High Spatiotemporal Precision Mapping of Optical Nanosensor Array Using Machine Learning.

Optical nanosensors, including single-walled carbon nanotubes (SWCNTs), provide real-time spatiotemporal reporting at the single-molecule level within a nanometer-scale area. However, their superior sensitivity also makes them susceptible to slight environmental influences such as reference analytes in media, external fluid flow, and mechanical modulations. Consequently, they often fail to achieve the optimal limit of detection (LOD) and frequently convey misinformation spatiotemporally. To address this challenge, we developed a single-pixel mapping technique for optical nanosensor arrays that operates with high spatiotemporal precision using machine learning. We systematically measured the spatial sensing images of various analyte concentrations below the LOD by using a near-infrared (nIR) fluorescent SWCNT nanosensor array. For dopamine (DA) as an example analyte, we extracted single-pixel level sensing features such as entropy, the Laplacian operator, and neighboring values under noise levels. We then trained the artificial intelligence (AI) model to accurately identify specific reaction pixels of the nanosensor array, even below the LOD region. Additionally, our method can distinguish subtle noise caused by fluid in the media or mechanical modulation of the array substrate. As a result, our approach significantly improved the detection sensitivity of the nanosensor array, achieving a 13-fold increase over the original LOD and halving the detection time of the reporter pixels, with F1 scores exceeding 0.9. This method not only lowers the LOD of optical nanosensors but also isolates sensor responses specific to the analyte, providing accurate spatiotemporal information to the user, even in noisy conditions. It can be universally applied to various optical nanosensor materials and analytes, maximizing the sensitivity and accuracy of the nanosensors used in diagnostics and analysis.

Highly Efficient Detection of Pd2+ in Aqueous Medium by an Elusive Mn(II) Coordination Polymer.

Herein, we report the synthesis of a Mn(II)-based coordination polymer (CP); and its structure, phase consistency and thermal stability have been established by single-crystal X-ray diffraction (SCXRD), powder X-ray diffraction (PXRD) and thermalgravimetric analysis (TGA) respectively. This is the first example of paramgnetic Mn(II)-based CP that acts as pH-dependent emitting material [lem= 525 nm (pH = 2.0-4.0) and 450 nm (pH = 5.0-12.0)]. Its emission is quenched by Pd2+ in aqueous medium in presence of other thirteen cations with reasonably low pH-dependent limits of detection (LODs) [21.178 ppb (pH= 3), 15.005 ppb (pH = 7.0) and 59.940 ppb (pH = 10.0)] as described by well-established mechanism. Therefore, urgency of such stable sensor remains high in regard to the environmental pollution.

A reliable qPCR technique for detecting viable Xanthomonas arboricola pv. pruni cells.

Xanthomonas arboricola pv. pruni (Xap) is the causal agent of bacterial spot of stone fruits and almond (Prunus spp). Detection of Xap is typically carried out using quantitative real-time PCR (qPCR) combined with culture-based isolation. However, qPCR does not differentiate between viable and dead cells, potentially leading to an overestimation of the infective population in a sample. Such overestimation could result in unnecessary phytosanitary measures. The present study aims to develop a specific protocol ideally targeting to detection of only live Xap bacterial cells. To address this challenge, the viable quantitative PCR (v-qPCR) method was evaluated using three nucleic acid-binding dyes: propidium monoazide (PMA), a combination of PMA and ethidium monoazide (EMA), and PMAxx™, an improved version of PMA. PMAxx™ proved to be the most suitable dye for the detection and quantification of living bacterial cells. This methodology was also evaluated in infected plant material over time and can be considered a rapid and reliable alternative to PCR methods for detecting only those putative infective Xap that may pose a risk for Prunus crops. KEY POINTS: • Protocol to detect biofilm and planktonic viable X. arboricola pv. pruni cells. • Host validated protocol. • Benefits, reduction of chemicals in disease control.

The LOD paradox: When lower isn't always better in biosensor research and development.

