Identification of individual goat animals by means of near infrared spectroscopy and chemometrics analysis of commercial meat cuts.

Although the identification of animal species and muscles have been reported previously, no studies have been found on the use of NIR spectroscopy to identify individual animals from the analysis of commercial meat cuts. The aim of this study was to evaluate the use of a portable near infrared (NIR) instrument combined with classical chemometrics methods [principal component analysis (PCA) and partial least squares discriminant analysis PLS-DA)] to identify the origin of individual goat animals using the spectral signature of their commercial cut. Samples were collected from several carcasses (6 commercial cuts x 24 animals) sourced from a commercial abattoir in Queensland (Australia). The NIR spectra of the samples were collected using a portable NIR instrument in the wavelength range between 950 and 1600 nm. Overall, the PLS-DA models correctly classify 82% and 79% of the individual goat samples using either the goat rack or loin cut samples, respectively. The study demonstrated that NIR spectroscopy was able to identify individual goat animals based on the spectra properties of some of the commercial cut samples analysed (e.g. loin and rack). These results showed the potential of this technique to identify individual animals as an alternative to other laboratory methods and techniques commonly used in meat traceability.

The ability of a portable near infrared instrument to evaluate the shelf-life of fresh and thawed goat muscles.

The objective of this study was to evaluate the use of a portable near infrared (NIR) instrument to monitor the shelf-life of four goat muscles [longissimus thoracis et lumborum (LTL), semimembranosus (SM), semitendinosus (ST) and biceps femoris (BF)] stored for up to 8 days (4 °C). The NIR spectra of the muscle samples were collected at day 0, and after 1, 4 and 8 days of storage using a MicroNIR instrument (900-1600 nm). The coefficient of determination in cross-validation (R2) and the standard error in cross validation (SECV) obtained for the prediction of days of storage ranged between 0.76 and 0.86, where the SECV ranged from 0.32 to 0.41. The best statistics in cross-validation were obtained for the prediction of days of storage in the BF samples, followed by the ST and LTL muscles. Differences in the PLS loadings for the cross-validation models were observed due to the interactions between the different muscle samples and days of storage. Overall, these results showed the potential of NIR spectroscopy to identify the time of storage in four different goat muscles. Similar data and techniques could be used to predict the remaining shelf life of meat derived from different species under storage. This information can then be used as a tool to predict and guarantee the safety of meat samples to the consumer along the meat supply and value chains.

Rapid screening of bacteriostatic and bactericidal antimicrobial agents against Escherichia coli by combining machine learning (artificial intelligence) and UV-VIS spectroscopy.

Antibiotics are compounds that have a particular mode of action upon the microorganism they are targeting. However, discovering and developing new antibiotics is a challenging and timely process. Antibiotic development process can take up to 10-15 years and over $1billion to develop a single new therapeutic product. Rapid screening tools to understand the mode of action of the new antimicrobial agent are considered one of the main bottle necks in the antimicrobial agent development process. Classical approaches require multifarious microbiological methods and they do not capture important biochemical and organism therapeutic-interaction mechanisms. This work aims to provide a rapid antibiotic-antimicrobial biochemical diagnostic tool to reduce the timeframes of therapeutic development, while also generating new biochemical insight into an antimicrobial-therapeutic screening assay in a complex matrix. The work evaluates the effect of antimicrobial action through "traditional" microbiological analysis techniques with a high-throughput rapid analysis method using UV-VIS spectroscopy and chemometrics. Bacteriostatic activity from tetracycline and bactericidal activity from amoxicillin were evaluated on a system using non-resistant Escherichia coli O157:H7 by confocal laser scanning microscopy (CLSM), scanning electron microscopy (SEM), and UV-VIS spectroscopy (high-throughput analysis). The data were analysed using principal component analysis (PCA) and support vector machine (SVM) classification. The rapid diagnostic technique could easily identify differences between bacteriostatic and bactericidal mechanisms and was considerably quicker than the "traditional" methods tested.

Pre-processing Applied to Instrumental Data in Analytical Chemistry: A Brief Review of the Methods and Examples.

