Reference Method Research Articles

Validation of the Peel Plate Staphylococcus Aureus (SA) Test for Enumeration of S. aureus in Selected Foods and Non-cultured Dairy Products: AOAC Performance Tested MethodSM 082401.

The microbial testing platform, Peel Plate™, was developed with Baird Parker ingredients for Staphylococcus aureus (SA) specificity. After rehydrating with 1 mL of the diluted food sample, Peel Plate SA is incubated for 24-48 h at 35-37 °C and observed for purple colonies. A validation study was performed to evaluate Peel Plate SA for enumeration of S. aureus in selected foods and non-cultured dairy products for Performance Tested MethodsSM (PTM) certification. Peel Plate SA was evaluated in inclusivity/exclusivity and matrix studies, product consistency, stability, and robustness testing. Non-fat dried milk, frozen raw cod fish, corned beef, frozen raw vegetables, potato salad, vegetable soup, frozen unshelled raw shrimp and baby food (apple, cinnamon, and granola) were evaluated in the matrix studies comparing Peel Plate SA to U.S. and international reference methods. Three levels of contamination along with non-inoculated controls were tested for each matrix. Peel Plate SA detected 49 of 50 S. aureus isolates tested. Of the 38 exclusivity species tested, none were detected. In the matrix studies, the Peel Plate SA results were determined to be equivalent to the reference method results by paired statistical analysis. In an accelerated stability study, the shelf-life of Peel Plate SA was shown to be stable for 12 months. Equivalence was demonstrated between different production lots. Small changes to critical test parameters did not significantly affect the Peel Plate SA results. Peel Plate SA is a ready-to-use method for enumeration of S. aureus in a variety of foods and non-cultured dairy products. As with reference methods, colonies Peel Plate SA colonies should be isolated and confirmed with differentiation tests such as catalase and strong coagulase positive. The data were reviewed by the PTM Program and certification was granted for the Peel Plate SA method PTM 082401.

Evaluation of the diagnostic techniques in the detection of hookworm infestation among school children in Ethiopia: Cross-sectional study design

BackgroundHookworm infestation is an important public health concern especially in regions with poor sanitation and limited resources. In healthcare institutions in Ethiopia, wet mount microscopy with low performance has been used as the sole diagnostic technique. Sensitive diagnostic methods are essential for the proper identification of hookworm infection in national strategies for hookworm prevention and management. Thus, the objective of the article was to evaluate the performance of diagnostic techniques in the detection of hookworm infestation among school children in the Gozamin district, Northwest Ethiopia. MethodsA cross-sectional study with 530 school children was conducted from February to April 2022 in Ethiopia. The study participants were selected by using systematic random sampling technique. Direct wet mount (DWM), Richie’s, Kato-Katz (KK), and spontaneous tube sedimentation (STS) diagnostic techniques were utilized to process the stool samples. The data were entered into the Epi-data version 4.2 and the data was analyzed using SPSS version 25.0. The sensitivity, specificity, predictive values and test efficiency of the test were calculated with respect to the Composite Reference Standard (CRS) as the reference method. The degree of agreement with the methods of diagnosis was assessed by the Kappa value. ResultsThe overall prevalence of hookworm was 34.9 %. The detection rate of STS, Richie’s, KK and DWM techniques in hookworm detection was 30.2 %, 27.0 %, 22.3 % and 15.1 %, respectively. The sensitivity and test efficiency of STS to detect hookworm were 86.5 % and 95.3 %, for Richie’s 77.3 % and 92.1 %, for KK 63.8 % and 87.4 %, for DWM method 43.2 % and 80.2 %, respectively. The agreement of STS, Richie’s, KK and DWM techniques with CRS were perfect (κ = 0.893), perfect (κ = 0.816), substantial (κ = 0.696) and moderate (κ = 0.498), respectively in detecting hookworm parasites. ConclusionThe prevalence of hookworm among school children was high. The STS method is superior to other methods for detecting hookworm infections. The Richie’s technique was more successful in detecting the hookworm parasite than the KK and DWM techniques. It is important to implement the STS technique in routine diagnostic methods and in endemic areas of hookworm infection because it cheaper, easy to perform, and identifies a wide range of parasitic species.

Pressurized liquid extraction of sulfite for quantitation by capillary zone electrophoresis.