Biosensor research has long focused on achieving the lowest possible Limits of Detection (LOD), driving significant advances in sensitivity and opening up new possibilities in analysis. However, this intense focus on low LODs may not always meet the practical needs or suit the actual uses of these devices. While technological improvements are impressive, they can sometimes overlook important factors such as detection range, ease of use, and market readiness, which are vital for biosensors to be effective in real-world applications. This review advocates for a balanced approach to biosensor development, emphasizing the need to align technological advancements with practical utility. We delve into various applications, including the detection of cancer biomarkers, pathology-related biomarkers, and illicit drugs, illustrating the critical role of LOD within these contexts. By considering clinical needs and broader design aspects like cost-effectiveness, sustainability, and regulatory compliance, we argue that integrating technical progress with practicality will enhance the impact of biosensors. Such an approach ensures that biosensors are not only technically sound but also widely useable and beneficial in real-world applications. Addressing the diverse analytical parameters alongside user expectations and market demands will likely maximize the real-world impact of biosensors.

Recent advances in electrochemical detection of common azo dyes.

PURPOSE: Food forensics is an emerging field and the initial part of this review showcases the toxic effects and the instrumental methods applied for the detection of the most commonly used azo dyes. Electrochemical detection has a lot of advantages and hence the significance of the most important techniques used in the electrochemical detection is discussed. The major part of this review highlights the surface modified electrodes, utilized for the detection of the most important azo dyes to achieve low detection limit (LOD). METHODS: A thorough literature study was conducted using scopus, science direct and other scientific databases using specific keywords such as toxic azo dyes, electrochemical detection, modified electrodes, LOD etc. The recent references in this field have been included. RESULTS: From the published literature, it is observed that with the growing interests in the field of electrochemical techniques, a lot of importance have been given in the area of modifying the working electrodes. The results unambiguously show that the modified electrodes outperform bare electrodes and offer a lower LOD value. CONCLUSION: According to the literature reports it can be concluded that, compared to other detection methods, electrochemical techniques are much dependable and reproducible. The fabrication of the electrode material with the appropriate modifications is the main factor that influences the sensitivity. Electrochemical sensors can be designed to be more sensitive, more reliable, and less expensive. These sensors can be effectively used by toxicologists to detect trace amounts of harmful dyes in food samples.

Rapid Drug Susceptibility Testing to Preserve Antibiotics.

Antibiotic resistance is a global challenge likely to cost trillions of dollars in excess costs in the health system and more importantly, millions of lives every year. A major driver of resistance is the absence of susceptibility testing at the time a healthcare worker needs to prescribe an antimicrobial. The effect is that many prescriptions are unintentionally wasted and expose mutable organisms to antibiotics increasing the risk of resistance emerging. Often simplistic solutions are applied to this growing issue, such as a naïve drive to increase the speed of drug susceptibility testing. This puts a spotlight on a technological solution and there is a multiplicity of such candidate DST tests in development. Yet, if we do not define the necessary information and the speed at which it needs to be available in the clinical decision-making progress as well as the necessary integration into clinical pathways, then little progress will be made. In this chapter, we place the technological challenge in a clinical and systems context. Further, we will review the landscape of some promising technologies that are emerging and attempt to place them in the clinic where they will have to succeed.

Rapidly and simply detecting Cr (VI) in aqueous media via a diketopyrrolopyrrole-based chemosensor with both high selectivity and low LOD.

BACKGROUND: The high toxicity of hexavalent chromium [Cr (VI)] could not only cause harmful effects on humans, including carcinogenicity, respiratory issues, genetic damage, and skin irritation, but also contaminate drinking water sources, aquatic ecosystems, and soil, impairing the reproductive capacity, growth, and survival of organisms. Due to these harmful effects, detecting toxic Cr (VI) is of great significance. However, the rapid, simple, and efficient detection at a low Cr (VI) concentration is extremely challenging, especially in an acidic condition (existing as HCrO4-) due to its low adsorption free energy. RESULTS: A diketopyrrolopyrrole-based small molecule (DPPT-PhSMe) is designed and characterized to act as a chemosensor, which allows a high selectivity to Cr (VI) at an acidic condition with a low limit of detection to 10-8 M that is two orders of magnitude lower than the cut of limit (1 µM) recommended by World Health Organization (WHO). Mechanism study indicates that the rich sulfur atoms enhance the affinity to HCrO4-. Combining with favorable features of diketopyrrolopyrrole, DPPT-PhSMe not only allows dual-mode detection (colorimetric and spectroscopic) to Cr (VI), but also enables disposable paper-based sensor for naked-eye detection to Cr (VI) from fully aqueous media. The investigation of DPPT-PhSMe chemosensor for the quantification of Cr (VI) in real life samples demonstrates a high reliability and accuracy with an average percentage recovery of 102.1 % ± 4 (n = 3). SIGNIFICANCE: DPPT-PhSMe represents the first diketopyrrolopyrrole-derived chemosensor for efficient detection to toxic Cr (VI), not only providing a targeted solution to the bottleneck of Cr (VI) detection in acidic conditions (existing as HCrO4-) caused by its low adsorption free energy, but also opening a new scenario for simple, selective, and efficient Cr (VI) detection with conjugated dye molecules.