The field of analytical chemistry has been significantly advanced by the availability of state-of-the-art instrumentation, allowing for the development of novel applications in this field. However, in many cases, the direct interpretation of the recorded data is often not straightforward, hence some level of pre-processing is required (e.g., baseline correction, derivatives, normalization, smoothing). These techniques have become a critical first step for the successful analysis of the data recorded, and it is recommended to use them before the application of chemometrics (e.g., classification, calibration development). The aim of this paper is to provide with an overview of the most used pre-processing methods applied to instrumental analytical methods (e.g., spectroscopy, chromatography). Examples of their application in near infrared and UV-VIS spectroscopy as well as in gas chromatography will be also discussed. Overall, this paper provides with a comprehensive understanding of pre-processing techniques in analytical chemistry, highlighting their importance during the analysis and interpretation of data, as well as during the development of accurate and reliable chemometric models.

Discrimination of lamb (Ovis aries), emu (Dromaius novaehollandiae), camel (Camelus dromedarius) and beef (Bos taurus) binary mixtures using a portable near infrared instrument combined with chemometrics.

Consumers demand safe and nutritious foods at accessible prices; where issues associated with adulteration, fraud, and provenance have become important aspects to be considered by the modern food industry. There are many analytical techniques and methods available to determine food composition and quality, including food security. Among them, vibrational spectroscopy techniques are at the first line of defence (near and mid infrared spectroscopy, and Raman spectroscopy). In this study, a portable near infrared (NIR) instrument was evaluated to identify different levels of adulteration between binary mixtures of exotic and traditional meat species. Fresh meat cuts of lamb (Ovis aries), emu (Dromaius novaehollandiae), camel (Camelus dromedarius) and beef (Bos taurus) sourced from a commercial abattoir were used to make different binary mixtures (95 % %w/w, 90 % %w/w, 50 % %w/w, 10 % %w/w and 5 % %w/w) and analysed using a portable NIR instrument. The NIR spectra of the meat mixtures was analysed using principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). Two isosbestic points corresponding to absorbances at 1028 nm and 1224 nm were found to be consistent across all the binary mixtures analysed. The coefficient of determination in cross validation (R2) obtained for the determination of the per cent of species in a binary mixture was above 90 % with a standard error in cross validation (SECV) ranging between 12.6 and 15 %w/w. Overall, the results of this study indicate that NIR spectroscopy can determine the level or ratio of adulteration in the binary mixtures of minced meat.

Predictors of in-hospital mortality of COVID-19 patients and the role of telemetry in an internal medicine ward during the third phase of the pandemic.

OBJECTIVE: The first pandemic phase of COVID-19 in Italy was characterized by high in-hospital mortality ranging from 23% to 38%. During the third pandemic phase there has been an improvement in the management and treatment of COVID-19, so mortality and predictors may have changed. A prospective study was planned to identify predictors of mortality during the third pandemic phase. PATIENTS AND METHODS: From 15 December 2020 to 15 May 2021, 208 patients were hospitalized (median age: 64 years; males: 58.6%); 83% had a median of 2 (IQR,1-4) comorbidities; pneumonia was present in 89.8%. Patients were monitored remotely for respiratory function and ECG trace for 24 hours/day. Management and treatment were done following the timing and dosage recommended by international guidelines. RESULTS: 79.2% of patients necessitated O2-therapy. ARDS was present in 46.1% of patients and 45.4% received non-invasive ventilation and 11.1% required ICU treatment. 38% developed arrhythmias which were identified early by telemetry and promptly treated. The in-hospital mortality rate was 10%. At multivariate analysis independent predictors of mortality were: older age (R-R for≥70 years: 5.44), number of comorbidities ≥3 (R-R 2.72), eGFR ≤60 ml/min (RR 2.91), high d-Dimer (R-R for≥1,000 ng/ml:7.53), and low PaO2/FiO2 (R-R for <200: 3.21). CONCLUSIONS: Management and treatment adherence to recommendations, use of telemetry, and no overcrowding appear to reduce mortality. Advanced age, number of comorbidities, severe renal failure, high d-Dimer and low P/F remain predictors of poor outcome. The data help to identify current high-risk COVID-19 patients in whom management has yet to be optimized, who require the greatest therapeutic effort, and subjects in whom vaccination is mandatory.

Clinical application of lung ultrasound score on COVID-19 setting: a regional experience in Southern Italy.

