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[Display omitted] • Exploration of anticancer dipeptide Aurantiamide acetate from the seeds of Brassica species. • Traditional 'Kolhu' method showed remarkable efficiency in extracting dipeptides. • Phytometabolite profiling was done by a validated UPLC-MS/QToF analytical method. • This novel method was found to be robust for the effective quantitation of dipeptides. Mustard (Brassica spp.) is one of the world's oldest condiments in the food basket, which holds a significant place in the global culinary landscape due to historical prominence and perceived health benefits. This study explores the extraction of oils from Mustard seeds by employing traditional 'Kolhu' method, modern supercritical fluid, and solvent extraction techniques. This study, for the first-time, identified Aurantiamide acetate, a potent anti-cancer dipeptide in Mustard seeds using ultra-performance liquid chromatography-mass spectrometry coupled with quadrupole time-of-flight (UPLC/MS-QToF) analytical platform. The analytical methodology was meticulously validated encompassing optimal parameters such as limit of detection, limit of quantification, precision, accuracy, linearity and robustness, within the range. Interestingly, 'Kolhu' method of oil extraction exhibited better yield of Aurantiamide acetate, suggesting superior efficiency of traditional methods. This study accentuates the importance of classical extraction methods, used traditionally, and emphasizes that naturally occurring substances indeed could be harnessed for better health. [ABSTRACT FROM AUTHOR]

SPARQL is a Query Language and a protocol popularly used in web semantics for the information retrieval. It is standard language declared by World Wide Web Consortium for resource description framework. Due to the exponential popularity of semantic web, bigdata, cloud computing, graph databases and linked open data, SPARQL Queries are playing a vital role in the stated domain for managing data with different aspects. This paper summarizes SPARQL usage in various domains touching the latest emerging technologies in computer science and various other fields. A brief analysis has been done of various tools on which SPARQL protocol can be executed for different purposes and it has been analyzed that using such protocols will generate tremendous results in different application areas towards integration of semantic web with different technologies like cloud computing, Linked Open Data (LOD) , Graph Databases and others. [ABSTRACT FROM AUTHOR]

The aim of the paper is to discuss the Levels Of Details (LODs) of 3D city models in order to assess the constructive and semantic characteristics that distinguish each of them. The standard approach used in order to build the 3D model is the CityGML 3.0 Conceptual Model. A key role for the development of the CityGML Conceptual Model is to provide a common definition of the basic entities, attributes, and relations of a semantically rich 3D city model. This approach is important with respect to the cost-effective sustainable maintenance of 3D city models, allowing the reuse of the same data in different application fields. In this context, we have developed a method to build a 3D CityGML model using SketchUP software and some of the tools implemented in it. In addition, the constructed model was displayed and validated by using an open source software (FZK viewer). The building taken into consideration is a vernacular dwelling structure called “trullo” (plural “trulli”) and present in the Apulia region, Italy. “Trulli” are extraordinary examples of dry stone construction with conical or pyramidshaped roof made with slabs, a technique dating back to prehistoric times and still in use today in Apulia. Before building the 3D model, it was necessary to perform the 3D survey of the building; this task was carried out by using Terrestrial Laser Scanner (TLS) that allowed a realistic and detailed reconstruction of the structures. From the point cloud, a special procedure was developed in order to build CityGML models in several LODs. [ABSTRACT FROM AUTHOR]

The development of science and technology had a strong impact on all branches of engineering, including geodesy and the possibility of acquiring and processing measurement data. The best example of this is the Terrestrial Laser Scanning, whih can perform measurements in the form of a multi-million-point cloud. The cloud, representing places and objects, becomes a spatial database. The current problem in engineering is no longer data acquisition and processing, but information excess and redundancy. The solution to this problem is optimisation, which is the process of reducing the amount of data. It should implement its assumptions in such a way as to remove or reduce unnecessary information without losing the information presented by an object. This issue is particularly important in the process of using point clouds in 3D modelling at various levels of detail. The appropriate levels of the LOD0–LOD4 model require a different type of data: on the one hand ensuring the obtainment of the appropriate accuracy class in the study, and on the other hand, the data source should not contain too detailed information that is unnecessary for the study, which makes the work harder and slows it down due to the need to operate on a huge amount of redundant information Therefore, the purpose of this paper is to determine the scope of work on the optimisation of the point cloud in order to adjust its number and quality to the needs of individual LODs. The results of the work allowed to determine the scope of data unification for the respective precision groups of 3D models generating. [ABSTRACT FROM AUTHOR]

This work is focused on the application of a laser-based technique, i.e., matrix-assisted pulsed laser evaporation (MAPLE) for the development of electrochemical sensors aimed at the detection of nitrites in water. Commercial carbon-based screen-printed electrodes were modified by MAPLE via the application of a newly developed composite coating with different concentrations of carbon nanotubes (CNTs), chitosan, and iron (II) phthalocyanine (C32H16FeN8). The performance of the newly fabricated composite coatings was evaluated both by investigating the morphology and surface chemistry of the coating, and by determining the electro-catalytic oxidation properties of nitrite with bare and modified commercial carbon-based screen-printed electrode. It was found that the combined effect of CNTs with chitosan and C32H16FeN8 significantly improves the electrochemical response towards the oxidation of nitrite. In addition, the MAPLE modified screen-printed electrodes have a limit of detection of 0.12 µM, which make them extremely useful for the detection of nitrite traces. [ABSTRACT FROM AUTHOR]