Proof of a LOD Prediction Model with Orthogonal PAT Methods in Continuous Wet Granulation and Drying.

Real-time monitoring of critical quality attributes, such as residual water in granules after drying which can be determined through loss-on-drying (LOD), during wet granulation and drying is essential in continuous manufacturing. Near-infrared (NIR) spectroscopy has been widely used as process analytical technology (PAT) for in-line LOD monitoring. This study aims to develop and apply a model for predicting the LOD based on process parameters. Additionally, the efficacy of an orthogonal PAT approach using NIR and mass balance (MB) for a vibrating fluidized bed dryer (VFBD) is demonstrated. An in-house-built, cost-effective NIR sensor was utilized for measurements and exhibited good correlation compared to standard method via infrared drying. The combination of NIR and MB, as independent methods, has demonstrated their applicability. A good correlation, with a Pearson r above 0.99, was observed for LOD up to 16 % (w/w). The use of an orthogonal PAT method mitigated the risk of false process adaption. In some experiments where the NIR sensor might have been covered by powder and therefore did not measure accurately, LOD monitoring via MB remained feasible. The developed model effectively predicted LOD or process parameters, resulting in an R2 of 0.882 and a RMSE of 0.475 between predicted and measured LOD using the standard method.

[Verification Study of the Detection Method for Unauthorized Genetically Modified Papaya by Combining DNA Polymerases and Real-time PCR Instruments].

In the Japanese official detection method for unauthorized genetically modified (GM) papayas, one of two types of real-time PCR reagents with DNA polymerase (TaqMan Gene Master Mix [TaqMan Gene] or FastGene QPCR Probe Mastermix w/ROX [FastGene]) is primarily used for measurement. In 2022, we conducted a laboratory performance study on the unauthorized GM papaya line PRSV-YK, and the results revealed that high threshold cycle (Cq) values for the PRSV-YK detection test were obtained using TaqMan Gene with the 7500 Fast & 7500 Real-Time PCR System (ABI7500) and QuantStudio 12K Flex (QS12K), indicating the possibility of false negatives. The possibility of similar problems with all unauthorized GM papaya lines detection tests needs to be evaluated. In this study, we performed detection tests on unauthorized GM papaya lines (PRSV-YK, PRSV-SC, and PRSV-HN), the cauliflower mosaic virus 35S promotor (CaM), and a papaya positive control (Chy), and examined how the limits of detection (LOD) for each test are affected by two types of DNA polymerases (TaqMan Gene and FastGene) and three types of real-time PCR instruments (ABI7500, QS12K, and LightCycler 480 Instrument II [LC480]). In the PRSV-YK and PRSV-SC detection tests using ABI7500 and QS12K, measurement with TaqMan Gene showed a higher LOD than FastGene. In this case, an exponential amplification curve was confirmed on the amplification plot; however, the amplification curve did not cross the ΔRn threshold line and the correct Cq value was not obtained with a threshold line=0.2. The other tests (PRSV-HN, CaM, and Chy with ABI7500 and QS12K, and all detection tests with LC480) showed no important differences in the LOD for each test using either DNA polymerase. Therefore, when performing PRSV-YK and PRSV-SC detection tests with the ABI7500 or QS12K, FastGene should be used to avoid false negatives for foods containing GM papaya lines PRSV-YK and PRSV-SC at low mixing levels.

