Determining the Presence and Size of Shoulder Lesions in Sows Using Computer Vision.

Shoulder sores predominantly arise in breeding sows and often result in untimely culling. Reported prevalence rates vary significantly, spanning between 5% and 50% depending upon the type of crate flooring inside a farm, the animal's body condition, or an existing injury that causes lameness. These lesions represent not only a welfare concern but also have an economic impact due to the labor needed for treatment and medication. The objective of this study was to evaluate the use of computer vision techniques in detecting and determining the size of shoulder lesions. A Microsoft Kinect V2 camera captured the top-down depth and RGB images of sows in farrowing crates. The RGB images were collected at a resolution of 1920 × 1080. To ensure the best view of the lesions, images were selected with sows lying on their right and left sides with all legs extended. A total of 824 RGB images from 70 sows with lesions at various stages of development were identified and annotated. Three deep learning-based object detection models, YOLOv5, YOLOv8, and Faster-RCNN, pre-trained with the COCO and ImageNet datasets, were implemented to localize the lesion area. YOLOv5 was the best predictor as it was able to detect lesions with an mAP@0.5 of 0.92. To estimate the lesion area, lesion pixel segmentation was carried out on the localized region using traditional image processing techniques like Otsu's binarization and adaptive thresholding alongside DL-based segmentation models based on U-Net architecture. In conclusion, this study demonstrates the potential of computer vision techniques in effectively detecting and assessing the size of shoulder lesions in breeding sows, providing a promising avenue for improving sow welfare and reducing economic losses.

Raman spectroscopy coupled to high-resolution continuum source flame molecular absorption spectrometry for sequential determination of nitrogen species in fertilizers.

Raman spectroscopy (RS) was used to identify and quantify different nitrogen species in fertilizers. This is a fast and inexpensive method that requires no extensive sample preparation. Urea and nitrate were determined at 1000 and 1045 cm-1, respectively. Calibration plots obtained for these analytes showed adequate linearity, with regression coefficients (r) of 0.9989 and 0.9976, respectively. Ammonium was determined by difference after total N determination by high-resolution continuum source flame molecular absorption spectrometry (HR-CS FMAS), which provided a calibration plot with r = 0.9960. The inline coupling of RS and HR-CS FMAS allowed for a fast sequential determination of ammonium, nitrate, and urea, with limits of detection of 0.03 mg/L ammonium, 0.03 mg/L nitrate, and 0.01 mg/L urea. Relative standard deviations were ≤ 11 %, and the external standard calibration method provided accurate results for all analytes determined in certified reference materials, raw materials, and commercial samples of fertilizers. For comparison purposes, all samples were also analyzed by traditional Kjeldahl method. The RS HR-CS FMAS method was further validated by addition and recovery experiments, which provided recoveries in the 93 - 113 % range.

Multi-internal standard calibration applied to inductively coupled plasma optical emission spectrometry.

Several species are simultaneously used for internal standardization to improve accuracy in inductively coupled plasma optical emission spectrometry (ICP-OES). In multi-internal standard calibration (MISC), signal ratios between the analyte and each of several internal standard species are used for calibration. A single calibration solution is required, and the MISC graph is built with intensity ratios calculated with analytical signals recorded for the sample (IA,sam) on the y-axis, while those recorded for the calibration standard (IA,std) are plot on the x-axis (i.e. IA,sam/IIS(i)vs. IA,std/IIS(i), where IIS(i) represents the signal intensity for a given internal standard species). Nine analytes (As, Cd, Cr, Cu, Fe, Mg, Mn, Pb and Zn), and two sets of internal standard species (i.e. Bi, Ge, In, Rh, Sc, Te, Tl and Y in solution, or eighteen emission lines from plasma naturally occurring Ar) were evaluated in this proof-of-concept study. The MISC method's efficiency was evaluated by analyte addition and recovery experiments and by analyzing two certified reference materials. Figures of merit for MISC (limit of detection, repeatability and trueness) were comparable to those obtained for the traditional external standard calibration (EC) and internal standard (IS) methods. Different from IS, MISC requires no time-consuming study to identify an ideal internal standard species, and signal biases are minimized by an averaged, more encompassing internal standardization effect.

Evaluation of different approaches to applying the standard additions calibration method.