The prompt progression of web data and the number of web visitors creates a latent information overload problem and complicates data mining to select the right items on the web. E-commerce websites and applications manage information overload using several information filtering techniques such as personalized recommendation systems. The recommendation system creates a list of products to helps users. The proposed NOMINATE methodology offers characteristic values for definite elements from the LOD source as input for matrix factorization. This helps NOMINATE to retrieve user-specific functions. Subsequently studying the functions, the proposed approach produces an enhanced cluster of consumers by the weight of every user above the desired values of the element characteristics. For this, the NOMINATE methodology uses the particle swarm optimization (PSO) algorithm and k-means clustering algorithm. Using clustered results, the NOMINATE approach estimatiesthe centrality of proximity among other users in the cluster and identifies an experienced user for each cluster. In addition, the proposed recommendation scheme produces a set of characteristic values for each user based on the adept information of the users in the respective clusters. [ABSTRACT FROM AUTHOR]

In this review article, we performed an overview of extraction and chromatographic analysis methods of NPS in hair from 2007 to 2021, evaluating the limit of detection (LOD), limit of quantification (LOQ), limit of reporting (LOR), and limit of identification (LOI) values reported for each NPS. Our review aimed to highlight the limitations of modern hair analytical techniques, and the prerequisites for the proper evaluation and use of analytical results in relation to the objectives of NPS hair analysis. In the selected studies the detection of a total of 280 NPS was reported. The detected NPS belonged to seven classes: synthetic cannabinoids with 109 different substances, synthetic opioids with 58, cathinones with 50, phenethylamines with 34, other NPS with 15, tryptamines with ten, and piperazines with four substances. The NPS hair analysis of real forensic/ clinical cases reported the detection of only 80 NPS (out of the 280 targeted), in significantly higher levels than the respective LODs. The analytical protocols reviewed herein for NPS hair analysis showed continuously growing trends to identify as many NPS as possible; the extraction methods seem to have a limited potential to improve, while the various mass spectroscopic techniques and relevant instrumentation provide an enormous field for development and application. Hair is a biological indicator of the past chronic, sub-chronic, and, even, in certain cases, acute exposure to xenobiotics. Therefore, future research in the field could progress NPS hair analysis and aim the monitoring of NPS expansion and extent of use in the community.

ABSTRACT Ensuring SARS-CoV-2 diagnostics that can reliably detect emerging variants has been an ongoing challenge. Due to the rapid spread of the Omicron variant, point-of-care (POC) antigen tests have become more widely used. This study aimed at (i) comparing the analytical sensitivity (LOD) of 4 POC antigen assays, BD Veritor, Abbott BinaxNow, Orasure InteliSwab and Quidel QuickVue, for the Omicron versus the Delta variant and (ii) verifying the reproducible detection of Omicron by the 4 antigen assays. The LOD for all four assays were evaluated using Omicron and Delta virus stocks quantified for infectivity and genome copies. The four assays detected all replicates of Omicron and Delta dilutions at 104 and 105 TCID50/mL, respectively. We quantified both viral stocks using droplet digital PCR (ddPCR), which revealed that the Omicron stock had equivalent copies of the N gene to Delta at a one log lower infectious virus. The Abbott BinaxNow and Orasure InteliSwab had the highest analytical sensitivity for Omicron while the Orasure InteliSwab and the Quidel QuickVue had the highest analytical sensitivity for Delta. When 14 SARS-CoV-2 real-time PCR positive nasal/nasopharyngeal swab samples (12 Omicron and 2 Delta, mean Ct = 19.1), were tested by the four assays, only the QuickVue detected all samples. Antigen test positivity correlated with recovery of infectious virus on cell culture in 9 out of 13 tested specimens from symptomatic, asymptomatic, unvaccinated, and vaccinated individuals. Although our study confirms the reduced analytical sensitivity of antigen testing compared to molecular methods, the Omicron variant was detectable by the four evaluated rapid antigen tests. IMPORTANCE In the manuscript, we report an evaluation of the capability of 4 point of care (POC) antigen assays, the BD Veritor, Abbott BinaxNow, Orasure InteliSwab and Quidel QuickVue to detect the Omicron variant of SARS-CoV-2, and we compared their analytical sensitivity for Omicron versus Delta. In this analysis we found that all four assays detected Omicron and Delta at 104 and 105 TCID50/mL, respectively. We further quantified the viral stocks used by droplet digital (ddPCR) and found that the Omicron stock had equivalent copies of the N gene to Delta at a one log lower infectious virus titer and that an increased RNA to infectious virus ratio may be contributing to discrepancies in limit of detection in Omicron compared to Delta. We evaluated 14 SARS-CoV-2 real-time PCR positive nasal/nasopharyngeal swab samples (12 Omicron and 2 Delta), with an average cycle threshold value of 19.1, and only the QuickVue showed 100% agreement.

