResultsIn 2020, mortality due to drugs and firearms combined reduced male life expectancy by1.67 years compared to 0.67 years in 2000, and without the effect of these two causes of death, male life expectancy in 2019 would have been 78.02 years. For women, drugs and firearm-related mortality reduced life expectancy by 0.20 years in 2000 and 0.63 years in 2020, and female life expectancy would have been 82.25 years in 2019 without the retarding effect of these two preventable causes. ConclusionsDrug- and firearm-related deaths have increased so rapidly, especially among younger populations, that life expectancy at birth is significantly reduced by these causes of death. Without urgent action to tackle these preventable causes of death, US life expectancy will continue to stagnate and may even decline, even without the effect of COVID-19.

Multi-year comparison of VITEK MS performance for identification of rarely encountered pathogenic Gram-negative organisms (GNOs) in a large integrated Canadian healthcare region.

This multi-year study (2014-2019) compared identification of rare and unusual Gram-negative organisms (GNOs) by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) (VITEK MS, bioMérieux, Laval Que.) to 16S rRNA gene sequencing (16S) according to our laboratories routine workflow; 16S is done if initial MALDI-TOF MS gave discordant, wrong, or no results. GNB isolates were first analyzed by standard phenotypic methods and MALDI-TOF MS using direct deposit-full formic acid extraction; proteomics was repeated if no result occurred. Medically approved 16S analyses were done using fast protocols. Isolate sequences were analyzed using the Integrated Database Network System (IDNS3) bacterial database (SmartGene, Lausanne, Switzerland). Three hundred thirty-one GNOs including 251 (76%) aerobic Gram-negative bacilli (GNB), 63 (19%) fastidious Gram-negative coccobacilli (fGNCBs), and 17 (5%) Campylobacterales (CAMPB) isolates were recovered from 304 specimens; >1 isolate was recovered from 19 (6%). GNOs were mainly recovered from blood cultures (31.6%) and lower respiratory specimens (43%) (one-half were isolated from cystic fibrosis patients). Accurate genus vs species identities were obtained for 67.7% and 32.5% aerobic GNBs, 73% and 60% fGNCBs, and 23.5% CAMPB (with no discrepant species), respectively. Wrong or no results were obtained for 81 (32.3%) aerobic GNBs, 17 (27%) fGNCBs, and 13 (72.2%) CAMPB. No results or misidentifications occurred for 33% of aerobic GNBs, 26% of fGNCBs, and 76.5% of CAMPB due to absence of species in the instrument's database. VITEK MS performance remained stable for aerobic GNBs and fGNCBs but improved for CAMPB with addition of Campylobacter rectus and Campylobacter curvus to the database. 16S remains important for identification of GNOs when proteomics fails.IMPORTANCEMatrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has transformed the identification of commonly encountered Gram-negative organisms (GNOs) in the clinical laboratory, but rare and unusual organisms continue to challenge the technology. This study verified performance of VITEK MS for identification of a broad range of rare and unusual clinical GNO isolates by our large reference laboratory workflow over a multi-year period. Although most GNOs were accurately identified by MALDI-TOF MS, a small number of clinical isolates (~1%-6%) required 16S sequencing for identification depending on the GNO category. Approximately one-third of aerobic Gram-negative bacilli (GNBs) and two-thirds of Campylobacterales could not be accurately identified by proteomics due to lack of an organism in the instrument's database. MALDI-TOF MS databases should be continuously updated and validated, and laboratories should have a workflow for identification of unusual or rarely encountered aerobic, fastidious, and Campylobacterales GNOs that includes 16S rRNA gene sequencing whenever proteomics cannot give a definitive identification.