The extrapolation approach, traditionally used with standard additions (SA), is compared with the alternative strategies of interpolation, reversed-axis, and normalization. The interpolation approach is based on employing twice the analytical signal recorded for the sample (ysam) to determine an unknown analyte concentration. In the reversed-axis strategy, x- and y-axes are swapped when building the SA calibration plot to facilitate uncertainty estimation. A new strategy, based on signal normalization using ysam, is also described and compared to the other approaches. Results from 3 instrumental methods, 396 sample replicates, 16 analytes, and 2 certified reference materials are included in this study. For most applications, all four SA approaches provide statistically similar trueness and precision. However, extrapolation and reversed-axis provide more consistent values (within narrower ranges) than the other strategies when employing inductively coupled plasma optical emission spectrometry (ICP OES). On the other hand, normalization provides better trueness for the less robust method of microwave-induced plasma OES (MIP OES), as it is capable of minimizing systematic errors associated with different points of the calibration curve. Normalization is particularly useful for quickly processing data, without the need for inspecting each individual calibration plot to identify outlying points. Reversed-axis and normalization are the most adequate approaches for SA applications involving MIP OES and ICP-based methods. In addition to providing similar accuracies to the traditional extrapolation approach, these strategies present the advantage of a simple uncertainty estimation, which can be easily calculated using commonly available software such as Microsoft Excel and R.

Machine learning tools to estimate the severity of matrix effects and predict analyte recovery in inductively coupled plasma optical emission spectrometry.

Supervised and unsupervised machine learning methods are used to evaluate matrix effects caused by carbon and easily ionizable elements (EIEs) on analytical signals of inductively coupled plasma optical emission spectrometry (ICP OES). A simple experimental approach was used to produce a series of synthetic solutions with varying levels of matrix complexity. Analytical lines (n = 29), with total line energies (Esum) in the 5.0-15.5 eV range, and non-analyte signals (n = 24) were simultaneously monitored throughout the study. Labeled (supervised learning) and unlabeled (unsupervised learning) data on normalized non-analyte signals (from plasma species) were used to train machine learning models to characterize matrix effect severity and predict analyte recoveries. Dimension reduction techniques, including principal component analysis, uniform manifold approximation and projection and t-distributed stochastic neighborhood embedding, were able to provide visual and quantitative representations that correlated well with observed matrix effects on low-energy atomic and high-energy ionic emission lines. Predictive models, including partial least squares regression and generalized linear models fit with the elastic net penalty, were tuned to estimate analyte recovery error when using the external standard calibration method (EC). The best predictive results were found for high-energy ionic analytical lines, e.g. Zn II 202.548 nm (Esum = 15.5 eV), with accuracy and R2 of 0.970 and 0.856, respectively. Two certified reference materials (CRMs) were used for method validation. The strategy described here may be used for flagging compromising matrix effects, and complement method validation based on addition/recovery experiments and CRMs analyses. Because the data analysis workflows feature signals from plasma-based species, there is potential for developing instrument software capable of alerting users in real time (i.e. before data processing) of inaccurate results when using EC.

Survey of Lead in Drinking Water from Schools and Child Care Centers Operating as Public Water Suppliers in North Carolina, USA: Implications for Future Legislation.

Few schools and child care facilities test for Pb in their drinking water. Reviewing the United States Environmental Protection Agency Lead and Copper rule data can contribute to guiding future legislation on Pb testing. This work aims to (i) identify variations in Pb levels in North Carolina school and child care drinking water by building age, (ii) evaluate the effect of corrosion control measures on reducing these levels, and (iii) evaluate the adequacy of Pb reporting limits according to modern instrumentation. To achieve these objectives, information on 26,608 water samples collected in 206 North Carolina child centers between 1991 and 2019 has been analyzed. Lead concentrations were above a recently proposed 5 µg/L trigger level in 12.3%, 10.4%, 7.5%, and 0.9% of samples from pre-1987, 1987-1990, 1991-2013, and post-2013 buildings, respectively. Thus, recently proposed legislation requiring testing only for pre-1987 (or pre-1991) buildings will fail to identify all centers at risk. The odds that a greater than 5 µg/L Pb level is detected has been decreasing over the years, with a faster decreasing rate for buildings reporting corrosion control. Over 15% of samples report a method detection limit of 5 µg/L. For accurate results, future legislation should require sub-µg/L detection limits, which are easily achievable with commonly available instrumentation.