Background: Polypharmacy is common in people with dementia. The use of psychotropic drugs (PDs) and other, potentially inappropriate medications is high. The aims of this cross-sectional study were 1) to investigate the use of drugs in people with advanced dementia (PWAD), living at home or in long term care (LTC); 2) to focus on PD use; and 3) to identify determinants of PD use.Methods: The study was performed in the context of EPYLOGE (IssuEs in Palliative care for people in advanced and terminal stages of YOD and LOD in Germany). 191 PWAD were included. All drugs that were administered at the date of the examination were recorded. Multiple logistic regression analysis identified determinants of PD use.Results: 96% of PWAD received medication with a median number of four drugs. 49.7% received five or more drugs. According to the Beers Criteria 39% of PWAD ≥ 65 years received at least one potentially inappropriate medication. 79% of PWAD were treated with PDs. Older PWAD and PWAD living in LTC facilities received significantly more drugs than younger PWAD, and PWAD living at home, respectively. Dementia etiology was significantly associated with the use of antipsychotics, antidepressants and sedative substances. Place of living was associated with the use of pain medication. Behavioral disturbances were associated with the use of antipsychotics and sedative substances.Conclusions: To mitigate the dangers of polypharmacy and medication related harm, critical examination is required, whether a drug is indicated or not. Also, the deprescribing of drugs should be considered on a regular basis.Trial Registration: Clinicaltrial.gov, NCT03364179 . Registered 6 December 2017. [ABSTRACT FROM AUTHOR]

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The COVID‐19 pandemic swept across the globe in the latter half of 2019, throughout 2020 and into 2021. In response, many organizations implemented work from home policies, while others stopped operations entirely in an effort to limit the spread throughout their workforce and supporting communities. This containment strategy was not universally viable; long‐term shutdowns impacted the economic viability of companies, and some industries were designated as an "essential service" and thus continued operations. These employers faced the proposition of balancing the needs of the business and the community with a continued responsibility to provide a safe workplace for employees. This paper demonstrates how the application of common risk management methodologies, such as bowtie analysis combined with an appropriate assurance and verification process (e.g., the lines of defense model), can help the risks associated with a resumption or continuation of in‐person operations in a pandemic to be better understood and ensure the measures in place to manage said risk are appropriate and effective. [ABSTRACT FROM AUTHOR]

Diclofenac (DCL) is a nonsteroidal anti‐inflammatory commonly prescribed to treat inflammatory joint diseases and mild to moderate pain. DCL residues have often been detected in freshwater environments and it belongs to the list of emerging pollutants (EPs) because of the risk it presents for health and environment. Many studies have described the potential effects of DCL on organisms when exposed to environmental levels ranging from a few ng L−1 to tens of μg L−1 in surface water. Until now, its detection essentially depends on conventional techniques, such HPLC and GC/MS. Although these analytic techniques are very robust, they are expensive, require experts, and are not portable. Electrochemical sensors are an attractive alternative. They provide many benefits over thermal, optical, and piezoelectric detection including ease of use, rapidity, cost‐effectiveness, high sensitivity and selectivity, ease of miniaturization and robustness. The aim of this review is to report electrochemical methods used for the detection of DCL and to describe strategies for improving performances of each sensors. [ABSTRACT FROM AUTHOR]

The rendering of urban 3D scenes involves a large number of models, where the computer performance becomes a limitation. Arbitrarily putting all the models in a folder for storage significantly reduces the data processing efficiency when the models are called. There are also issues of storage redundancy and semantic fragmentation at the storage boundary. We propose a 3D scene management method based on an adaptive quadtree and scene graph (AQT-SG) that can solve the above problems. According to the spatial distribution characteristics of 3D scene data, this method adopts an adaptive quadtree for organizing complex 3D city scenes at the macro and meso scales, traversing the quadtree from bottom to top and calculating the geometric error at each level and in the middle. The node generates level of detail, builds a flexible multiscale 3D tile model, and uses scene graphs for the microscale organization and management of 3D scenes. We verified the proposed method with park data from a smart park management system. Large-scale complex 3D scene visualization and a comparison of the results of storage redundancy experiments verified that the data organization efficiency was optimized and the visual experience was improved by this method. [ABSTRACT FROM AUTHOR]

H 2 gas sensors for different applications require various detection ranges, such as 1–100 ppm for exhale breath test and 0–40000 ppm for H 2 energy vehicles. Coarse-tuning of the detection range could be realized by the selection of the type of H 2 sensors. The fine-tuning of the detection range within one type of H 2 sensor, however, is little concerned and reported. Herein, we propose to achieve the fine-tuning of the H 2 gas detection range of the AlGaN/GaN HEMT devices by adjusting the Pt gate thickness. Devices with various Pt gate thicknesses of 2, 20, 60, and 100 nm were fabricated and investigated. Results show that the HEMT devices have excellent pinch-off characteristic with an on-to-off ratio of ∼four orders of magnitude. For the 100 nm thick device exposed to 500 ppm H 2 , ultrafast response time of 1.5 s is observed together with high response. With the decrease of gate thickness, both the response and the response time gradually increase, 1850% and 6 s for the 2 nm thick device. Moreover, both the low limit of detection (LOD) and the saturation cencentration decrease from 1.6 to 0.14 ppm and from 30,000 to 5000 ppm, respectively, with the gate thickness reduced from 100 to 2 nm, revealing that fine-tuning of the detection range could be achieved by adjusting the gate thickness. Finally, the response activation energy is also studied, 15.9, 19.7, and 42.8 kJ/mol for 2, 60, and 100 nm thick devices, respectively. [Display omitted] • Employment of AlGaN/GaN HEMT device as a H2 gas sensor. • Demonstration of a high performance H2 sensor with small LOD ∼0.14 ppm and ultrafast response ∼1.5 s. • Realization the fine-tuning of the detection range by simply adjusting the gate thickness. • Study the dependence of the response activation energy Ea on the gate thickness. [ABSTRACT FROM AUTHOR]