OBJECTIVE: We aimed to assess the correlation between LUS Soldati proposed score and clinical presentation, course of disease and the possible need of ventilation support/intensive care. PATIENTS AND METHODS: All consecutive patients with laboratory confirmed SARS-CoV-2 infection and hospitalized in two COVID Centers were enrolled. All patients performed blood gas analysis and lung ultrasound (LUS) at admission. The LUS acquisition was based on standard sequence of 14 peculiar anatomic landmarks with a score between 0-3 based on impairment of LUS picture. Total score was computed with their sum with a total score ranging 0 to 42, according to Soldati LUS score. We evaluated the course of hospitalization until either discharge or death, the ventilatory support and the transition in intensive care if needed. RESULTS: One hundred and fifty-six patients were included in the final analysis. Most of patients presented moderate-to-severe respiratory failure (FiO2 <20%, PaO2 <60 mmHg) and consequent recommendation to invasive mechanic ventilation (CPAP/NIV/OTI). The median ultrasound thoracic score was 28 (IQR 18-36) and most of patients could be ascertained either in a score 2 (40%) or score 3 pictures (24.4%). The bivariate correlation analysis displayed statistically significant and high positive correlations between the LUS score and the following parameters: ventilation (rho=0.481, p<0.001), lactates (rho=0.464, p<0.001), dyspnea (rho=0.398, p=0.001) mortality (rho=0.410, p=0.001). Conversely, P/F (rho= -0.663, p<0.001), pH (rho = -0.363, p=0.003) and pO2 (rho = -0.400 p=0.001) displayed significant negative correlations. CONCLUSIONS: LUS score improve the workflow and provide an optimal management both in early diagnosis and prognosis of COVID-19 related lung pathology.

Insights on the role of chemometrics and vibrational spectroscopy in fruit metabolite analysis.

The last three decades have demonstrated the ability of combining data analytics (e.g. big data, machine learning) with modern analytical instrumental techniques such as vibrational spectroscopy (VIBSPEC) (e.g. NIR, Raman, MIR) and sensing technologies (e.g. electronic noses and tongues, colorimetric sensors) to analyse, measure and monitor a wide range of properties and samples. Developments in instrumentation, hardware and software have placed VIBSPEC as a useful tool to quantify several bioactive compounds and metabolites in a wide range of fruit and plant samples. With the incorporation of hand-held and portable instrumentation, these techniques have been valuable for the development of in-field and high throughput applications, opened new frontiers of analysis in fruits and plants. This review will present and discuss some of the current applications on the use of VIBSPEC techniques combined with data analytics on the measurement bioactive compounds and plant metabolites in different fruit samples.

Hong-Ou-Mandel interference between independent III-V on silicon waveguide integrated lasers.

The versatility of silicon photonic integrated circuits has led to a widespread usage of this platform for quantum information-based applications, including quantum key distribution (QKD). However, the integration of simple high-repetition-rate photon sources is yet to be achieved. The use of weak-coherent pulses (WCPs) could represent a viable solution. For example, measurement device independent QKD (MDI-QKD) envisions the use of WCPs to distill a secret key immune to detector side channel attacks at large distances. Thus, the integration of III-V lasers on silicon waveguides is an interesting prospect for quantum photonics. Here we report the experimental observation of Hong-Ou-Mandel interference with 46±2% visibility between WCPs generated by two independent III-V on silicon waveguide integrated lasers. This quantum interference effect is at the heart of many applications, including MDI-QKD. This Letter represents a substantial first step towards an implementation of MDI-QKD fully integrated in silicon and could be beneficial for other applications such as standard QKD and novel quantum communication protocols.

A review of methods for the detection of pathogenic microorganisms.

The testing and rapid detection of pathogenic organisms is a crucial protocol in the prevention and identification of crises related to health, safety and wellbeing. Pathogen detection has become one of the most challenging aspects in the food and water industries, because of the rapid spread of waterborne and foodborne diseases in the community and at significant costs. With the prospect of inevitable population growth, and an influx of tourism to certain water bodies testing will become a requirement to control and prevent possible outbreaks of potentially fatal illnesses. The legislation is already particularly rigorous in the food industry, where failure to detect pathogenic materials represents a catastrophic event, particularly for the elderly, very young or immune-compromised population types. In spite of the need and requirement for rapid analytical testing, conventional and standard bacterial detection assays may take up to seven days to yield a result. Given the advent of new technologies, biosensors, chemical knowledge and miniaturisation of instrumentation this timescale is not acceptable. This review presents an opportunity to fill a knowledge gap for an extremely important research area; discussing the main techniques, biology, chemistry, miniaturisation, sensing and the emerging state-of-the-art research and developments for detection of pathogens in food, water, blood and faecal samples.