Automated matrix-matching calibration using standard dilution analysis with two internal standards and a simple three-port mixing chamber.

Simple data processing and unattended calibration are achieved in automated standard dilution analysis (aSDA) using two internal standards and an inline lab-made mixing chamber furnished from a common plastic syringe. Only two calibration solutions are required per sample, which minimizes reagent consumption and waste generation. Solution 1 contains 50% sample and 50% of a standard containing the analytes and internal standard 1 (IS1). Solution 2 has 50% sample and 50% of a blank containing internal standard 2 (IS2). The concentration of analyte in the sample is calculated from (i) the slope and intercept of an analyte vs. IS1 plot, (ii) the concentration of analyte in the standard added to Solution 1, and (iii) the intercept of a second plot with IS1vs. IS2. The aSDA method was used to determine Cd, Co, Cr, Cu, Pb and Zn in tap and creek water, beer, cola soft drink, mouthwash, cough syrup and cachaça by ICP OES. Addition/recovery experiments involving these same samples and other challenging matrices (i.e. 40% v/v HNO3, and 1% m/v Na, Ca or C) were performed to evaluate the method's accuracy. The results were compared with values obtained with external standard calibration (EC), internal standardization (IS) and standard additions (SA). Considering all samples and analytes evaluated, aSDA provided the best accuracy, with an average absolute error (ε‾=|analytepercentrecovery-100|) of 4% (EC, IS and SA had 13%, 9% and 7% errors, respectively). The aSDA strategy is a simple and inexpensive alternative to traditional methods. It has great potential for broad implementation with existing ICP OES instrumentation, as it requires little modification to systems already in place in routine laboratories.

Effects of platinum-based anticancer drugs on the trace element profile of liver and kidney tissue from mice.

BACKGROUND: Platinum-based anticancer drugs are relatively successful chemotherapeutic agents, which can cause significant elemental changes in key organs and are known for undesirable side effects, such as nephrotoxicity (damage to the kidneys). OBJECTIVES AND METHODS: Inductively coupled plasma mass spectrometry (ICP-MS) and traditional statistical tools such as two-sample Student's t-test and Pearson's correlation analysis are used to evaluate the effects of different investigational Pt-based anticancer drugs on the elemental constitution of kidneys and liver of mice. Principal component analysis is used to uncover relationships in element concentration and potential correlations between those and clinical effects. Random forest importance is used to identify elements most associated with the drug's maximum tolerated doses (MTDs). RESULTS: Strong negative correlations between Pt and both Cu (-0.814) and Zn (-0.784) in kidneys were observed for one of the Pt-acridine anticancer agents evaluated (Drug C). Strong positive correlations were observed between Cu in both kidneys (0.834) and liver (0.756) with Zn in liver for the same compound. Cisplatin administration correlates to higher concentrations of Ca, Cu, Rb and Zn in liver. Calcium and Mo in kidneys and Pt and Zn in liver are the features most associated with MTDs. CONCLUSIONS: The results indicate that the Pt-based agents investigated are major modulators of ion homeostasis in excretory organs, which most likely contributes to their systemic toxicity and limits their efficacy. A better understanding of subtle patterns and correlations among elements in key organs may provide deeper insights into the mechanisms of action and ultimately contribute for better, safer drugs. To achieve this goal, researchers involved in cancer drug development may leverage the high sensitivity and high sample throughput of ICP-MS, and the capabilities of modern statistical tools to extract relevant information from a large dataset.

Identifying and assessing matrix effect severity in inductively coupled plasma optical emission spectrometry using non-analyte signals and unsupervised learning.