Infrared (IR) spectroscopic imaging instruments' performance can be characterized and optimized by an analysis of their limit of detection (LOD). Here we report a systematic analysis of the LOD for Fourier transform IR (FT-IR) and discrete frequency IR (DFIR) imaging spectrometers. In addition to traditional measurements of sample and blank data, we propose a decision theory perspective to pose the determination of LOD as a binary classification problem under different assumptions of noise uniformity and correlation. We also examine three spectral analysis approaches, namely, absorbance at a single frequency, average of absorbance over selected frequencies and total spectral distance – to suit instruments that acquire discrete or contiguous spectral bandwidths. The analysis is validated by refining the fabrication of a bovine serum albumin protein microarray to provide eight uniform spots from ∼2.8 nL of solution for each concentration over a wide range (0.05–10 mg/mL). Using scanning parameters that are typical for each instrument, we estimate a LOD of 0.16 mg/mL and 0.12 mg/mL for widefield and line scanning FT-IR imaging systems, respectively, using the spectral distance approach, and 0.22 mg/mL and 0.15 mg/mL using an optimal set of discrete frequencies. As expected, averaging and the use of post-processing techniques such as minimum noise fraction transformation results in LODs as low as ∼0.075 mg/mL that correspond to a spotted protein mass of ∼112 fg/pixel. We emphasize that these measurements were conducted at typical imaging parameters for each instrument and can be improved using the usual trading rules of IR spectroscopy. This systematic analysis and methodology for determining the LOD can allow for quantitative measures of confidence in imaging an analyte's concentration and a basis for further improving IR imaging technology. Graphical Abstract [ABSTRACT FROM AUTHOR]

The paper describes the problems of intentions of the rapid introduction of BIM technologies in the construction industry of Ukraine. The research methodology involves analysis of national building standards, BIM technologies that have already been partially tested and a new logical structure of design processes in the logic of BIM technology in Ukraine. It is proposed to introduce into the design practice a number of actions aimed at harmonizing the key stages of BIM-technologies development with the regulatory framework. The European LOD stages and Ukrainian stages of designing are compared; it is proposed to introduce and gradation enshrine it in state building standards. The correctness problem of competitive tender documentation form for the development of project documentation in Ukraine is highlighted. The issue of the need for a detailed review of European Union standards in terms of national specifics and their gradual implementation in the Ukrainian legal framework was raised. It is proved that the proposed measures will improve the quality of design solutions in terms of economic feasibility and environmental friendliness, and government agencies will be able to qualitatively control all design and construction processes. [ABSTRACT FROM AUTHOR]

The construction industry relies on precise building information for evaluating designs performance, collaboration, and delivery. For more than a decade, the Level of Development (LOD) is the most popular concept for describing the progression of geometric and semantic information across the design phases. The LOD is a domain language that aims to establish a common understanding of what each level means to facilitate communication and defining deliverables in contracts among the project participants. However, multiple similar standards are published worldwide for a similar purpose, such as Level of Detail, Level of Definition, and Level of Information Need. However, although they are similar at first glance, in many cases, they have numerous deviations in their fundamentals. This paper investigates the differences of the LOD standards and their interpretation by the scientific community through a thorough analysis. For this purpose, 58 LOD guidelines were reviewed, and a systematic literature review of 299 peer-reviewed publications was conducted. As a result, existing trends in using the LOD in research and the most widespread LOD naming conventions and specifications were identified. Additionally, the results highlight 16 common use cases for applying the LOD. [ABSTRACT FROM AUTHOR]

Wanting to answer the questions unsolved by a previous study supported by a survey with total station, this article illustrates the results obtained with 3D laser scanning acquisitions and photo shot datasets. The precision provided by the phase shift ranging scanner technology has allowed to measure to the millimeter the deviation between the surveyed model (objective of reality, although discontinuous) and the geometric model on these data interpreted. In addition, the mathematical hypotheses useful for parametric modelling (geometry processing) are discussed. Virtualizations have been created by adopting knowledge filters and scientific tools that address to the digital (re)construction (HBIM) that allows to share and manage information and to integrate interoperable models in accordance with current public procurement regulations.

