Trace level detection of melamine and cyanuric acid extracted from pet liquid food (milk) using a SERS Au nanogap substrate

This study reported an application of Au nanogap substrates for surface-enhanced Raman scattering (SERS) measurements to quantitatively analyze melamine and its derivative products at trace levels in pet liquid food (milk) combined with a waveband selection approach, namely variable importance in projection (VIP). Six different concentrations of melamine, cyanuric acid, and melamine combined with cyanuric acid were created, and SERS spectra were acquired from 550 to 1620cm-1. Detection was possible up to 200 pM for melamine-contaminated samples, and 400 pM concentration detection for other two groups. The VIP-PLSR models obtained correlation coefficient (R2) values of 0.997, 0.985, and 0.981, with root mean square error of prediction (RMSEP) values of 18.492 pM, 19.777 pM, and 15.124 pM for prediction datasets. Additionally, partial least square discriminant analysis (PLS-DA) was used to classify both pure and different concentrations of spiked samples. The results showed that the maximum classification accuracy for melamine was 100%, for cyanuric acid it was 96%, and for melamine coupled with cyanuric acid it was 95%. The results obtained clearly demonstrated that the Au nanogap substrate offers low-concentration, rapid, and efficient detection of hazardous additive chemicals in pet consuming liquid food.

Study of High-Transverse-Momentum Higgs Boson Production in Association with a Vector Boson in the qqbb Final State with the ATLAS Detector

This Letter presents the first study of Higgs boson production in association with a vector boson (V=W or Z) in the fully hadronic qqbb final state using data recorded by the ATLAS detector at the LHC in proton-proton collisions at sqrt[s]=13  TeV and corresponding to an integrated luminosity of 137  fb^{-1}. The vector bosons and Higgs bosons are each reconstructed as large-radius jets and tagged using jet substructure techniques. Dedicated tagging algorithms exploiting b-tagging properties are used to identify jets consistent with Higgs bosons decaying into bb[over ¯]. Dominant backgrounds from multijet production are determined directly from the data, and a likelihood fit to the jet mass distribution of Higgs boson candidates is used to extract the number of signal events. The VH production cross section is measured inclusively and differentially in several ranges of Higgs boson transverse momentum: 250-450, 450-650, and greater than 650 GeV. The inclusive signal yield relative to the standard model expectation is observed to be μ=1.4_{-0.9}^{+1.0} and the corresponding cross section is 3.1±1.3(stat)_{-1.4}^{+1.8}(syst)  pb.

Measurement of the Centrality Dependence of the Dijet Yield in p+Pb Collisions at sqrt[s_{NN}]=8.16 TeV with the ATLAS Detector

ATLAS measured the centrality dependence of the dijet yield using 165  nb^{-1} of p+Pb data collected at sqrt[s_{NN}]=8.16  TeV in 2016. The event centrality, which reflects the p+Pb impact parameter, is characterized by the total transverse energy registered in the Pb-going side of the forward calorimeter. The central-to-peripheral ratio of the scaled dijet yields, R_{CP}, is evaluated, and the results are presented as a function of variables that reflect the kinematics of the initial hard parton scattering process. The R_{CP} shows a scaling with the Bjorken x of the parton originating from the proton, x_{p}, while no such trend is observed as a function of x_{Pb}. This analysis provides unique input to understanding the role of small proton spatial configurations in p+Pb collisions by covering parton momentum fractions from the valence region down to x_{p}∼10^{-3} and x_{Pb}∼4×10^{-4}.

Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at sqrt[s]=13 TeV with the ATLAS Detector

Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140  fb^{-1} of pp collisions at sqrt[s]=13  TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or b jet and either one lepton (e,μ), photon, or second light jet or b jet in the anomalous regions. No significant deviations from the background hypotheses are observed. Limits on contributions from generic Gaussian signals with various widths of the resonance mass are obtained for nine invariant masses in the anomalous regions.

Observation of WZγ Production in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector

This Letter reports the observation of WZγ production and a measurement of its cross section using 140.1±1.2  fb^{-1} of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. The WZγ production cross section, with both the W and Z bosons decaying leptonically, pp→WZγ→ℓ^{'}^{±}νℓ^{+}ℓ^{-}γ (ℓ^{(^{'})}=e, μ), is measured in a fiducial phase-space region defined such that the leptons and the photon have high transverse momentum and the photon is isolated. The cross section is found to be 2.01±0.30(stat)±0.16(syst)  fb. The corresponding standard model predicted cross section calculated at next-to-leading order in perturbative quantum chromodynamics and at leading order in the electroweak coupling constant is 1.50±0.06  fb. The observed significance of the WZγ signal is 6.3σ, compared with an expected significance of 5.0σ.