Gold Nanoparticle-Based Plasmonic Detection of Escherichia coli, Salmonella enterica, Campylobacter jejuni, and Listeria monocytogenes from Bovine Fecal Samples.

Current diagnostic methods for detecting foodborne pathogens are time-consuming, require sophisticated equipment, and have a low specificity and sensitivity. Magnetic nanoparticles (MNPs) and plasmonic/colorimetric biosensors like gold nanoparticles (GNPs) are cost-effective, high-throughput, precise, and rapid. This study aimed to validate the use of MNPs and GNPs for the early detection of Escherichia coli O157:H7, Salmonella enterica spp., Campylobacter jejuni, and Listeria monocytogenes in bovine fecal samples. The capture efficiency (CE) of the MNPs was determined by using Salmonella Typhimurium (ATCC_13311) adjusted at an original concentration of 1.5 × 108 CFU/mL. One (1) mL of this bacterial suspension was spiked into bovine fecal suspension (1 g of fecal sample in 9 mL PBS) and serially diluted ten-fold. DNA was extracted from Salmonella Typhimurium to determine the analytical specificity and sensitivity/LOD of the GNPs. The results showed that the CE of the MNPs ranged from 99% to 100% and could capture as little as 1 CFU/mL. The LOD of the GNPs biosensor was 2.9 µg/µL. The GNPs biosensor was also tested on DNA from 38 naturally obtained bovine fecal samples. Out of the 38 fecal samples tested, 81.6% (31/38) were positive for Salmonella enterica spp., 65.8% (25/38) for C. jejuni, 55.3% (21/38) for L. monocytogenes, and 50% (19/38) for E. coli O157:H7. We have demonstrated that MNP and GNP biosensors can detect pathogens or their DNA at low concentrations. Ensuring food safety throughout the supply chain is paramount, given that these pathogens may be present in cattle feces and contaminate beef during slaughter.

Phytochemical investigation and characterisation of methanolic extract of Glycine max seeds using LCMS/MS and in silico studies for wound healing activity.

Soybean is scientifically known as Glycine max. It belongs to the Fabaceae family. It consists of a lot of bioactive phytochemicals like saponin, phenolic acid, flavonoid, sphingolipids and phytosterols. It also owns excellent immune-active effects in the physiological system. Soy and its phytochemicals have been found to have pharmacological properties that include anticancer, antioxidant, anti-hypercholesterolaemic, anti-diabetic, oestrogenic, anti-hyperlipidaemic, anti-inflammatory, anti-obesity, anti-hypertensive, anti-mutagenic, immunomodulatory, anti-osteoporotic, antiviral, hepatoprotective, antimicrobial, goitrogenic anti-skin ageing, wound healing, neuroprotective and anti-photoageing activities. Present study has been designed to set standard pharmacognostical extraction method, complexation of compounds, qualitative evaluation through phytochemical screening, identification by TLC, physicochemical properties, solubility profile, total phenolic, flavonoid content as well as analytical evaluation or characterisation like UV and FT-IR of methanolic extract of G. max. The final observations like physicochemical properties such as total ash value, LOD and pH were recorded. Phytochemical screenings show the presence of flavonoid, alkaloid, saponin, carbohydrate, tannins, protein, gums and mucilage, fixed oils and fats. The results were found significant. Further in silico studies proved creatinine and euparin to be potent wound healing agents.

An experimental and theoretical study on mechanistic insights into urolithin-based ratiometric fluorescent probe for instant quantitative detection of fluoride ions.

Fluoride detection has been playing an important role in chemical, biological, and medicinal field, especially for keeping physical health and resisting environmental pollution. Herein, a urolithin B fluorescent probe has been successfully developed with good sensitivity, selectivity, anti-interference ability. The low limit of detection (LOD) refers to 0.156 µM, and the instant response time to F- is less than 1 s. The probe is suitable for quantitatively and qualitatively ratiometric detection for F- in solution with two distinct emission bands at 425 (blue) and 566 nm (orange), with the coordinate change of CIE from (0.38, 0.41) to (0.22, 0.11). Urolithin B displayed a remarkable ratiometric fluorescence response towards F-. The detection mechanistic was further proposed by NMR and electronic spectroscopic experiments combining with time-dependent density functional theoretical calculation.