Differential quadrature lattice Boltzmann method for simulating fluid flows

In this study, a novel method for simulating incompressible flows using the lattice Boltzmann method is presented, aiming to improve robustness. This method is enhanced by the Qadyan numerical method. In the Qadyan method, Partial differential equations are solved using semi-discrete schemes combined with the differential quadrature method. To discretize the spatial derivatives of the lattice Boltzmann equation, the upwind differential quadrature method is employed, while the first-order forward difference scheme and/or fourth-order Runge-Kutta method handle the temporal term. The decision to exclude more complex methods stems from their requirement for refined computational grids. This work focuses on achievable results with similar types of uniform grids. The proposed scheme introduces and evaluates a novel method for solving both steady and unsteady problems. The present numerical method is validated by solving five benchmark problems, including heat diffusion on a slab, Stokes’ first problem, Taylor-Green vortex flow, flow around a flat plate, and flow in a lid-driven cavity. Reasonable agreements are obtained between the solutions obtained using this method and those from analytical/other numerical approaches. The Qadyan formulation delivers more accurate results compared to the finite-difference lattice Boltzmann method, (FDLBM), without requiring an increase in the number of grids. Notably, the novel Qadyan method achieves this increased accuracy without introducing additional complexity to the standard lattice Boltzmann method or resorting to non-uniform grids. This is possible due to the nature of the differential quadrature method, which utilizes more combinations of candidate stencils. The Qadyan method has a higher computational cost in comparison with the FDLBM.

Somatic coliphages as bioindicators of contamination in Lake Guamuez, Colombia

Lake Guamuez is the second largest lake in Colombia and economically supports hundreds of families in the area. The main activities carried out in the region have focused on tourism, agriculture, livestock, and rainbow trout production; however, these activities have been associated with contamination of the lake. This research aimed to evaluate the water quality of Lake Guamuez using somatic coliphages (SCs) as bioindicators. For this purpose, periodic sampling was carried out for six months at 9 strategic points of the lake. For the detection of SCs, the method described in 9211 D of the Standard Methods for the Examination of Water and Wastewater was used. The genomic variability and presence of virulence genes in the isolated SCs were determined. Water contamination in the lake is evident, and the SCs titer is greater in areas with a high flow of anthropogenic activities. An important degree of genetic diversity and a high prevalence of virulence genes could be observed among the SCs analyzed. The results when compared with guidelines and water quality standards from various countries, showed concentrations of SCs higher than those allowed. The high prevalence of gastrointestinal diseases in the region suggests a link to water contamination.

Methodology for the automated selection of time-frequency representations

Data preprocessing is a key step in extracting useful information from sound and vibration data and often involves selecting a time-frequency representation. No single time-frequency representation is always optimal, and no standard method exists for selecting the appropriate time-frequency representation, so selecting the time-frequency representation requires expert knowledge and is susceptible to human bias. To address this, this work introduces a methodology to automate the selection of a time-frequency representation for a dataset using only a subset of the healthy, or normal, class of data. To select the parameters for each type of time-frequency representation, Bayesian optimization is used. With a candidate from each type of time-frequency representation, the average similarity is used to select the final candidate. Additionally, the use of multiple time-frequency representations within a single model is explored. Because there is currently no objective method to compare the selected time frequency representations against, the proposed methodology is evaluated in two case studies. In the case studies, the time frequency representations are used as inputs to a simple convolutional neural network that achieved 100% accuracy in classifying bearing faults and 94% accuracy in classifying the contact tip to workpiece distance in wire arc additive manufacturing. Additionally, the proposed methodology presents a 75% and 94% reduction in the data size for the two case studies. This offers further benefits for reducing costs of data transmission and storage in modern digital manufacturing architectures.

Dengue-mediated changes in the vectorial capacity of Aedes aegypti (Diptera: Culicidae): manipulation of transmission or infection by-product?