An unsupervised data-driven methodology is used to quantify matrix effects caused by carbon and easily ionizable elements (EIEs) in inductively coupled plasma optical emission spectrometry (ICP OES). Background signals from nine plasma naturally-occurring species of Ar, H and O are used with principal component analysis (PCA) and affinity propagation (AP) clustering to evaluate the effects of complex matrices on ionic emission lines of Cd, Co, Cr and Pb. Matrix effect severity is then quantified based on Euclidean distance in principal component space from an average calibration curve point. The method has been applied to spiked solutions of Mediterranean Sea and Dead Sea water samples, and a significant correlation (- 0.997) was found between Euclidean distance and analyte recoveries. For sea water analysis, accurate results are found using external standard calibration (EC) when Euclidean distance < 1 for a given sample, and/or when that sample point groups with the calibration curve after affinity propagation clustering. Thus, by applying the PCA-AP strategy, one needs to perform no addition/recovery experiment to evaluate EC applicability. In addition, it can be carried out on the fly, as the background species used to monitor plasma changes are simultaneously recorded with the analytical signals, and a specific algorithm can be added to the instrument control software to flag instances in which EC may be ineffective. This is a proof-of-concept study, and additional work is required to evaluate the method's applicability to a larger number of analytes and sample matrices. However, the PCA-AP method described here for ICP OES can be used to quantify matrix effects, allowing for informed decisions regarding calibration. It requires no additional sample preparation and can be easily implemented in routine analyses of such complex-matrix samples as sea water.

Chemical Synthesis of Glycosides of N-Acetylneuraminic Acid.

Investigations of methodologies aimed on improving the stereoselective synthesis of sialosides and the efficient assembly of sialic acid glycoconjugates has been the mission of dedicated research groups from the late 1960s. This review presents major accomplishments in the field, with the emphasis on significant breakthroughs and influential synthetic strategies of the last decade.

Analysis of single, cisplatin-induced DNA bends by atomic force microscopy and simulations.

Bent DNA, or DNA that is locally more flexible, is a recognition motif for many DNA binding proteins. These DNA conformational properties can thus influence many cellular processes, such as replication, transcription, and DNA repair. The importance of these DNA conformational properties is juxtaposed to the experimental difficulty to accurately determine small bends, locally more flexible DNA, or a combination of both (bends with increased flexibility). In essence, many current bulk methods use average quantities, such as the average end-to-end distance, to extract DNA conformational properties; they cannot access the additional information that is contained in the end-to-end distance distributions. We developed a method that exploits this additional information to determine DNA conformational parameters. The method is based on matching end-to-end distance distributions obtained experimentally by atomic force microscopy imaging to distributions obtained from simulations. We applied this method to investigate cisplatin GG biadducts. We found that cisplatin induces a bend angle of 36° and softens the DNA locally around the bend.

Inductively coupled plasma mass spectrometry and standard dilution analysis applied to concentrated acids.

This work describes a procedure using the recently proposed standard dilution analysis (SDA) calibration method for the determination of As, Cr and Ni in concentrated HNO3 and HCl by inductively coupled plasma tandem mass spectrometry (ICP-MS/MS). Because of the low contaminant levels, and consequently low limits of detection required for these reagents (commonly used in trace element analysis and the semiconductor industry), samples were minimally diluted. The analysis of concentrated acids can result in matrix/transport effects, which may compromise accuracy in ICP-MS determinations. High-chlorine content samples are also challenging for As and Cr determination due to the formation of polyatomic species such as 40Ar35Cl+ and 35Cl16OH+, which overlap the only As isotope, 75As+, and the main Cr isotope, 52Cr+, respectively. The combination of SDA and ICP-MS/MS was evaluated to overcome matrix, transport and spectral interferences in order to increase accuracy, precision and sample throughput. The performance of SDA was compared with the traditional methods of external standard calibration (EC), internal standardization (IS), and standard additions (SA). The limits of detection for SDA were calculated as 6, 10, and 30ngL-1 for As, Cr, and Ni, respectively. Recoveries for spike experiments using the new method were in the 90-114% range for all analytes. The procedure described here provides similar or even better analytical performance in comparison with EC, IS and SA.

Standard dilution analysis of beverages by microwave-induced plasma optical emission spectrometry.

In this work, standard dilution analysis (SDA) is combined with microwave-induced plasma optical emission spectrometry (MIP OES) to determine seven elements in coffee, green tea, energy drink, beer, whiskey and cachaça (Brazilian hard liquor). No sample preparation other than simple dilution in HNO3 1% v v(-1) is required. Due to relatively low plasma temperatures, matrix effects may compromise accuracies in MIP OES analyzes of complex samples. The method of standard additions (SA) offers enhanced accuracies, but is time-consuming and labor intensive. SDA offers a simpler, faster approach, with improved accuracies for complex matrices. In this work, SDA's efficiency is evaluated by spike experiments, and the results are compared to the traditional methods of external calibration (EC), internal standard (IS), and standard additions (SA). SDA is comparable to the traditional calibration methods, and it provides superior accuracies for applications involving ethanol-containing beverage samples. The SDA-MIP OES procedure is effective. Using only two calibration solutions, it may be easily automated for accurate and high sample throughput routine applications.