Combined Measurement of the Higgs Boson Mass from the H→γγ and H→ZZ^{*}→4ℓ Decay Channels with the ATLAS Detector Using sqrt[s]=7, 8, and 13 TeV pp Collision Data

A measurement of the mass of the Higgs boson combining the H→ZZ^{*}→4ℓ and H→γγ decay channels is presented. The result is based on 140  fb^{-1} of proton-proton collision data collected by the ATLAS detector during LHC run 2 at a center-of-mass energy of 13 TeV combined with the run 1 ATLAS mass measurement, performed at center-of-mass energies of 7 and 8 TeV, yielding a Higgs boson mass of 125.11±0.09(stat)±0.06(syst)=125.11±0.11  GeV. This corresponds to a 0.09% precision achieved on this fundamental parameter of the Standard Model of particle physics.

Search for Dark Photons in Rare Z Boson Decays with the ATLAS Detector

A search for events with a dark photon produced in association with a dark Higgs boson via rare decays of the standard model Z boson is presented, using 139  fb^{-1} of sqrt[s]=13  TeV proton-proton collision data recorded by the ATLAS detector at the Large Hadron Collider. The dark boson decays into a pair of dark photons, and at least two of the three dark photons must each decay into a pair of electrons or muons, resulting in at least two same-flavor opposite-charge lepton pairs in the final state. The data are found to be consistent with the background prediction, and upper limits are set on the dark photon's coupling to the dark Higgs boson times the kinetic mixing between the standard model photon and the dark photon, α_{D}ϵ^{2}, in the dark photon mass range of [5, 40] GeV except for the ϒ mass window [8.8, 11.1] GeV. This search explores new parameter space not previously excluded by other experiments.

The impact of healthy pregnancy on features of heart rate variability and pulse wave morphology derived from wrist-worn photoplethysmography

Due to the association between dysfunctional maternal autonomic regulation and pregnancy complications, tracking non-invasive features of autonomic regulation derived from wrist-worn photoplethysmography (PPG) measurements may allow for the early detection of deteriorations in maternal health. However, even though a plethora of these features-specifically, features describing heart rate variability (HRV) and the morphology of the PPG waveform (morphological features)-exist in the literature, it is unclear which of these may be valuable for tracking maternal health. As an initial step towards clarity, we compute comprehensive sets of HRV and morphological features from nighttime PPG measurements. From these, using logistic regression and stepwise forward feature elimination, we identify the features that best differentiate healthy pregnant women from non-pregnant women, since these likely capture physiological adaptations necessary for sustaining healthy pregnancy. Overall, morphological features were more valuable for discriminating between pregnant and non-pregnant women than HRV features (area under the receiver operating characteristics curve of 0.825 and 0.74, respectively), with the systolic pulse wave deterioration being the most valuable single feature, followed by mean heart rate (HR). Additionally, we stratified the analysis by sleep stages and found that using features calculated only from periods of deep sleep enhanced the differences between the two groups. In conclusion, we postulate that in addition to HRV features, morphological features may also be useful in tracking maternal health and suggest specific features to be included in future research concerning maternal health.

Measurement of Suppression of Large-Radius Jets and Its Dependence on Substructure in Pb+Pb Collisions at sqrt[s_{NN}]=5.02 TeV with the ATLAS Detector

This letter presents a measurement of the nuclear modification factor of large-radius jets in sqrt[s_{NN}]=5.02  TeV Pb+Pb collisions by the ATLAS experiment. The measurement is performed using 1.72  nb^{-1} and 257  pb^{-1} of Pb+Pb and pp data, respectively. The large-radius jets are reconstructed with the anti-k_{t} algorithm using a radius parameter of R=1.0, by reclustering anti-k_{t} R=0.2 jets, and are measured over the transverse momentum (p_{T}) kinematic range of 158 Collapse

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Measurement of the Sensitivity of Two-Particle Correlations in pp Collisions to the Presence of Hard Scatterings

A key open question in the study of multiparticle production in high-energy pp collisions is the relationship between the "ridge"-i.e., the observed azimuthal correlations between particles in the underlying event that extend over all rapidities-and hard or semihard scattering processes. In particular, it is not known whether jets or their soft fragments are correlated with particles in the underlying event. To address this question, two-particle correlations are measured in pp collisions at sqrt[s]=13  TeV using data collected by the ATLAS experiment at the LHC, with an integrated luminosity of 15.8  pb^{-1}, in two different configurations. In the first case, charged particles associated with jets are excluded from the correlation analysis, while in the second case, correlations are measured between particles within jets and charged particles from the underlying event. Second-order flow coefficients, v_{2}, are presented as a function of event multiplicity and transverse momentum. These measurements show that excluding particles associated with jets does not affect the measured correlations. Moreover, particles associated with jets do not exhibit any significant azimuthal correlations with the underlying event, ruling out hard processes contributing to the ridge.