The paper explores the strategies and methods for preserving Linked Open Data (LOD). To this aim it first presents an overview of the main scientific initiatives that have dealt with this topic. Then it describes some digital technologies that may result useful for preserving LOD, providing some insights on their application to LOD. It also provides a concrete example of implementation of the Semantic Web technologies for preserving Linked Data. Finally, it suggests some specific themes and directions that should be further investigated in order to elaborate a comprehensive solution to this problem: the preservation of Linked Open Data cannot be demanded to a single tool or method, it is rather the result of technical, organizational and procedural choices that altogether make up a consistent framework for LOD preservation.

Linked Open Data (LOD) is an emerging Web technology to store and publish structured data in the form of interlinked knowledgebases like DBpedia, Freebase, Wikidata, and Yago. It uses structured data from multiple domains, and it can be used to conceptualize a concept of interest. Recently, researchers have shown that incorporating contextual features in recommender systems improves rating prediction accuracy. However, identification of contextual features for building context-aware recommender systems is a major bottleneck. To this end, in this article, we present the development of a context-based recommender system, CRecSys, for item ratings prediction in movie domain. CRecSys extracts item-based contextual features from the underlying dataset and generates an RDF graph to model items and their contextual features for computing context-based items similarity using graph matching techniques and item-based collaborative filtering. It uses LOD and two well-known movie data sources - Rotten Tomatoes and IMDB for item profiling using a dataset of 1300 movies. CRecSys is experimentally evaluated over two movie datasets, one is generated by the authors and second is the MovieLens-1M benchmark dataset. CRecSys is also compared with ten baselines and two state-of-the-art recommendation methods, and performs significantly better. It is also empirically established that CRecSys is able to effectively deal with some of the open challenges like cold-start and limited content problems of the traditional recommender systems.

The objectives of this paper will be to discuss the issues related to the determination of the limits of detection (LOD) in laser-induced breakdown spectroscopy (LIBS) analytical applications. The derivation of the commonly used ‘3-sigma over slope’ rule and its evolution towards the new official definition recently adopted by the International Union of Pure and Applied Chemistry (IUPAC) will be illustrated. Methods for extending the calculation of the LOD to LIBS multivariate analysis will also be discussed, using as an example the detection of Cu traces in cast iron samples by LIBS.

Heritage Building Information Modeling (HBIM) is increasingly utilized to develop accurate and semantic-rich databases for the representation, preservation, and renovation of cultural heritage. A critical factor in successful HBIM delivery is the intended uses of the model, which need to be established by stakeholders at the onset of the program. Despite the greater application of Building Information Modeling (BIM) technologies to HBIM workflows, the discipline continues to lack clarity regarding information requirements from a tenant perspective. The first stage of this research was a review of 26 published HBIM case studies to extract information including HBIM workflows, level of development (LOD) models in the field, and the stakeholders’ participation in the HBIM program. The findings from the case studies conclude that most HBIM methodologies did not seek to understand the needs of assumptive stakeholders and lacked a clearly defined objective. Ten interviews with proprietors of ten different historic courthouses in the southeastern United States were also included in the study, which were used to identify the priorities of HBIM programs from a built heritage stakeholder’s standpoint. These priorities were used in conjunction with reviewed field standards to develop LOD supplement guidelines applicable for HBIM, which were then validated through a case study. The findings of this research conclude that the creation of LOD guidelines for HBIM application is both achievable and advisable, as they allow stakeholders to identify their priorities for HBIM projects. Such guidelines would assist in standardizing the HBIM discipline and disseminating its usefulness to historic building managers. This research also provides standards that allow cultural heritage stakeholders to make informed decisions about potential HBIM programs and maximize the use of resources to implement such programs. Moreover, the methodology implemented in this research offers a valuable example for future studies on HBIM guidelines and regulations.

There are rising issues regarding the presence and discharge of emerging pollutants (EPs) in the ecosystem, including pharmaceutical waste, organic contaminants, heavy metals, pesticides, antibiotics and dyes. The human populace is typically exposed to a variety of EPs and toxins, such as those found in the soil, air, food supply, and drinkable water. Thus, creating new purification methods and effective pollution detection tools is a significant task. Several researchers globally have created unique analytical techniques including chromatography/mass and gaseous atomic absorption spectroscopy for the identification of contaminants to date. The aforementioned techniques have excellent sensitivity, but they are costly, time-consuming, costly, need sophisticated expertise to operate and are difficult to execute due to their enormous scale. Electrochemical sensors with resilience, specificity, sensibility, and real-time observations are thus been designed as a solution to the aforementioned shortcomings. The development of innovative systems to assures human and environmental protection has been aided by significant improvements in nanostructured carbon-based electrochemical sensor platforms. These platforms show enticing characteristics including excellent electrocatalytic operations, increased electrical conductance, and efficient surface region when compared to conventional methods. This paper intends to provide an analysis of low-cost nanostructured carbon-based electrochemical sensors from 2015 to 2022 that could detect and eradicate components of EPs from various origins. This review discusses the characteristics and uses of nanostructured carbon-based electrochemical sensors, which include carbon nanotubes, MXenes, carbon dots/graphene dots, graphene/graphene oxide, and other materials. These sensors are used to detect EPs such as heavy metal ions (Pb(II), Cd(II), Hg(II), etc), pharmaceutical waste, dyes and pesticides. Additionally, processing and characterization techniques, including differential-pulsed voltammograms, SW voltammograms, ultraviolet-visible spectroscopy, fluorescence, electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and scanning electron microscopy (SEM) are discussed in detail to examine the prospects of these carbon-based electrochemical sensors and associated detection mechanisms. It is intended that this analysis would stimulate the development of new detection methods for protecting public health and restoring the environment.