Standard dilution analysis.

Standard dilution analysis (SDA) is a novel calibration method that may be applied to most instrumental techniques that will accept liquid samples and are capable of monitoring two wavelengths simultaneously. It combines the traditional methods of standard additions and internal standards. Therefore, it simultaneously corrects for matrix effects and for fluctuations due to changes in sample size, orientation, or instrumental parameters. SDA requires only 200 s per sample with inductively coupled plasma optical emission spectrometry (ICP OES). Neither the preparation of a series of standard solutions nor the construction of a universal calibration graph is required. The analysis is performed by combining two solutions in a single container: the first containing 50% sample and 50% standard mixture; the second containing 50% sample and 50% solvent. Data are collected in real time as the first solution is diluted by the second one. The results are used to prepare a plot of the analyte-to-internal standard signal ratio on the y-axis versus the inverse of the internal standard concentration on the x-axis. The analyte concentration in the sample is determined from the ratio of the slope and intercept of that plot. The method has been applied to the determination of FD&C dye Blue No. 1 in mouthwash by molecular absorption spectrometry and to the determination of eight metals in mouthwash, wine, cola, nitric acid, and water by ICP OES. Both the accuracy and precision for SDA are better than those observed for the external calibration, standard additions, and internal standard methods using ICP OES.

Differential response of MCF7, MDA-MB-231, and MCF 10A cells to hyperthermia, silver nanoparticles and silver nanoparticle-induced photothermal therapy.

PURPOSE: Silver nanoparticles (Ag NP) can generate heat upon exposure to infrared light. The in vitro response of breast cell lines to Ag NP, both with and without nanoparticle-induced heating was evaluated. MATERIALS AND METHODS: Ag NP heat generation, intracellular silver concentration, and cell viability of MDA-MB-231, MCF7, and MCF 10A breast cells with Ag NP alone, or after exposure to 0.79 or 2.94 W/cm2 of 800 nm light were evaluated. RESULTS: The concentration of Ag NP to induce sufficient heat for cell death, upon exposure to 800 nm light, was 5-250 µg/mL. Clonogenics assay indicates a cytotoxic response of MCF7 (45% decrease) and MDA-MB-231 (80% decrease) cells to 10 µg/mL, whereas MCF 10A had a 25% increase. Without Ag NP, MDA-MB-231 cells were more susceptible to hyperthermia, compared to MCF7 and MCF 10A cells. Clonogenics assay of Ag NP-induced photothermal ablation demonstrated that MCF 10A cells have the highest survival fraction. MCF7 cells had more silver in the cytoplasm, MDA-MB-231 cells had more in the nuclei, and MCF 10A cells had equivalent concentrations in the cytoplasm and nuclei. CONCLUSIONS: Ag NP are effective photothermal agents. A secondary benefit is the differential response of breast cancer cells to Ag NP-induced hyperthermia, due to increased intracellular silver content, compared to non-tumorigenic breast epithelial cells.

Bismuth as a general internal standard for lead in atomic absorption spectrometry.

Bismuth was evaluated as internal standard for Pb determination by line source flame atomic absorption spectrometry (LS FAAS), high-resolution continuum source flame atomic absorption spectrometry (HR-CS FAAS) and line source graphite furnace atomic absorption spectrometry (LS GFAAS). Analysis of samples containing different matrices indicated close relationship between Pb and Bi absorbances. Correlation coefficients of calibration curves built up by plotting A(Pb)/A(Bi)versus Pb concentration were higher than 0.9953 (FAAS) and higher than 0.9993 (GFAAS). Recoveries of Pb improved from 52-118% (without IS) to 97-109% (IS, LS FAAS); 74-231% (without IS) to 96-109% (IS, HR-CS FAAS); and 36-125% (without IS) to 96-110% (IS, LS GFAAS). The relative standard deviations (n=12) were reduced from 0.6-9.2% (without IS) to 0.3-4.3% (IS, LS FAAS); 0.7-7.7% (without IS) to 0.1-4.0% (IS, HR-CS FAAS); and 2.1-13% (without IS) to 0.4-5.9% (IS, LS GFAAS).