Biochemical control and toxicity for favorable- and intermediate-risk patients using real-time intraoperative inverse optimization prostate seed implant: Less is more!

PURPOSE: To report the biochemical control rate and clinical outcomes with real-time inverse planning (inverse optimization prostate seed implant [IO-PSI]) for favorable-risk (FR) and intermediate-risk (IR) prostate adenocarcinoma in a community practice setting. This analysis is an extended followup of our initial report, with favorable early biochemical control rate (biochemical nonevidence of disease) of 97% at 4 years. METHODS AND MATERIALS: Three hundred fifty-seven evaluable patients with FR and IR prostate cancer underwent real-time IO-PSI (iodine-125/145 Gy or palladium-103/120 Gy) between 2001 and 2013. RESULTS: With a median followup of 54 months (range, 24-110 months), the absolute biochemical failure free survival of disease was 96%. The 8-year actuarial probability of prostate-specific antigen failure-free survival for FR and IR cohorts was 92.4% and 87%, respectively. Late genitourinary and gastrointestinal toxicity remained low. Late Grade 2 and Grade 3 genitourinary toxicity was 19% and 1%, respectively. Late Grade 2 and 3 rectal bleeding rates were 1% and 0%, respectively. No difference in biochemical control was observed with preimplant short course androgen deprivation or between Gleason score 3 + 4 vs. 4 + 3 patients. No dosimetric parameter was predictive of biochemical failure. Patients with FR had a significantly decreased risk of failure (hazard ratio = 0.26; 95% confidence interval = 0.09-0.78; p = 0.02) compared with those with IR. Patients with a prostate-specific antigen nadir >0.4 ng/mL had an increased risk of failure (hazard ratio = 1.37; 95% confidence interval = 1.27-1.47; p < 0.0001). CONCLUSIONS: Our initial biochemical and clinical outcomes using real-time IO-PSI persisted with extended followup and support our original hypothesis for use of a reduced number of sources, needles, and total activity, suggesting that with IO, less is more.

TM6SF2 Glu167Lys polymorphism is associated with low levels of LDL-cholesterol and increased liver injury in obese children.

BACKGROUND: The Glu167Lys (E167K) transmembrane 6 superfamily member 2 (TM6SF2) variant has been associated with liver steatosis, high alanine transaminase (ALT) levels and reduced plasma levels of liver-derived triglyceride-rich lipoproteins. OBJECTIVES: The objectives of this study were to investigate in a group of obese children the association among the 167K allele of TM6SF2 gene and ALT, cholesterol and triglycerides levels, and hepatic steatosis, and to evaluate the potential interaction between this variant and the I148M patatin like phospholipase 3 gene (PNPLA3) polymorphism on liver enzymes. METHODS: We genotyped 1010 obese children for TM6SF2 E167K and PNPLA3 I148M polymorphisms. Anthropometrical and biochemical data were collected. Ultrasound imaging of the liver was performed. RESULTS: The 167K allele showed an association with steatosis (P < 0.0001), higher ALT levels (P < 0.001) and lower total cholesterol (P < 0.00001), low-density lipoprotein cholesterol (P < 0.0001), triglycerides (P = 0.02) and non-high-density lipoprotein cholesterol levels (P < 0.000001). The subjects homozygous for the PNPLA3 148M allele carrying the rare variant of TM6SF2 showed an odds ratio of 12.2 (confidence interval 3.8-39.6, P = 0.000001) to present hypertransaminasaemia compared with the remaining patients. CONCLUSION: Although the TMS6SF2 E167K variant predisposes the obese children to non-alcoholic fatty liver disease, there is an association between this variant and lower levels of cardiovascular risk factors. Overall, the data suggest differential effects of TMS6SF2 E167K variant on liver and heart health.

In situ study of water uptake by the seeds, endosperm and husk of barley using infrared spectroscopy.