An arthropod's vectorial capacity summarizes its disease transmission potential. Life-history traits, such as fecundity or survival, and behavioral traits, such as locomotor activity, host-seeking and feeding behavior, are important components of vectorial capacity. Studies have shown that mosquito-borne pathogens may alter important vectorial capacity traits of their mosquito vectors, thus directly impacting their transmission and epidemic potential. Here, we compile and discuss the evidence supporting dengue-mediated changes in the yellow fever mosquito Aedes aegypti (L.), its primary vector, and evaluate whether the observed effects represent an evolved trait manipulation with epidemiological implications. Dengue infection appears to manipulate essential traits that facilitate vector-host contact, such as locomotor activity, host-seeking, and feeding behavior, but the underlying mechanisms are still not understood. Conversely, life-history traits relevant to vector population dynamics, such as survival, oviposition, and fecundity, appear to be negatively impacted by dengue virus. Overall, any detrimental effects on life-history traits may be a negligible cost derived from the virulence that dengue has evolved to facilitate its transmission by manipulating Ae. aegypti behavior and feeding performance. However, methodological disparities among studies render comparisons difficult and limit the ability to reach well-supported conclusions. This highlights the need for more standardized methods for the research into changes in virus-mediated traits. Eventually, we argue that the effects on life-history traits and behavior outlined here must be considered when assessing the epidemiological impact of dengue or other arbovirus-vector-host interactions.

The Application of Aluminium- and Natural Clay- Based Compounds in the Treatment of Eutrophicated Waters in Semiarid Brazil

Objective: The presence of cyanobacteria in raw water can affect aquatic biota and human health, as some species are potentially toxic. In addition, these organisms can cause operational problems in water treatment plants, causing interference in the coagulation and flocculation processes, in addition to clogging the filters. The objective of this study was to test the efficiency of the application of poly aluminium chloride (PAC) and aluminium sulphate, with and without association with natural clay, in the removal of total phosphorus, chlorophyll a and cyanobacteria cells in eutrophic reservoir waters of the semi-arid region of Northeast Brazil. Theoretical Framework: The study is based on the application of materials (natural clays) with the capacity to adsorb and precipitate phosphorus from the aquatic environment, blocking its release after sedimentation. This application is efficient in removing sedimentation from cyanobacterial blooms with toxic potential from the aquatic environment Method: This is an experimental study, with tests carried out in Jar Test, with water from a eutrophic environment and with cyanobacteria blooms. Water samples were collected from the subsurface to analyze the parameters: pH, total phosphorus (PT), chlorophyll-a and quantity of cyanobacteria. PT pH and concentration were determined according to the techniques described in Standard Methods APHA (2012). Chlorophyll concentration was analyzed using the extraction technique with 96% ethanol (Jespersen; Christoffersen, 1987). For the qualitative and quantitative study of cyanobacteria, the analysis was carried out using an inverted microscope, according to the methodology of Utermöhl (1958), with sedimentation time in the counting chamber established according to the method of Margalef (1983). The density calculation was carried out according to Ross (1979), being expressed in number of individuals per milliliter (ind. mL-1). Results and Conclusion: The combined application of aluminium sulphate and PAC with natural clay (bentonite) functioned as an efficient technique to remove concentrations of total phosphorus and chlorophyll a, in addition to reducing the density of cyanobacteria. The reduction in the number of cyanobacterial cells with associated application of bentonite and coagulants was promising, with the removal of up to 100% of colonial species and 89% of filamentous species. Implications of the Researsh: The research highlights the relevance of applying low-cost techniques that optimize the quality of water offered for public supply. It should be noted that the presence of cyanobacteria in raw water can affect aquatic biota and human health, as some species have toxigenic potential. Furthermore, these organisms can cause operational problems in water treatment plants, interfering with the coagulation and flocculation processes, in addition to clogging filters. Originaly/Value: This study contributes to the understanding of the application of natural products (clays) as a phosphorus adsorbent and intact cyanobacteria cells. The research highlights that with additional studies, this approach could be a useful tool for removing cyanobacteria cells in water from eutrophic environments intended for public supply.