Sulfite is an additive used in shrimp processing to prevent discoloration. However, sulfite can cause health issues for sensitive consumers, making its monitoring necessary. Determining sulfite concentrations is complex because the Monier-Williams reference method is laborious and has low analytical throughput. Additionally, new techniques are needed to stabilize sulfite during the extraction process because this analyte undergoes rapid oxidation. A new method involving extraction and derivatization of sulfite with formaldehyde through automated pressurized liquid extraction (PLE), followed by quantitation by capillary zone electrophoresis with diode-array detector in indirect mode, was developed and optimized using multivariate planning. The PLE procedure was compared to another solid-liquid extraction method. The new method successfully stabilized and extracted sulfite from shrimp in few steps with adequate precision (CV<3.8%), producing extracts that were stable for 10 days. Recovery was satisfactory (97%-99%), and the limits of detection (4.6mgkg-1) and quantitation (15.4mgkg-1) were suitable for the intended purpose.

Mastering Snow Analysis: Enhancing Sampling Techniques and Introducing ACF Extraction Method with Applications in Svalbard.

Semi-volatile organic contaminants (SVOCs) are known for their tendency to evaporate from source regions and undergo atmospheric transport to distant areas. Cold condensation intensifies dry deposition, particle deposition, and scavenging by snow and rain, allowing SVOCs to move from the atmosphere into terrestrial and aquatic ecosystems in alpine and polar regions. However, no standardized methods exist for the sampling, laboratory processing, and instrumental analysis of persistent organic pollutants (POPs) in snow. The lack of reference methods makes these steps highly variable and prone to errors. This study critically reviews the existing literature to highlight the key challenges in the sampling phase, aiming to develop a reliable, consistent, and easily reproducible technique. The goal is to simplify this crucial step of the analysis, allowing data to be shared more effectively through standardized methods, minimizing errors. Additionally, an innovative method for laboratory processing is introduced, which uses activated carbon fibers (ACFs) as adsorbents, streamlining the analysis process. The extraction method is applied to analyze polychlorobiphenyls (PCBs) and chlorinated pesticides (α-HCH, γ-HCH, p,p'-DDE, o,p'-DDT, HCB, and PeCB). The entire procedure, from sampling to instrumental analysis, is subsequently tested on snow samples collected on the Svalbard Islands. To validate the efficiency of the new extraction system, quality control measures based on the EPA methods 1668B and 1699 for aqueous methods are employed. This study presents a new, reliable method that covers both sampling and lab analysis, tailored for detecting POPs in snow.

Improving time-efficiency and accuracy in echocardiography: real-time automated measurements of left ventricular global longitudinal strain using deep learning

Abstract Background Accurate quantification of left ventricular (LV) systolic function is fundamental in echocardiography. LV Global Longitudinal Strain (GLS) offers advantages over LV ejection fraction, being more sensitive, reproducible and offering better prognostic value. However, existing semi-automatic methods are time-consuming and heavily operator-dependent. Additionally, poor image quality and foreshortening decrease accuracy and reproducibility of GLS. As a result, these challenges lead to suboptimal efficiency and underutilization of GLS quantification in clinical practice. Purpose Our objective was to develop a deep learning (DL) application for real-time automated measurements of GLS, capable of providing tracking quality and foreshortening feedback during scanning. Subsequently, we aimed to validate the novel method in a prospective cohort study. Methods Deep learning networks were trained to identify apical views, identify timing of end-systole and end-diastole, conduct cardiac segmentation, estimate myocardial motion, assess LV length in each view for foreshortening detection, and present real-time visualization of tracking quality and GLS values for three cardiac cycles to the operator for review (Figure 1). The DL method was validated in a prospective cohort of 40 patients included regardless of image quality. Agreement with manual measurements obtained using semi-automatic software (EchoPAC version 204, GE HealthCare, Horten, Norway) was evaluated. Bland-Altman statistics and Pearson's correlation coefficient were used to evaluate agreement and correlation. Results Feasibility for real-time DL measurements of GLS was 98%, with one patient excluded due to poor image quality. There was good agreement (Bias 0.7%, LoA: -1.6 to 3.1%, figure 2) and excellent correlation (Pearson’s correlation coefficient of 0.93, p&amp;lt;0.001) between the real-time DL application and manual reference measurements for GLS. Using the DL application during scanning resulted in a 58% (95% CI 56%-61%) reduction in time required for scanning and post-processing to obtain GLS values, compared to using the semi-automatic method. Average time consumption was 2 minutes and 16 seconds for the DL method and 5 minutes and 27 seconds for the reference method. Conclusion Using deep learning, real-time fully automated measurement of GLS during scanning is feasible, time-saving, and provides good agreement with reference methods. Real-time measurements also offer the potential to reduce operator-related variability by integrating tools to provide image and tracking quality feedback to the user, ultimately benefiting patients.Application user interfaceAgreement between DL and reference