Variations in the amount and rates of water uptake influence the seed hydration as well as the modification of the endosperm for industrial uses (e.g., malting). The aim of this study was to investigate and interpret absorption frequencies in the mid infrared (MIR) region associated with water uptake in whole seeds, husk and endosperm of barley seeds during the initial period of soaking in water. Partial least squares (PLS) regression models for the prediction of water uptake in the set of samples yield a coefficient of determination (R(2)) and a standard error in cross validation of 0.75 and 2.57 (% w/w), respectively. The biological implications of this study are that the first stages of germination can be monitored using the information derived from the MIR spectra. These results also demonstrated that whole seeds, endosperm and husk derived from the same variety or genotype have different patterns in the MIR region.

A novel approach to monitor the hydrolysis of barley (Hordeum vulgare L) malt: a chemometrics approach.

Malting barley is a process that has been profusely studied and is known to be influenced by several physical and biochemical properties of the grain. In particular, the amount of material that can be extracted from the malt (malt extract) is an important measure of brewing performance and end quality. The objectives of this study were (a) to compare the time course of hydrolysis of different malting barley (Hordeum vulgare L) varieties and (b) to evaluate the usefulness of mid-infrared (MIR) spectroscopy as high-throughput method to monitor malt hydrolysis. Differences in the pattern of hydrolysis were observed between the malt samples analyzed where samples from the same variety that have similar hot water extract (HWE) values tend to have the same pattern of hydrolysis. Principal component score plots based on the MIR spectra showed similar results. Partial least-squares discriminate analysis (PLS-DA) was used to classify malt samples according to their corresponding variety and time course of hydrolysis. The coefficient of determination (R(2)) and the standard error of cross validation (SECV) obtained for the prediction of variety and time course of hydrolysis were 0.67 (1.01) and 0.38 (19.90), respectively. These differences might be the result of the different composition in sugars between the barley varieties analyzed after malting, measured as wort density and not observed when only the HWE value at the end point is reported. This method offers the possibility to measure several parameters in malt simultaneously, reducing the time of analysis as well as requiring minimal sample preparation.

An attenuated total reflectance mid infrared (ATR-MIR) spectroscopy study of gelatinization in barley.

The aim of this study was to evaluate the use of attenuated total reflectance and mid infrared (ATR-MIR) spectroscopy and to understand the gelatinization and retro-gradation of flour barley samples and the relationship with malting quality. Samples were sourced from two commercial barley varieties exhibiting high hot water extract (HWE) namely Navigator (n=8), and Admiral (n=8). Samples were analysed using the Rapid Visco Analyser (RVA) and ATR-MIR analysis. These results showed that ATR-MIR spectroscopy is capable of characterising gel samples derived from barley flour samples having different malting characteristics. Infrared spectra can effectively represent a 'fingerprint' of the sample being analysed and can be used to simplify and reduce analytical times in the routine methods currently used.

The role of total lipids and fatty acids profile on the water uptake of barley grain during steeping.

Steeping is the first operation of malting and its overall purpose is to increase the water content of the grain, as well as to activate the enzymatic pool in the endosperm. The aim of this study was to evaluate the effects of total lipids content and individual fatty acids on water uptake, by commercial barley varieties. The results from this study showed that unsaturated fatty acids, such as oleic acid (18:1-n9), have a role in controlling water uptake by the barley endosperm during steeping. When partial least squares (PLS) regression was used to relate total lipids, individual fatty acids and water uptake, oleic (18:1-n9) acid had a positive effect, while long chain unsaturated fatty acids such as arachidic (20:0) and lignoceric (24:0) acids had a negative effect on explaining 72% of the total variability in water uptake. Water uptake by the endosperm is just a component of the system that is responsible for the overall malt quality properties and chemical characteristics of a given material. In this context, both total lipids and individual fatty acids have a role on determining malt quality in barley.

A Review on the Role of Vibrational Spectroscopy as An Analytical Method to Measure Starch Biochemical and Biophysical Properties in Cereals and Starchy Foods.