The Effect of a Combination of Multiwalled Carbon Nanotubes (MWCNT), Gold Nanoparticles (AuNPs), and Silica Microspheres (Si) on the Detection of 17α -Ethinylestradiol (EE2)

17α-ethinylestradiol (EE2) is a female synthetic hormone with high estrogenic activity that can disrupt the environment, which can lead to dire health problems. The current standard method is very time-consuming and expensive, so the objective of this study is to develop chemical sensors that are faster and much cheaper to detect EE2 in water samples. In this work, an electrochemical sensor using a combination of multiwall carbon nanotubes (MWCNT), gold nanoparticles (AuNPs), and silica microspheres (Si) as a modified electrode is reported to demonstrate 17α-ethinylestradiol (EE2) detection using electrochemical analysis. MWCNT-AuNPs, MWCNT-Si, and Si-AuNPs are prepared for the development of this chemical sensor by depositing each material on the carbon electrode by using the drop casting method. The resistance and conductivity of MWCNT-AuNPs, MWCNT-Si, and Si-AuNPs modified electrodes demonstrated stable electrochemical current responses towards the detection of EE2. It demonstrates that when MWCNTs and AuNPs are combined with Si, the sensitivity and R2 value improves at EE2 concentrations ranging from 10 to 50 μM, respectively.

Isolation and Characterization of Exosomes from Ocular Samples.

Exosomes are microsize vesicles secreted by nearly all cells to the extracellular space. The vesicles transport cell signaling and communicate with other cells. Ultracentrifugation is the standard method to isolate exosomes from culture media or body fluid. Without ultracentrifuge, exosomes can be precipitated by polyethylene glycol or separated by size exclusion chromatography. After isolation, nanoparticle tracking analysis can help to estimate the size and concentration of exosome samples. Transmission electron microscopy can directly show the size and morphology of exosomes. Moreover, the sample should be characterized by the expression of several exosome biomarker proteins. Exosomal contents such as proteins and miRNAs could be profiled using appropriate technologies.

Improved Standard Addition Method for Measuring Stable Isotopic Compositions and Its Application to Sulfur Isotope Composition.

The standard addition method (SAM) is widely used to measure the isotopic compositions of natural samples, particularly those with a complex matrix. However, traditional SAM has limitations for isotope systems with significant variations in isotope composition due to its reliance on approximation in calculation and the requirement for a priori estimates of analyte isotopic compositions and accurate concentrations. To overcome the issues, our work proposes an improved SAM that explicitly calculates isotope ratio R (i.e., XE/YE, 34S/32S for example) instead of approximating R* (mass number of isotope X divided by total mass number of all isotopes of an element) with R in SAM. Additionally, the sample fraction within standard-sample mixture in improved SAM is determined using the isotope compositions of standards, sample-standard mixtures, and the mixtures of both standards, rather than relying on sample concentrations and volumes. Both improvements not only overcome the shortcomings of traditional SAM but also empowered the approach's ability to accurately determine sample concentrations. To validate its effectiveness, we applied the improved SAM to natural samples with substantial sulfur (S) isotope variation (1.94 to 27.19‰) and low S concentration (0.81 to 3.47 μg g-1). The calculated δ34S values and concentrations of these samples are consistent with direct measurements within the error ranges while reducing sample sizes to 20% of those required for direct measurement. Moreover, our method achieves higher accuracy in δ34S values compared with traditional SAM. Both comparisons affirm the reliability and superiority of improved SAM.

Clinical pilot of bacterial transcriptional profiling as a combined genotypic and phenotypic antimicrobial susceptibility test.