Review of Detection Limits for Various Techniques for Bacterial Detection in Food Samples.

Foodborne illnesses can be infectious and dangerous, and most of them are caused by bacteria. Some common food-related bacteria species exist widely in nature and pose a serious threat to both humans and animals; they can cause poisoning, diseases, disabilities and even death. Rapid, reliable and cost-effective methods for bacterial detection are of paramount importance in food safety and environmental monitoring. Polymerase chain reaction (PCR), lateral flow immunochromatographic assay (LFIA) and electrochemical methods have been widely used in food safety and environmental monitoring. In this paper, the recent developments (2013-2023) covering PCR, LFIA and electrochemical methods for various bacterial species (Salmonella, Listeria, Campylobacter, Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli)), considering different food sample types, analytical performances and the reported limit of detection (LOD), are discussed. It was found that the bacteria species and food sample type contributed significantly to the analytical performance and LOD. Detection via LFIA has a higher average LOD (24 CFU/mL) than detection via electrochemical methods (12 CFU/mL) and PCR (6 CFU/mL). Salmonella and E. coli in the Pseudomonadota domain usually have low LODs. LODs are usually lower for detection in fish and eggs. Gold and iron nanoparticles were the most studied in the reported articles for LFIA, and average LODs were 26 CFU/mL and 12 CFU/mL, respectively. The electrochemical method revealed that the average LOD was highest for cyclic voltammetry (CV) at 18 CFU/mL, followed by electrochemical impedance spectroscopy (EIS) at 12 CFU/mL and differential pulse voltammetry (DPV) at 8 CFU/mL. LOD usually decreases when the sample number increases until it remains unchanged. Exponential relations (R2 > 0.95) between LODs of Listeria in milk via LFIA and via the electrochemical method with sample numbers have been obtained. Finally, the review discusses challenges and future perspectives (including the role of nanomaterials/advanced materials) to improve analytical performance for bacterial detection.

Evaluation of Lab-on-a-Disc Technique Performance for Soil-Transmitted Helminth Diagnosis in Animals in Tanzania.

Soil-transmitted helminth (STH) infections are caused by roundworms, hookworms, whipworms, and thread worms. Accurate diagnosis is essential for effective treatment, prevention, and control of these infections. This study evaluates a new diagnostic method called Single-image Parasite Quantification (SIMPAQ), which uses a lab-on-a-disc (LoD) technique to isolate STH eggs into a single imaging zone for digital analysis. The study evaluates the purification performance of the SIMPAQ technique for detecting STH eggs in animal samples. This was a cross-sectional study conducted among 237 pigs and 281 dogs in the Morogoro region in Tanzania. Faecal samples were collected and processed with the LoD technique, as well as flotation and McMaster (McM) methods for comparison purposes. The overall prevalence of STH infections was high as per the LoD technique (74%), followed by McM (65.44%) and flotation (65.04%). Moreover, the overall performance of the LoD technique, using McM as the gold standard, was 93.51% (sensitivity), 60.89% (specificity), 81.91% (PPV), and 83.21% (NPV). The LoD technique exhibited high prevalence, sensitivity, and NPV, which demonstrates its value for STH egg detection and its crucial role in the era of accurate STH diagnosis, promoting proper management of the infection.

Genetic Map Construction Using F2 and RIL/DH Mapping Population.

Genetic mapping is the determination of the position and relative genetic distance between genes or molecular markers in the chromosomes of a particular species. The construction of genetic maps uses data from the genotyping of the mapping population. Among the different mapping populations used, two are relatively common: the F2 and recombinant inbred lines (RILs) obtained as a result of the controlled crossing of genetically diverse parental forms (e.g., inbred lines). Also, the dihaploid (DH) population is often used in plants, but obtaining DHs in different crops, including rye, is very difficult or even impossible. Any molecular marker system can be used for genotyping. Polymorphic markers are used for linkage analysis, differentiating parental forms with segregation in the mapping population, consistent with the appropriate single-gene model. A genetic map is a great source of information on a species and can be an exquisite tool for analyzing important quantitative traits (QT).This chapter presents the procedure of genetic map construction with two different algorithms using the JoinMap5.0 program. First, the Materials section briefly informs about the mapping program, showing how to obtain a mapping population and prepare data for mapping. Finally, the Methods section describes the protocol for the mapping procedure itself.