Cardiac magnetic resonance T1 imaging for the diagnosis of cardiac amyloidosis among patients with symptomatic heart failure

Abstract Background Cardiac amyloidosis (CA) is a significant cause of heart failure in elderly patients. However, specific signs in cardiac imaging are lacking, hence bone scintigraphy in combination with screening for monoclonal protein, or myocardial biopsy is required for the diagnosis. Cardiac magnetic resonance (CMR) imaging with T1 mapping is a promising diagnostic tool, which may allow to differentiate causes of left ventricular (LV) hypertrophy, particularly CA. Purpose The aim of this study was to test the diagnostic accuracy of T1 mapping for the diagnosis of CA in elderly patients with symptomatic heart failure and red flags for CA. Methods We prospectively enrolled 120 patients aged above 60 years with symptomatic heart failure NYHA II-IV, LV ejection fraction ≥ 40%, increased LV wall thickness of ≥ 12 mm end-diastolic on echocardiography, and elevated cardiac biomarkers (N-terminal pro-B-type natriuretic peptide (NT-proBNP) ≥ 1,000 ng/L, high-sensitivity cardiac troponin T (hs-cTnT) ≥ 14 ng/L). All patients underwent standardized quantitative CMR with a 3.0T scanner. 99mTc-DPD bone scintigraphy, blood screening for monoclonal protein, and, where applicable, cardiac biopsy, were performed as reference methods in all patients. Primary endpoint was diagnostic accuracy of native T1 mapping for the diagnosis of CA. Results 112 patients were included in the final analysis. Median age was 81.0 years (interquartile range 74.0–85.0 years), and 45% were female. CA was diagnosed in 38 patients (34%), of which 32 suffered from a Transthyretin (ATTR) and 6 patients from light chain (AL) amyloidosis. The areas under the receiver operating characteristic curves for native T1 were 0.713, 0.772, 0.836 for global, septal short-axis (SAX), and septal 4-chamber (4Ch) view measurements. The corresponding value of extracellular volume fraction (ECV) was 0.904 (Figure 1). Based on these results, we developed a new diagnostic algorithm for the diagnosis of CA including T1 septal 4Ch and ECV, with a sensitivity and positive predictive value of both 92.9% and a specificity and negative predictive value of 95.8% (Figure 2). Thereby, contrast application can be avoided in 33% of patients. A definite diagnosis could be provided in 81%. Conclusion CMR with T1 imaging provides a high diagnostic accuracy to diagnose CA in patients with symptomatic heart failure at risk for CA. These data may help to identify underlying causes in heart failure which require specific treatment. An earlier diagnosis of CA may improve outcome of these patients.Figure 1Figure 2

Machine learning methods for propensity and disease risk score estimation in high-dimensional data: a plasmode simulation and real-world data cohort analysis.

Machine learning (ML) methods are promising and scalable alternatives for propensity score (PS) estimation, but their comparative performance in disease risk score (DRS) estimation remains unexplored. We used real-world data comparing antihypertensive users to non-users with 69 negative control outcomes, and plasmode simulations to study the performance of ML methods in PS and DRS estimation. We conducted a cohort study using UK primary care records. Further, we conducted a plasmode simulation with synthetic treatment and outcome mimicking empirical data distributions. We compared four PS and DRS estimation methods: 1. Reference: Logistic regression including clinically chosen confounders. 2. Logistic regression with L1 regularisation (LASSO). 3. Multi-layer perceptron (MLP). 4. Extreme Gradient Boosting (XgBoost). Covariate balance, coverage of the null effect of negative control outcomes (real-world data) and bias based on the absolute difference between observed and true effects (for plasmode) were estimated. 632,201 antihypertensive users and nonusers were included. ML methods outperformed the reference method for PS estimation in some scenarios, both in terms of covariate balance and coverage/bias. Specifically, XgBoost achieved the best performance. DRS-based methods performed worse than PS in all tested scenarios. We found that ML methods could be reliable alternatives for PS estimation. ML-based DRS methods performed worse than PS ones, likely given the rarity of outcomes.