Direct determination of sodium, potassium, chromium and vanadium in biodiesel fuel by tungsten coil atomic emission spectrometry.

High levels of sodium and potassium can be present in biodiesel fuel and contribute to corrosion, reduced performance and shorter engine lifetime. On the other hand, trace amounts of chromium and vanadium can increase the emission of pollutants during biodiesel combustion. Sample viscosity, immiscibility with aqueous solutions and high carbon content can compromise biodiesel analyzes. In this work, tungsten filaments extracted from microscope light bulbs are used to successively decompose biodiesel's organic matrix, and atomize and excite the analytes to determine sodium, potassium, chromium and vanadium by tungsten coil atomic emission spectrometry (WCAES). No sample preparation other than simple dilution in methanol or ethanol is required. Direct analysis of 10-µL sample aliquots using heating cycles with less than 150 s results in limits of detection (LOD) as low as 20, 70, 70 and 90 µg kg(-1) for Na, K, Cr and V, respectively. The procedure's accuracy is checked by determining Na and K in a biodiesel reference sample and carrying out spike experiments for Cr and V. No statistically significant differences were observed between reference and determined values for all analytes at a 95% confidence level. The procedure was applied to three different biodiesel samples and concentrations between 6.08 and 95.6 mg kg(-1) for Na and K, and between 0.22 and 0.43 mg kg(-1) for V were obtained. The procedure is simple, fast and environmentally friendly. Small volumes of reagents, samples and gases are used and no residues are generated. Powers of detection are comparable to other traditional methods.

Cobalt as chemical modifier to improve chromium sensitivity and minimize matrix effects in tungsten coil atomic emission spectrometry.

Cobalt is used as chemical modifier to improve sensitivity and minimize matrix effects in Cr determinations by tungsten coil atomic emission spectrometry (WCAES). The atomizer is a tungsten filament extracted from microscope light bulbs. A solid-state power supply and a handheld CCD-based spectrometer are also used in the instrumental setup. In the presence of 1000 mg L(-1) Co, WCAES limit of detection for Cr (λ=425.4 nm) is calculated as 0.070 mg L(-1); a 10-fold improvement compared to determinations without Co modifier. The mechanism involved in such signal enhancement is similar to the one observed in ICP OES and ICP-MS determinations of As and Se in the presence of C. Cobalt increases the population of Cr(+) by charge transfer reactions. In a second step, Cr(+)/e(-) recombination takes place, which results in a larger population of excited-state Cr atoms. This alternative excitation route is energetically more efficient than heat transfer from atomizer and gas phase to analyte atoms. A linear dynamic range of 0.25-10 mg L(-1) and repeatability of 3.8% (RSD, n=10) for a 2.0 mg L(-1) Cr solution are obtained with this strategy. The modifier high concentration also contributes to improving accuracy due to a matrix-matching effect. The method was applied to a certified reference material of Dogfish Muscle (DORM-2) and no statistically significant difference was observed between determined and certified Cr values at a 95% confidence level. Spike experiments with bottled water samples resulted in recoveries between 93% and 112%.

A portable tungsten coil atomic emission spectrometer for the simultaneous determination of metals in water and soil samples.

Tungsten coil atomic emission spectrometry (WCAES) has been evaluated as a potentially portable technique for field applications. The tungsten coil (W-coil) was extracted from a commercially available slide projector bulb and used as both the atomizer and the excitation source. The coil was powered by a small solid-state power supply. A hand-held CCD spectrometer, powered from a laptop computer, collected the signal. Fifteen elements were used to evaluate the portable system. For elements in the UV region, LODs were increased by a factor of 2000 for Cu; 200 for Ag; and 25 for Co through a 400-W solid state power supply compared to a 200-W solid state power supply. Signals for Al, Cr, Ga, Mn, Li and V in the near UV region also increased around a factor of 25. Therefore, the WCAES device could be used for elements in both the visible and UV regions, and the system could be taken into the field to measure elements in various samples.