Observation of an Excess of Dicharmonium Events in the Four-Muon Final State with the ATLAS Detector

A search is made for potential ccc[over ¯]c[over ¯] tetraquarks decaying into a pair of charmonium states in the four muon final state using proton-proton collision data at sqrt[s]=13  TeV, corresponding to an integrated luminosity of 140  fb^{-1} recorded by the ATLAS experiment at LHC. Two decay channels, J/ψ+J/ψ→4μ and J/ψ+ψ(2S)→4μ, are studied. Backgrounds are estimated based on a hybrid approach involving Monte Carlo simulations and data-driven methods. Statistically significant excesses with respect to backgrounds dominated by the single parton scattering are seen in the di-J/ψ channel consistent with a narrow resonance at 6.9 GeV and a broader structure at lower mass. A statistically significant excess is also seen in the J/ψ+ψ(2S) channel. The fitted masses and decay widths of the structures are reported.

An updated Catalogue of Cossoidea (Lepidoptera) from India

We catalogue 165 species in 81 genera representing six families of Cossoidea present in India. Sesiidae is the most dominant family in India, consisting 89 species in 38 genera, followed by Cossidae with 47 species in 28 genera, Brachodidae with 13 species in six genera, Metarbelidae with 12 species in seven genera, Ratardidae with three species in single genus and the Dudgeoneidae is known by single species. A comprehensive data on the species diversity of all the families of Indian Cossoidea, with information on type species, type locality, synonyms, clarifications, and distribution in different parts of India and Globe, are provided.

Test of CP Invariance in Higgs Boson Vector-Boson-Fusion Production Using the H→γγ Channel with the ATLAS Detector

A test of CP invariance in Higgs boson production via vector-boson fusion has been performed in the H→γγ channel using 139  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV collected by the ATLAS detector at the LHC. The optimal observable method is used to probe the CP structure of interactions between the Higgs boson and electroweak gauge bosons, as described by an effective field theory. No sign of CP violation is observed in the data. Constraints are set on the parameters describing the strength of the CP-odd component in the coupling between the Higgs boson and the electroweak gauge bosons in two effective field theory bases: d[over ˜] in the HISZ basis and c_{HW[over ˜]} in the Warsaw basis. The results presented are the most stringent constraints on CP violation in the coupling between Higgs and weak bosons. The 95% C.L. constraint on d[over ˜] is derived for the first time and the 95% C.L. constraint on c_{HW[over ˜]} has been improved by a factor of 5 compared to the previous measurement.

Stochastic gradient descent optimisation for convolutional neural network for medical image segmentation

In accordance with the inability of various hair artefacts subjected to dermoscopic medical images, undergoing illumination challenges that include chest-Xray featuring conditions of imaging acquisi-tion situations built with clinical segmentation. The study proposed a novel deep-convolutional neural network (CNN)-integrated methodology for applying medical image segmentation upon chest-Xray and dermoscopic clinical images. The study develops a novel technique of segmenting medical images merged with CNNs with an architectural comparison that incorporates neural networks of U-net and fully convolutional networks (FCN) schemas with loss functions associated with Jaccard distance and Binary-cross entropy under optimised stochastic gradient descent + Nesterov practices. Digital image over clinical approach significantly built the diagnosis and determination of the best treatment for a patient's condition. Even though medical digital images are subjected to varied components clarified with the effect of noise, quality, disturbance, and precision depending on the enhanced version of images segmented with the optimised process. Ultimately, the threshold technique has been employed for the output reached under the pre- and post-processing stages to contrast the image technically being developed. The data source applied is well-known in PH2 Database for Melanoma lesion segmentation and chest X-ray images since it has variations in hair artefacts and illumination. Experiment outcomes outperform other U-net and FCN architectures of CNNs. The predictions produced from the model on test images were post-processed using the threshold technique to remove the blurry boundaries around the predicted lesions. Experimental results proved that the present model has better efficiency than the existing one, such as U-net and FCN, based on the image segmented in terms of sensitivity = 0.9913, accuracy = 0.9883, and dice coefficient = 0.0246.