Monitoring of the Analytical Performance of Four Different Blood Glucose Monitoring Systems: A Post-market Performance Follow-Up Study.

A sizeable minority of commercially available blood glucose monitoring (BGM) systems fail to satisfy regulatory accuracy requirements, such as ISO 15197:2013, after approval. This study assessed whether the BGMs tested could consistently meet these ISO requirements by investigating their accuracy in a non-standardized setting. In this 18-month post-market performance study, using the ISO criteria, healthcare professionals tested the accuracy of four CE-marked BGM systems (Roche Diabetes Care, Mannheim, Germany) on European adults with diabetes mellitus. ISOcriteria included 95% of blood glucose (BG) values being within ± 15mg/dl of a reference measurement for BG < 100mg/dl or ± 15% for BG ≥ 100mg/dl and, in the Parkes Consensus Error grid for type 1 diabetes comparing capillary BGM measurements versus reference method, 99% of BG values falling within zone A (no effect on clinical action or outcome) and zone B (altered clinical action with little or no effect on clinical outcome). BGM readings were obtained from 1650 participants, and the number of readings per BGM system was between 1712 and 2376. The percentage of BGM readings that fell within ISO 15197:2013 limits ranged from 99.4 to 99.9%. For all meter types, 100% of data points fell within zone A or zone B, and most data points for each meter (≥ 99.9%) were in zone A. All four CE-marked BGM models showed results within the accuracy limits defined by ISO 15197 in a non-standardized setting and thus consistently met regulatory accuracy requirements.

Assessing the Efficacy of Chlorhexidine in Combating Most Important Causative Agents of Fungal Keratitis: An in Vitro Comparative Study With Seven Antifungal Agents

Purpose Fungal keratitis (FK) is a difficult condition to treat, particularly in underdeveloped nations. The study aimed to compare the in vitro activity of chlorhexidine (CHX) and seven antifungal agents against a collection of fungi recovered from FK patients. Methods Seventy-three fungi were collected from patients with FK included in study. The antifungal agents tested were fluconazole, voriconazole, posaconazole, miconazole, natamycin, amphotericin B, and caspofungin. The concentration range for CHX was 1–1024 μg/mL. Assessments of antifungal susceptibility were conducted using the EUCAST broth microdilution reference method. Results The findings demonstrated the beneficial in vitro inhibition of filamentous and yeast fungi by CHX. CHX demonstrated efficacy against Fusarium spp., Aspergillus spp., Candida spp., S. apiospermum and dematiceous fungi at concentrations of 4–64, 32–64, 4–32, 8, and 4–16 µg/mL respectively. The median MICs and MIC distributions of CHX showed no significant differences among the evaluated spp. (p > 0.05). The most effective antifungal drug was posaconazole, which was followed by voriconazole, caspofungin, and amphotericin B. Conclusion In situations where access to a range of antifungal medications and microbiological facilities is limited, CHX should be further investigated as a potential treatment for FK. It might be able to treat the condition as an inexpensive topical treatment.

An equation for estimating low-density lipoprotein-triglyceride content and its use for cardiovascular disease risk stratification.

The triglyceride (TG) content of low-density lipoprotein (LDL-TG) has been shown to be more predictive of atherosclerotic cardiovascular disease (ASCVD) events than the cholesterol content of LDL (LDL-C). The goal of our study was to develop an equation for estimating LDL-TG (eLDL-TG) based on the standard lipid panel and to compare it to estimated LDL-C as an ASCVD risk biomarker. Using least-square regression analysis, the following eLDL-TG equation was developed: . LDL-TG was measured by the β-quantification (BQ) reference method (N = 40,202). LDL-C was calculated by the Sampson-NIH equation. The association of LDL-C and eLDL-TG with ASCVD risk markers was performed in the National Heart and Nutrition Examination Survey (NHANES) (N = 37,053) and with ASCVD events in a primary prevention cohort from the UK Biobank (UKB) (N = 429,367) and the Atherosclerosis Risk in Communities (ARIC) study (N = 14,632). eLDL-TG showed better ASCVD risk stratification of UKB participants than LDL-C (Wilcoxon Chi-Square: 2,099.6 vs. 418.7, respectively). Receiving-operating characteristics analysis revealed that eLDL-TG had a stronger association with ASCVD events than LDL-C (AUC: 0.596 vs. 0.542, respectively) and other conventional lipid markers. Similar findings were found in ARIC. Discordance analysis in UKB showed that the group with low LDL-C/high eLDL-TG had a similar risk as the high LDL-C/high eLDL-TG group. Furthermore, these same two groups with the highest eLDL-TG levels and the highest ASCVD event rate also had higher mean levels of systolic blood pressure, Body Mass Index, hemoglobin A1C, and C-reactive protein than the two lower eLDL-TG groups. Using eLDL-TG > 44.6 mg/dl (80th percentile) as a cut-point leads to a hazard ratio of 1.32 (95% CI, 1.29-1.36) for ASCVD events, which remained significant after adjustment for LDL-C and apoB. Furthemore, using eLDL-TG as a risk-enhancer test leads to reclassification of 50% more high-risk individuals than current lipid-enhancer test rules. Like LDL-C, LDL-TG can also be calculated from the results of the standard lipid panel. Compared to estimated LDL-C, eLDL-TG was a better risk marker for primary prevention and hence could improve initial ASCVD risk stratification.