Imputation of missing values in lipidomic datasets.

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.

Exploring the potential of Mustard (Brassica spp.) seeds through 'Kolhu' traditional method of extraction and novel identification of an anti-cancer dipeptide, Aurantiamide acetate (Asperglaucide) on ultra-performance liquid chromatography-mass spectrometry coupled with quadrupole time-of-flight (UPLC/MS-QToF) analytical platform.

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.

Metabolomics and Lipidomics Analyses Aid Model Classification of Type 2 Diabetes in Non-Human Primates.

Type 2 diabetes (T2D) is a global public health issue characterized by excess weight, abdominal obesity, dyslipidemia, hyperglycemia, and a progressive increase in insulin resistance. Human population studies of T2D development and its effects on systemic metabolism are confounded by many factors that cannot be controlled, complicating the interpretation of results and the identification of early biomarkers. Aged, sedentary, and overweight/obese non-human primates (NHPs) are one of the best animal models to mimic spontaneous T2D development in humans. We sought to identify and distinguish a set of plasma and/or fecal metabolite biomarkers, that have earlier disease onset predictability, and that could be evaluated for their predictability in subsequent T2D studies in human cohorts. In this study, a single plasma and fecal sample was collected from each animal in a colony of 57 healthy and dysmetabolic NHPs and analyzed for metabolomics and lipidomics. The samples were comprehensively analyzed using untargeted and targeted LC/MS/MS. The changes in each animal's disease phenotype were monitored using IVGTT, HbA1c, and other clinical metrics, and correlated with their metabolic profile. The plasma and fecal lipids, as well as bile acid profiles, from Healthy, Dysmetabolic (Dys), and Diabetic (Dia) animals were compared. Following univariate and multivariate analyses, including adjustments for weight, age, and sex, several plasma lipid species were identified to be significantly different between these animal groups. Medium and long-chain plasma phosphatidylcholines (PCs) ranked highest at distinguishing Healthy from Dys animals, whereas plasma triglycerides (TG) primarily distinguished Dia from Dys animals. Random Forest (RF) analysis of fecal bile acids showed a reduction in the secondary bile acid glycoconjugate, GCDCA, in diseased animals (AUC 0.76[0.64, 0.89]). Moreover, metagenomics results revealed several bacterial species, belonging to the genera Roseburia, Ruminococcus, Clostridium, and Streptococcus, to be both significantly enriched in non-healthy animals and associated with secondary bile acid levels. In summary, our results highlight the detection of several elevated circulating plasma PCs and microbial species associated with fecal secondary bile acids in NHP dysmetabolic states. The lipids and metabolites we have identified may help researchers to differentiate individual NHPs more precisely between dysmetabolic and overtly diabetic states. This could help assign animals to study groups that are more likely to respond to potential therapies where a difference in efficacy might be anticipated between early vs. advanced disease.

Enhancing LOD determination in gas chromatography: Validating the Hubaux-Vos method for gas concentration measurement.

The limit of detection (LOD) is a crucial measure in analytical methods, representing the smallest amount of a substance that can be distinguished from background noise. In the realm of gas chromatography (GC), however, determining LOD can be quite subjective, leading to significant variability among researchers. In this study, we validate the Hubaux-Vos method, an International Standards Organization(ISO)-approved approach for determining LOD in gas concentration measurements, using a GC equipped with a discharge ionization detector (DID) and a dynamic dilution system. We employ a gas mixture certified reference material (CRM) of CO, CH4, and CO2 at various concentrations to generate calibration curves for each gas. Subsequently, we estimate the LODs for each gas using the Hubaux-Vos method. Surprisingly, our findings indicate a notable difference between the LODs calculated using the Hubaux-Vos method and those confirmed through experiments. This highlights the importance of critically examining the theoretical foundations of LOD determination. We strongly recommend researchers to scrutinize the principles guiding LOD determination. The method proposed in this study offers an effective way to rigorously validate theoretical approaches for estimating LODs in gas concentration measurements using GC.