Lipidomic data often exhibit missing data points, which can be categorized as missing completely at random (MCAR), missing at random, or missing not at random (MNAR). In order to utilize statistical methods that require complete datasets or to improve the identification of potential effects in statistical comparisons, imputation techniques can be employed. In this study, we investigate commonly used methods such as zero, half-minimum, mean, and median imputation, as well as more advanced techniques such as k-nearest neighbor and random forest imputation. We employ a combination of simulation-based approaches and application to real datasets to assess the performance and effectiveness of these methods. Shotgun lipidomics datasets exhibit high correlations and missing values, often due to low analyte abundance, characterized as MNAR. In this context, k-nearest neighbor approaches based on correlation and truncated normal distributions demonstrate best performance. Importantly, both methods can effectively impute missing values independent of the type of missingness, the determination of which is nearly impossible in practice. The imputation methods still control the type I error rate., (© 2024 The Authors. Proteomics published by Wiley‐VCH GmbH.)

Histamine is commonly present in food containing proteins, like in mackerel. Consuming fish is imperative for the improvement of human muscles. Nevertheless, some studies reported ingesting fish containing histamine more than 50 mg·kg-1 can cause toxicity. This study analyzed and determined the composition of histamine in mackerel and its products commonly consumed in Malaysia, especially on the East Coast of Malaysia. These included processed mackerel such as canned products, satay (skewed fish) and keropok lekor (fish cake/ cracker). Histamine analysis was performed using High Performance Liquid Chromatography (HPLC) equipped with a fluorescence detector. A derivatizing reaction was applied to increase the sensitivity of HPLC to histamine using 9-flourenilmethylchloroformate (FMOC-Cl). The chromatographic separation was achieved in 15 min. Method validation was in accordance to Commission Decision 657/2002/CE. The linear range was at 0.16 - 5.00 µg·mL-1 (histamine) with the LOD at 0.10 µg·mL-1 and LOQ at 0.30 µg·mL-1. Method applicability was checked on seven real samples involving raw, cooked, and dry products, yielding acceptable recovery. [ABSTRACT FROM AUTHOR]

Background: The current group B streptococcal (GBS) preventive measures had reduced invasive GBS early onset disease (EOD) incidences worldwide, but the late onset disease (LOD) incidences had remained unchanged. Administration of a safe and effective GBS vaccine in addition to the current strategies were thought to be the next steps in reducing the incidences of invasive GBS infection especially LOD. In this study, we aimed to examine the causative GBS serotypes in invasive GBS disease, determine the incidences of EOD and LOD, and compare the risk factors between EOD and LOD.Methods: A retrospective study of infants ≤ 90-day-old over an 8-year period (2010-2017). The incidences of EOD and LOD were obtained by using patients with EOD and LOD who were born in our institution as the numerator and the live births in our institution per year of the study period as the denominator. Available GBS isolates were serotyped by the National Public Health Laboratory using capsular serotyping methods. The risk factors of EOD and LOD were compared.Results: A total of 71 infants were identified; 16 (22.5%) and 55 (77.5%) of them had EOD and LOD, respectively. Serotype III (n = 42, 71.2%) was the most common serotype amongst the 59 isolates available for serotyping. Serotypes Ia, Ib, II, III, and V accounted for 98.3% (n = 58) of the invasive GBS diseases. The overall incidence was 0.42 per 1000 live births. The mean incidences of EOD and LOD were 0.13 per 1000 live births and 0.29 per 1000 live births, respectively. On multivariate analysis, risk factors for LOD as compared to EOD were: Chinese ethnicity (OR 27.1, 95% CI 3.0-243.1, p = 0.003) and negative/unknown maternal GBS status (OR 20.0, 95% CI 2.0-250.0, p = 0.012). Prematurity and intrapartum risk factors (peripartum maternal pyrexia, prolonged rupture of membrane) of EOD were not associated with LOD.Conclusions: The LOD incidence had remained higher than EOD incidence in our cohort. A GBS vaccine that covers the major causative serotypes found in our cohort can potentially reduce the overall GBS disease burden in the country. [ABSTRACT FROM AUTHOR]

Laser-induced breakdown spectroscopy (LIBS) was explored as a method of monitoring oxygen (O) concentration in electrolytic reduction salt of pyroprocessing. Simulated salt samples were fabricated, and each sample was put in a transparent and sealed vial filled with argon gas. An neodymium-doped yttrium aluminum garnet (Nd:YAG) laser pulse was applied to the sample through the vial surface, and the optical emission spectrum was measured. O(I) 777.2 nm lines were clearly identified in the spectrum of a sample containing Li2O, and the intensity of the O peak and the intensity ratio of O and lithium (Li) peaks, in which Li was used as the normalization, increased linearly as the O concentration in the salt sample was increased. The limit of detection and root mean square error were calculated for the cases of O peak area, O peak height, peak area ratio of O–Li, and the peak height ratio of O–Li, and all the cases could indicate that the O concentration in the electrolytic reduction salt was out of normal range. Our result shows that LIBS has the possibility to be used as a method for monitoring of O in electrolytic reduction salt. Graphical Abstract [ABSTRACT FROM AUTHOR]