Performance Characteristics of the Quantitative Method for Staphylococcus aureus in Food Products Correspond to ISO 16140-3: 2021

Staphylococcus aureus is a pathogenic bacterium that poses significant health risks when present in food products. High levels of Staphylococcus aureus in food can indicate poor hygiene and handling practices during food production, processing, or storage. In order to maintain food safety and quality, verification of the quantitative method of Staphylococcus aureus is very important. Method verification represents a crucial stage in guaranteeing that all employed procedures conform to the necessary criteria for dependable and precise data. Following the guidelines established in ISO 16140-3:2021, method verification is accomplished through the calculation of the Intralaboratory Reproducibility Standard Deviation (SIR) for implementation validation and the eBias value for verifying the suitability of the method for assessing specific food items. This research was conducted with the objective of confirming the ISO 6888-1:2021 as the designated reference method for quantifying Staphylococcus aureus in food products. For the purpose of confirming the implementation of the method, Cheese was utilized as the test food item. In the context of verifying the method's applicability to different food products, a range of items including condensed milk, margarine, baby porridge, cassava chips and ready-to-eat sausage were examined as challenging foods. Every chosen food item was artificially contaminated with Staphylococcus aureus WDCM 00034. The SIR value obtained was 0.04 ≤ 2× 0.11 (the lowest mean of SR value from ISO 6888-1:2021) which indicated that the National Quality Control Laboratory of Drug and Food (NQCLDF), Indonesian FDA was able to implement the method very well. In addition, the eBias value for all types of food tested was below 0.5log10, which showed that the quantitative method for coagulase-positive Staphylococci (Staphylococcus aureus and other types) could be applied in the NQCLDF laboratory for the extensive scope of food.

A Multi-Isotopic Chemometric Approach for Tracing Hazelnut Origins.

High-value products, such as hazelnuts, are particularly vulnerable to fraud due to their price dependence on geographical origin. Guaranteeing hazelnuts' authenticity is essential for consumer trust and safety. Stable isotope analysis has become a reference method for origin authentication as it is reliable, robust, and easily transferable across laboratories. However, multiple isotopic markers coupled with chemometric techniques are often needed to authenticate food provenance accurately. In this study, we focused on assessing the potential of bulk δ18O, along with δ2H and δ13C of the main fatty acids, as hazelnut-origin authenticity markers. PLS-DA classification models were developed to differentiate samples (n = 207) according to their region of origin. This multi-isotopic approach provided promising external validation results, achieving a 94% global correct classification rate in discriminating hazelnuts from regions with distinct geographical and environmental conditions. This study lays the groundwork for further model development and evaluation across additional production areas and harvest years.

Comparative Analysis of Quantitative Methods for Campylobacter spp. Quantification: ISO 10272-2:2017, Tempo® and Real-Time PCR in Refrigerated and Frozen Turkey Cuts.

New technologies for more effective microbiological assays are being adopted by the food industry to intervene more rapidly in its production chain. The aim of this study was to evaluate the alternative methods of TEMPO® CAM and real-time PCR (rtPCR) Biotecon® in comparison with the ISO 10272-2:2017 reference method for Campylobacter spp. quantification in turkey meat, aiming to validate a quick and easily replicable method in these meat matrices. A total of 416 samples were analyzed over a one-year period. The TEMPO® methodology showed inadequate performance with a significant difference (p < 0.05) compared with the reference methodology; therefore, its use was not recommended for turkey meat matrices. However, the performance of the rtPCR Biotecon® methodology showed adequate performance with no significant difference (p > 0.05), and its use was recommended in turkey meat matrices. The study was limited to exclusive research in turkey meat matrices, and expansion of the research into other matrices is recommended to verify whether the behavior of alternative methodologies is similar. The findings of this study illustrate the necessity for a thorough and comprehensive evaluation during the implementation of alternative methodologies that may potentially supplant conventional approaches.