Starch is the major component of cereal grains and starchy foods, and changes in its biophysical and biochemical properties (e.g., amylose, amylopectin, pasting, gelatinization, viscosity) will have a direct effect on its end use properties (e.g., bread, malt, polymers). The use of rapid and non-destructive methods to study and monitor starch properties, such as gelatinization, retrogradation, water absorption in cereals and starchy foods, is of great interest in order to improve and assess their quality. In recent years, near infrared reflectance (NIR) and mid infrared (MIR) spectroscopy have been explored to predict several quality parameters, such as those generated by instrumental methods commonly used in routine analysis like the rapid visco analyser (RVA) or viscometers. In this review, applications of both NIR and MIR spectroscopy to measure and monitor starch biochemical (amylose, amylopectin, starch) and biophysical properties (e.g., pasting properties) will be presented and discussed.

Characterization of pituitary cells targeted by antipituitary antibodies in patients with isolated autoimmune diseases without pituitary insufficiency may help to foresee the kind of future hypopituitarism.

PURPOSE: Detection of antipituitary antibodies (APA) at high levels and with a particular immunofluorescence pattern in patients with autoimmune polyendocrine syndromes may indicate a possible future autoimmune pituitary involvement. This longitudinal study was aimed at characterizing in patients with a single organ-specific autoimmune disease the pituitary cells targeted by APA at start, verifying whether this characterization allows to foresee the kind of possible subsequent hypopituitarism. METHODS: Thirty-six APA positive and 40 APA negative patients with isolated autoimmune diseases participated in the study. None of them had pituitary dysfunction at entry. Characterization by four-layer immunofluorescence of pituitary cells targeted by APA in APA positive patients at entry and study of pituitary function in all patients were performed every 6 months during a 5 year follow-up. RESULTS: Antipituitary antibodies immunostained selectively one type of pituitary-secreting cells in 21 patients (58.3 %, group 1), and several types of pituitary cells in the remaining 15 (41.7 %, group 2). All patients in group 1 showed subsequently a pituitary insufficiency, corresponding to the type of cells targeted by APA in 18 of them (85.7 %). Only 8 out of 15 patients in group 2 (53.3 %) showed a hypopituitarism, isolated in 7 and combined in the other one. None of APA negative patients showed hypopituitarism. CONCLUSIONS: The characterization of pituitary cells targeted by APA in patients with isolated autoimmune diseases, when the pituitary function is still normal, may help to foresee the kind of subsequent hypopituitarism, especially when APA immunostained selectively only one type of pituitary cells. A careful follow-up of pituitary function in these patients is advisable to allow an early diagnosis of hypopituitarism, even in subclinical phase and a consequent timely replacement therapy.

Prediction of starch pasting properties in barley flour using ATR-MIR spectroscopy.

The objective of this study was to evaluate the feasibility of using attenuated total reflectance (ATR) mid infrared (MIR) spectroscopy to predict starch pasting properties in barley flour samples. A total of 180 barley flour samples sourced from the University of Adelaide germplasm collection, harvested over three seasons (2009, 2010 and 2011) were analysed using both ATR-MIR and the rapid visco analyser (RVA) techniques. Calibrations (n=100) were developed using partial least squares (PLS1) regression and full cross validation. The coefficient of determination (R(2)) and the standard error in cross validation (SECV) were 0.74 (SECV=875 RVU) for peak viscosity (PV), 0.63 (SECV=561 RVU) for trough (THR), 0.80 (SECV=173 RVU) for breakdown (BRK), 0.74 (SECV=126 RVU) for setback (STB), 0.77 (SECV=679 RVU) for final viscosity (FV), and 0.73 (SECV=0.57 s) for time to peak (TTP). The RPD values (SD/SEP) from the validation indicated that only BRK can be accurately predicted (RPD=4). We have demonstrated that ATR-MIR spectroscopy has the potential to significantly reduce analytical time and cost during the analysis of barley flour for starch pasting properties.

Technical solutions for analysis of grape juice, must, and wine: the role of infrared spectroscopy and chemometrics.

Information about constituents of grape juice, must, and wine can be used for management and decision support systems in order to improve, monitor, and adapt grape and wine production to new challenges. Numerous sensors that gather this information are either currently available or in development. Nevertheless there is still a need to adapt these sensors to special requirements, for example robustness, calibration and maintenance, operating costs, duration, sensitivity, and specificity to a particular application. The sensors commonly used by the wine industry are those that are based on mid-infrared (MIR), near-infrared (NIR), visible (VIS) and ultraviolet (UV) spectroscopy. This article reviews some recent technical solutions for analysis of juice, must and wine based on the combination of infrared spectroscopy and chemometrics.