Antimicrobial resistance is a growing health threat, but standard methods for determining antibiotic susceptibility are slow and can delay optimal treatment, which is especially consequential in severe infections such as bacteremia. Novel approaches for rapid susceptibility profiling have emerged that characterize either bacterial response to antibiotics (phenotype) or detect specific resistance genes (genotype). Genotypic and Phenotypic AST through RNA detection (GoPhAST-R) is a novel assay, performed directly on positive blood cultures, that integrates rapid transcriptional response profiling with the detection of key resistance gene transcripts, thereby providing simultaneous data on both phenotype and genotype. Here, we performed the first clinical pilot of GoPhAST-R on 42 positive blood cultures: 26 growing Escherichia coli, 15 growing Klebsiella pneumoniae, and 1 with both. An aliquot of each positive blood culture was exposed to nine different antibiotics, lysed, and underwent rapid transcriptional profiling on the NanoString platform; results were analyzed using an in-house susceptibility classification algorithm. GoPhAST-R achieved 95% overall agreement with standard antimicrobial susceptibility testing methods, with the highest agreement for beta-lactams (98%) and the lowest for fluoroquinolones (88%). Epidemic resistance genes including the extended spectrum beta-lactamase blaCTX-M-15 and the carbapenemase blaKPC were also detected within the population. This study demonstrates the clinical feasibility of using transcriptional response profiling for rapid resistance determination, although further validation with larger and more diverse bacterial populations will be essential in future work. GoPhAST-R represents a promising new approach for rapid and comprehensive antibiotic susceptibility testing in clinical settings.IMPORTANCEExposure to antibiotics causes differential transcriptional signatures in susceptible vs resistant bacteria. These differences can be leveraged to rapidly predict resistance profiles of Escherichia coli and Klebsiella pneumoniae in clinically positive blood cultures.

The construction and validity assessment of the respiratory air quality health index (AQHI) based on the analytic hierarchy process in Tianjin, China

BackgroundAir quality health index (AQHI), as a developed air quality risk communication tool, has been proved to be more accurate in predicting air quality related health risks than air quality index (AQI) by previous studies. However, the standard method to construct AQHI is summing the excess risks of single-pollutant models directly, which may ignore the joint effect of air pollutant mixtures.MethodsIn this study, a new method which could solve the aforementioned problem, Analytic hierarchy process (AHP), was introduced. Based on this method, we constructed the respiratory health related AQHI using years of life lost (YLL) as indicator of health outcome and compared its validity with AQI.ResultsThere was a correlation between daily AQI and AQHI in 2019 (R2 = 0.830, P < 0.01), and the chi-square test between the two excellent rates showed a statistically significant difference (χ2 = 4.156, P < 0.05). Both AQI and AQHI were correlated with the daily respiratory YLL (P < 0.01), however, the coefficient of AQHI was larger than those of AQI.ConclusionsThis study indicated that compared with AQI, the constructed AQHI based on AHP may predict the health risk of air pollution more effectively. AHP may become a new method to construct AQHI which needs to be proved by taking into consideration by more studies.

Dual-tuned floating solenoid balun for multi-nuclear MRI and MRS

Common-mode currents can degrade the RF coil performance and introduce potential safety hazards in MRI. Baluns are the standard method to suppress these undesired common-mode currents. Specifically, floating baluns are preferred in many applications because they are removable, allow post-installation adjustment and avoid direct soldering on the cable. However, floating baluns are typically bulky to achieve excellent common-mode suppression, taking up valuable space in the MRI bore. This is particularly severe for multi-nuclear MRI/MRS applications, as two RF systems exist. In this work, we present a novel dual-tuned floating balun that is fully removable, does not require any physical connection to the coaxial cable, and has a significantly reduced footprint. The floating design employs an inductive coupling between the cable solenoid and a floating solenoid resonator rather than a direct physical connection. Unlike the previous floating solenoid balun, this balun employs a two-layer design further to improve the mutual coupling between the two solenoids. A pole-insertion method is used to suppress common-mode currents at two user-selectable frequencies simultaneously. Bench testing of the fabricated device at 7 T demonstrated high common-mode rejection ratios at Larmor frequencies of both 1H and 23Na, even with a compact dimension (diameter 18 mm and length 12 mm). This balun's removable, compact, and multi-resonant nature enables light-weighting, allows more coil elements, and improves cable management for advanced multi-nuclear MRI/MRS systems.