Comparison of Vancomycin AUC24 Calculation Methods for Neonates and Infants.

For neonates and infants receiving intermittent vancomycin infusions, the area under the concentration-timecurve during 24 h (AUC24) is often estimated with Bayesian forecasting using one or more measured vancomycin concentrations. When practical peak and trough concentrations are measured at steady state, AUC24 can also be calculated with first-order steady-state equations for a one-compartment model (Sawchuk-Zaske method), but previously this method has been applied only for adults. The objective of this studywas to compare AUC24 values obtained with the Sawchuk-Zaske method and two Bayesian models. AUC24 values were estimated retrospectively for 18 neonates and infants with steady-state peak and trough concentrations using traditional compartmental analysis with a one-compartment model (reference method), the Sawchuk-Zaske method, and Bayesian forecasting with two previously published models. In Bayesian forecasting, both original and modified residual error models were used. In the modified models, the residual error was reduced by setting the additive residual error to zero and the proportional error to 15%. AUC24 estimates obtained with the Sawchuk-Zaske method differed -2.7 to 0.9% from the reference method. When both peak and trough concentrations were used in Bayesian forecasting, 61% and 33% of AUC24 estimates obtained with two original models differed less than 15% from the reference method, and these fractions increased to 83% and 72% with the modified models, respectively. When practical peak and trough concentrations are measured at steady state, the simple Sawchuk-Zaske method is very useful for AUC24 estimation in neonates and infants. In Bayesian forecasting, the reduced residual error model can be used to improve the model fit.

Signal Acquisition and Algorithm Design for Bioimpedance-Based Heart Rate Estimation from the Wrist

Background: Heart rate (HR) is a critical biomarker that provides insights into overall health, stress levels, and the autonomic nervous system. Pulse wave signals contain valuable information about the cardiovascular system and heart status. However, signal acquisition in wearables poses challenges, particularly when using electrical sensors, due to factors like the distance from the heart, body movement, and suboptimal electrode placement. Methods: Electrical bioimpedance (EBI) measurements using bipolar and tetrapolar electrode systems were employed for pulse wave signal acquisition from the wrist in both perpendicular and distal configurations. Signal preprocessing techniques, including baseline removal via Hankel matrix methods, normalization, cross-correlation, and peak detection, were applied to improve signal quality. This study describes the combination of sensor-level signal acquisition and processing for accurate wearable HR estimation. Results: The bipolar system was shown to produce larger ΔZ(t), while the tetrapolar system demonstrated higher sensitivity. Distal placement of the electrodes yielded greater ΔZ(t) (up to 0.231 Ω) when targeting both wrist arteries. Bandpass filtering resulted in a better signal-to-noise ratio (SNR), achieving 3.6 dB for the best bipolar setup and 4.8 dB for the tetrapolar setup, compared to 2.6 and 3.3 dB SNR, respectively, with the Savitzky–Golay filter. The custom HR estimation algorithm presented in this paper demonstrated improved accuracy over a reference method, achieving an average error of 1.8 beats per minute for the best bipolar setup, with a mean absolute percentage error (MAPE) of 8%. Conclusions: The analysis supports the feasibility of using bipolar electrode setups on the wrist and highlights the importance of electrode positioning relative to the arteries. The proposed signal processing method, featuring a preprocessing pipeline and HR estimation algorithm, provides a proof-of-concept demonstration for HR estimation from EBI signals acquired at the wrist.

Development and validation of a new anthropometric equation to predict fat mass percentage in a white Spanish population.