We report an ultrasensitive nanohybrid electrochemical DNA sensor developed to detect the LipL32 gene of Leptospira interrogans that causes leptospirosis. A carboxylated multiwalled carbon nanotubes electrode with gold nanoparticles (c-MWCNTs/nano-Au) was modified with polyamidoamine (PAMAM) and graphene quantum dots using cysteine (Cys) as a linker. The c-MWCNTs/nano-Au electrode was covalently bonded to polyamidoamine (PAMAM) via Cys through Au-SH bonding. The amino group of PAMAM was linked to carboxyl moiety of graphene quantum dots (GQD) to form a c-MWCNTs/nano-Au/Cys/PAMAM/GQD nanohybrid electrode. A 5'-amino (NH2) labeled single-stranded DNA (ssDNA) probe based on the LipL32 gene was immobilized on the surface of a c-MWCNTs/nano-Au/Cys/PAMAM/GQD nanohybrid electrode. The different dilutions of single-stranded genomic DNA (ssG-DNA) of L. interrogans were treated on immobilized DNA probe to allow the hybridization. The hybridization events are measured using cyclic voltammetry (CV), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS) using redox indicators of 1 mM methylene blue and potassium ferricyanide. Field emission scanning electron microscopy (FE-SEM) was performed to analyze the modifications done on the surface of the electrode. The developed nanohybrid sensor has a sensitivity of 1952.3 µA cm−2 ng−1 and a lower limit of detection (LOD) of 0.112 pg/µl (R2 = 0.98). The nanohybrid sensor showed good reproducibility over a period of 6 months, exhibiting only a 10% loss in actual DPV current. The developed nanohybrid sensor is found to be specific to L. interrogans with high sensitivity and reproducibility, and it can be used for routine analysis for L. interrogans identification and leptospirosis diagnosis. [ABSTRACT FROM AUTHOR]

Here, we present a direct comparison of different dyes and assays for the determination of protein concentrations. We compared the classical Bradford assay with two modern assays based on the fluorogenic dyes QuDye and ProteOrange and showed that the Bradford reagent achieved excellent results in the determination of protein concentrations as compared with more modern rivals. We also showed that standard approaches for determining the limit of detection (LoD) and limit of quantification (LoQ) may not work correctly with the tested dyes. We proposed a new approach that extends the standard algorithm for LoD and LoQ determination. This approach works well with both classical colorimetric and fluorogenic dyes, as well as with nontrivial fluorescent probes.

We report on the electrochemical determination of one the most effective and widely used chemotherapeutic, anti-inflammatory, and immunomodulator agents, methotrexate (MTX), using low-cost, green, and facile one-pot prepared graphitic carbon nitride (g-CN ) nanosheets. The g-CN nanosheets have been characterized utilizing Fourier transform infrared spectroscopy, X-ray diffraction(XRD), scanning electron microscopy(SEM), and density functional theory (DFT). In comparison to the bare carbon paste electrode (CPE), the g-CN -modified electrode showed a spectacular enhancement in the electrochemical oxidation and detection abilities of MTX. The proposed material exhibits very low limits of detection (12.45 nM) and quantification (41.5 nM), while possessing a wide linear range of 0.22–1.11 μM and 1.11–27.03 μM under optimized conditions at pH 7.0. Due to the ease of preparation of g-CN, it can be adopted for the cost-effective detection of MTX in industrial and clinical analyses.

Currently, Building Information Modeling (BIM) is increasingly entering the operational level in terms of creating a model for newly constructed facilities. For existing objects, and objects of Culture Heritage (CH), the creation of coherent and qualitative BIM models depends on the quality of the data constituting the basis for modelling. What’s more, BIM of CH is not only a challenge to obtain high-quality three-dimensional data, but also a time-consuming study of object documentation and photographic documentation in order to create a faithful library of parametric objects. In the article, the authors presented the synergy of spatial data with TLS and UAV as the basis for creating a BIM model for two CH objects. The aim of the article was to make such a synergy of TLS and UAV data that the geospatial database, developed for the needs of modelling historic objects in the HBIM trend, would have a specific amount of information without the frequently used redundancy. In principle, the acquired 3D database should be expressed in a global reference system with the degree of georeferencing accuracy for situational and altitude measurements and should be consistent to provide comprehensive information about the object. The analyses led to conclusions in which the authors assign superior importance to the accuracy of measurement information and the integration of individual data groups in the process of developing the HBIM model with the desired accuracy in opposition to the appropriate selection of the level of detail, which is usually assigned a superior role, which in turn results from the quality of the data geospatial modelling.