(1) To develop a new regression equation for estimating fat mass percentage (%FM) from anthropometric measurements in a heterogeneous Caucasian population and (2) to compare it with the Durnin and Womersley equation, which is one of the most used anthropometric equations for fat mass assessment. Body mass, stature, and four skinfolds (biceps, triceps, subscapular, and supracrestal) were assessed by an accredited anthropometrist, according to the International Society for Advancement in Kinanthropometry. Participants completed a dual-energy X-ray absorptiometry (DXA) whole-body scan to determine their %FM. A new anthropometric equation to estimate %FM was developed using multiple forward regression analyses with DXA as the reference method. Tests for the accuracy of the different equations included mean differences, coefficient of determination, standard error of the estimate (SEE), concordance correlation coefficient (CCC), and Bland-Altman plots. Spain. Two hundred and eighteen healthy Caucasian participants aged 18-65 years participated in this cross-sectional study. Our proposed equation explained 89.9% of the variance in the DXA-derived %FM, with a low random error (SEE = 3.00%), a very strong agreement (CCC = 0.93), no fixed or proportional bias, and a relatively low individual variability (5.84%). However, the Durnin and Womersley equations obtained a fixed bias of -3.65% when compared to DXA and a greater individual variability (6.74%). The proposed equation can accurately estimate %FM in a heterogeneous Caucasian population with a wide age range (18-65 years). Additionally, the Durnin and Womersley equation was inadequate when applied to our participants.

Modified Easley formula for elastic critical global shear buckling stress of corrugated steel webs considering real boundary conditions

The real juncture between corrugated steel webs (CSWs) and flanges follows a multi-segmented line, distinct from that of flat steel webs. Classic methods may yield significant deviations in predicting the elastic global shear buckling capacity of CSWs of various scales due to their failure to consider real boundary constraints. Therefore, a universally applicable formula for calculating the elastic critical global shear buckling stress of CSWs, which accounts for real boundary conditions, is proposed. This formula is pertinent to both large-scale engineering CSWs and small-scale testing CSWs. This study commenced with a comprehensive reassessment of the elastic global shear buckling calculation method. Subsequently, the influence of geometric parameter ratios on the elastic critical global buckling stress was examined. The primary parameter was identified and employed to improve the global buckling coefficient. The proposed calculation method was validated using different corrugation configurations, including 1000-type, 1200-type, 1600-type, 1800-type, and 2000-type CSWs, as well as other CSWs used in experimental settings. These results were compared with those obtained from other reference methods. Findings indicate that the accuracy of the classic theoretical method is affected by variations in both boundary conditions and geometric dimensions due to the constraint effect of real boundary conditions. Under the real boundary conditions, the elastic critical global shear buckling stress of CSWs with simply supported boundary conditions is close to that of CSWs with consolidated boundary conditions. The ratio of web height to corrugation depth primarily affects the elastic global shear buckling capacity, which decreases as the ratio increases. The Easley formula can be modified based on the web height to corrugation depth ratio. Comparisons of numerous numerical and theoretical results reveal that the proposed calculation method exhibits commendable computational precision. In comparison to alternative formulas, the proposed method demonstrates enhanced consistency for calculating CSWs with varying geometric dimensions and boundary conditions, thereby demonstrating its favorable applicability. These conclusions provide valuable reference for the shear design of CSWs.

Development of a Quadruplex RT-qPCR for the Detection of Feline Kobuvirus, Feline Astrovirus, Feline Bufavirus, and Feline Rotavirus

Feline kobuvirus (FeKoV), feline astrovirus (FeAstV), feline bufavirus (FeBuV), and feline rotavirus (FRV) are important pathogens for gastroenteritis, which is characterized by vomiting, diarrhea, and dehydration. Four pairs of primers and probes were designed to target the FeKoV VP1, FeAstV ORF2, FeBuV VP2, and FRV NSP4 genes, and a quadruplex real-time quantitative RT-PCR (RT-qPCR) assay capable of the simultaneous detection of four feline enteroviruses was developed after optimization of reaction conditions. The established quadruplex RT-qPCR assay showed high specificity, sensitivity, and reproducibility. The assay could detect and discriminate FeKoV, FeAstV, FeBuV, and FRV, but not other feline-related pathogens. The limits of detection (LODs) of FeKoV, FeAstV, FeBuV, and FRV were 109.761, 115.834, 125.481, and 113.875 copies/reaction, respectively. The intra- and inter-assay coefficients of variation (CV) were 0.15–1.61% and 0.15–1.59%, respectively. In all, 1869 clinical samples from Guangxi province in Southern China were tested using the developed assay, and the positivity rates of FeKoV, FeAstV, FeBuV, and FRV were 1.93%, 9.36%, 0.32%, and 0.75%, respectively. These samples were also tested using reference assays, and the coincidence rates of the results between the developed and reference methods were 99.63% (FeKoV), 98.72% (FeAstV), 100% (FeBuV), and 100% (FRV), respectively. The results indicated that the developed assay could provide a new detection method for these four viruses associated with feline gastroenteritis.

Comparison of two commercial broth microdilution panels for multidrug-resistant Gram-negative bacteria: Thermo Scientific™ Sensititre DKMGN vs. Beckman Coulter MicroScan NMDRM1.

Antimicrobial susceptibility testing (AST) using broth microdilution (BMD) is usually the reference method to obtain accurate minimum inhibitory concentrations and optimally manage infections with resistant organisms. Several commercial dry BMD are available for AST in clinical laboratories. Two commercial BMD panels for testing of multidrug-resistant Gram-negative bacteria were compared: the Thermo Scientific™ Sensititre DKMGN and the Beckman Coulter NMDRM1, for 17 antimicrobial agents. A total of 207 isolates were tested: three ATCC strains and one NCTC strain, six quality control strains from the Belgian National Antimicrobial Committee, and 197 clinical isolates, including carbapenem-resistant Enterobacterales, Pseudomonas aeruginosa, and Acinetobacter baumannii. The European Committee on Antimicrobial Susceptibility Testing (EUCAST) 2023 breakpoints version 13.1 were used to assign susceptibility categories. Overall, the categorical agreement (CA) and essential agreement (EA) were both above 90%, but several useful antibiotics for the treatment of multi-resistant organisms showed CA and EA under 90%, that is, meropenem, imipenem, and colistin for Enterobacterales and meropenem and colistin for P. aeruginosa. For Enterobacterales, the NMDRM1 panel showed a significantly higher resistance rate for meropenem, imipenem, amikacin, and colistin. For carbapenems, the minimal inhibitory concentrations (MICs) were underestimated by the DKMGN panel, as already pointed out by a warning on the EUCAST website. To better assess carbapenem susceptibility in carbapenem-resistant organisms, the DKMGN panel now requires the use of a higher inoculum in the insert kit. However, for a given isolate whose susceptibility to carbapenems is not known, there is a risk of underestimating the MIC values. Our results show that colistin testing remains a challenge, highlighting the urgent need for the development of more accurate commercial methods. The use of a single commercial method cannot guarantee good precision in the determination of the MIC value for colistin.

Rapid determination of fat content: Advanced spectroscopic methods across diverse fish species

The rapid estimation of fat content using spectroscopic-based sensors, irrespective of fish species (salmon, trout, sea bass, sea bream, tuna, cod, and mackerel), was primarily investigated in the present study. The fat content and fatty acid (FA) composition was quantified with reference methods. Fourier-Transform Infrared (FTIR) and Fourier-Transform Near-Infrared (FT-NIR) spectroscopy, along with multispectral imaging (MSI) instruments (both benchtop and portable), were evaluated for their ability to rapidly predict fat content in ground samples using data analysis. The performance of the PLS-R models was evaluated according to root mean square error (RMSE), coefficient of determination (R2) and residual prediction deviation (RPD). Also fish were classified as fat/low-fat and low/medium/high-fat using partial least squares discriminant analysis (PLS-DA). All fish species exhibited a consistent pattern of unsaturated fatty acids (UNFA) > monounsaturated fatty acids (MUFA) > polyunsaturated fatty acids (PUFA) > saturated fatty acids (SFA) and the range of fat content was from 22.8 (salmon) to 0.02 (cod), expressed in g/100 g of sample based on the reference methods. In terms of fat content prediction using rapid sensors the best performance indices of the test set were obtained from the benchtop-MSI (RMSE = 1.475, R2 = 0.847, RPD = 2.581) and FT-NIR (RMSE = 1.638, R2 = 0.855, RPD = 2.651) instruments, while FTIR and portable-MSI had scores of RMSE = 1.874, R2 = 0.815, RPD = 2.309 and RMSE = 1.737, R2 = 0.786, RPD = 2.191, respectively. All sensors discriminated fat from low-fat samples (accuracy = 100%). For low/medium/high fat the best results were achieved by benchtop-MSI (accuracy = 94.12%), followed by portable-MSI (accuracy = 88.24%) and FTIR (accuracy = 84.21%). Results were less satisfactory for the FT-NIR method (accuracy = 68.75%). This study demonstrates that vibrational and multispectral imaging spectroscopies, when coupled with data analysis, have potential to provide information about the nutritional quality (e.g., fat content) independent of the fish species. Such insights could contribute to the automation and potential digitalization of processes within the fields of food nutrition and the seafood industry.