Background: In 2017, the European Commission renewed the approval of glyphosate (GLY) but only for five years. GLY remains one of the most controversial and studied molecules. Method: A simplified method was tested for the determination of GLY in white rice (WR) and brown rice (BR), after extraction only with a methanol solution, by liquid chromatography coupled with inductively coupled mass triple quadrupole (HPLC-ICP-MS/MS) with a PRP-X100 anionic column. After performing a test on groundwater, the quantification of GLY in WR and BR was validated in terms of the LOD, LOQ, accuracy, precision, linearity, and the matrix effect. Results: The LOD was 0.0027 mg kg−1 for WR and 0.0136 mg kg−1 for BR. The LOQ was 0.0092 mg kg−1 for WR and 0.0456 mg kg−1 for BR. The mean recoveries were within 76–105% at three fortification levels. The relative standard deviation for the analysis (five replicates for three spike levels) was < 11% for both matrices. A linear response was confirmed in all cases in the entire concentration range (R2WR = 1.000 and R2BR = 0.9818). Conclusion: The proposed method could be considered useful for the determination of GLY in different types of rice and designed and adapted for other cereals. The matrix effect, quantified in BR matrix extraction, could be avoided by using a matrix-matched calibration line.

This article compares the applications of traditional gold and silver-based SERS substrates and less conventional (Pd/Pt, Cu, Al, Si-based) SERS substrates, focusing on sensing, biosensing, and clinical analysis. In recent decades plethora of new biosensing and clinical SERS applications have fueled the search for more cost-effective, scalable, and stable substrates since traditional gold and silver-based substrates are quite expensive, prone to corrosion, contamination and non-specific binding, particularly by S-containing compounds. Following that, we briefly described our experimental experience with Si and Al-based SERS substrates and systematically analyzed the literature on SERS on substrate materials such as Pd/Pt, Cu, Al, and Si. We tabulated and discussed figures of merit such as enhancement factor (EF) and limit of detection (LOD) from analytical applications of these substrates. The results of the comparison showed that Pd/Pt substrates are not practical due to their high cost; Cu-based substrates are less stable and produce lower signal enhancement. Si and Al-based substrates showed promising results, particularly in combination with gold and silver nanostructures since they could produce comparable EFs and LODs as conventional substrates. In addition, their stability and relatively low cost make them viable alternatives for gold and silver-based substrates. Finally, this review highlighted and compared the clinical performance of non-traditional SERS substrates and traditional gold and silver SERS substrates. We discovered that if we take the average sensitivity, specificity, and accuracy of clinical SERS assays reported in the literature, those parameters, particularly accuracy (93–94%), are similar for SERS bioassays on AgNP@Al, Si-based, Au-based, and Ag-based substrates. We hope that this review will encourage research into SERS biosensing on aluminum, silicon, and some other substrates. These Al and Si based substrates may respond efficiently to the major challenges to the SERS practical application. For instance, they may be not only less expensive, e.g., Al foil, but also in some cases more selective and sometimes more reproducible, when compared to gold-only or silver-only based SERS substrates. Overall, it may result in a greater diversity of applicable SERS substrates, allowing for better optimization and selection of the SERS substrate for a specific sensing/biosensing or clinical application.

In this study, we evaluated the performance of the in-house developed rRT-PCR assay for SARS-CoV-2 RNA targeting the envelope (E) and nucleocapsid (N) genes with internal control as human RNase P. A total of 50 positive samples and 50 negative samples of SARS-CoV-2 were tested by a reference kit at site 1 and a subset (30 positives and 16 negatives) of these samples are tested blindly at site 2. The limit of detection (LoD) was calculated by using a replication-deficient complete SARS-CoV-2 genome and known copy numbers, where Pseudo-virus samples were used to evaluate accuracy. On site 1, among the 50 SARS-CoV-2 positive samples 24, 18, and eight samples showed high (Ct < 26), moderate (26 < Ct ≤ 32), and low (32 < Ct ≤ 38) viral load, respectively, whereas in site 2, out of 30 SARS-CoV-2 positive samples, high, moderate, and low viral loads were found in each of the 10 samples. However, SARS-CoV-2 was not detected in the negative sample. So, in-house assays at both sites showed 100% sensitivity and specificity with no difference observed between RT PCR machines. The Ct values of the in-house kit had a very good correlation with the reference kits. LoD was determined as 100 copies/mL. It also displayed 100% accuracy in mutant and wild-type SARS-CoV-2 virus. This Bangasure™ RT-PCR kit shows excellent performance in detecting SARS-CoV-2 viral RNA compared to commercially imported CE-IVD marked FDA authorized kits.

In order to respect the good practices in archaeology disseminated by the MASA Consortium (Archaeologists and Archaeological Sites Memories), the Laboratoire Archéologie et Territoires (Tours, France) wished to evaluate the progress of ArSol database (Soil Archives), its field data management database, with regard to the FAIR principles or the Five-Star Linked Open Data. The work undertaken to achieve compliance with these precepts has shown that it is also necessary to ensure the relevance and reliability of the published data. For data to be reusable, it seems essential to ensure traceability. Various tools' set-up for the ArSol database makes it possible to ensure this traceability from the field recording, through its exploitation, to the publication of the results of the excavation. The traceability of data, to ensure their quality in terms of reliability and relevance, is an aspect that is fortunately already taken into account in the ArSol database and that complements satisfactorily the FAIR principles requirements. [ABSTRACT FROM AUTHOR]