Taxonomic review of the Miltochrista hollowai and M. curvifascia species-groups with descriptions of two new species from India (Erebidae: Arctiinae: Lithosiini)

The Miltochrista hollowai (Kirti & Gill, 2009) and M. curvifascia (Hampson, 1891) species-groups are reviewed, and two new species belonging to the M. hollowai species-group i.e., Miltochrista madathumala sp. nov. and M. kumarkaustubhi sp. nov. are described from South India. The female of M. paraarcuata is illustrated and diagnosed for the first time. Illustrations of adults and genitalia as well as diagnoses are provided for all the species considered.

Deep Learning-Based Quantitative Assessment of Melamine and Cyanuric Acid in Pet Food Using Fourier Transform Infrared Spectroscopy

Melamine and its derivative, cyanuric acid, are occasionally added to pet meals because of their nitrogen-rich qualities, leading to the development of several health-related issues. A nondestructive sensing technique that offers effective detection must be developed to address this problem. In conjunction with machine learning and deep learning technique, Fourier transform infrared (FT-IR) spectroscopy was employed in this investigation for the nondestructive quantitative measurement of eight different concentrations of melamine and cyanuric acid added to pet food. The effectiveness of the one-dimensional convolutional neural network (1D CNN) technique was compared with that of partial least squares regression (PLSR), principal component regression (PCR), and a net analyte signal (NAS)-based methodology, called hybrid linear analysis (HLA/GO). The 1D CNN model developed for the FT-IR spectra attained correlation coefficients of 0.995 and 0.994 and root mean square error of prediction values of 0.090% and 0.110% for the prediction datasets on the melamine- and cyanuric acid-contaminated pet food samples, respectively, which were superior to those of the PLSR and PCR models. Therefore, when FT-IR spectroscopy is employed in conjunction with a 1D CNN model, it serves as a potentially rapid and nondestructive method for identifying toxic chemicals added to pet food.

To evaluate serum cortisol levels in patients with alcohol withdrawal delirium v/s patients with delirium due to any other disorder

Background

Delirium is an acute confusional state characterized by changes in the mental status, level of consciousness, impaired cognition, and inattention. It can develop within hours or days. Cortisol release from the hypothalamic-pituitary-adrenal axis (HPA) is vital for the host survival in stress. Biomarkers are used as an indicator of pathogenic processes or to assess the responses to a therapeutic intervention. To improve delirium recognition and care, investigators have identified possible biomarkers that may help in diagnosing individuals with delirium, assessing the severity of delirium. Cortisol has been suggested as biomarker for the diagnosis of delirium.

Aims and Objectives

To evaluate and compare levels of serum cortisol in patients with alcohol withdrawal delirium with delirium due to other disorders.

Materials and Methods

It was a cross-sectional prospective observational study. A total of 30 patients in Group A and 32 in Group B were included. The participants were evaluated based on delirium rating scale (DRS).

Results

It was seen that in alcohol withdrawal delirium group, there was significant positive correlation between DRS score and serum cortisol level, i.e., with increase in DRS score, there was increase in serum cortisol levels and vice versa.

Conclusion

Serum cortisol levels are associated and directly correlate with the occurrence and severity of delirium. Further studies are needed to elucidate the implications of this association for diagnosis and treatment.

Au nanogap SERS substrate for the carbaryl pesticide determination in juice and milk using chemomterics

Conventional spectroscopic methods like IR, and Raman are not very effective at detecting low levels of pesticides or harmful chemicals in food matrices. A quick, highly accurate approach that can identify pesticides present in different food products at lower levels must be developed in order to address this problem and ensure food safety. In this study, a highly sensitive and uniform wafer-scale Au nanogap surface-enhanced Raman spectroscopy (SERS) substrate was used for the quantitative analysis of carbaryl pesticide levels in standard solution, mango juice, and milk samples using chemometrics. Carbaryl was detected up to 3 ppb concentration levels for all three group of samples. However, due to the higher sensitivity, uniformity, and enhancement factors of the SERS substrate used in this investigation, the limit of detection (LOD) values for the standard solution, mango juice, and milk were 0.37 ppb, 0.57 ppb, and 0.15 ppb at 1380 cm^-1, 1380 cm^-1, and 1364 cm^-1 wavenumber ranges. In order to predict different carbaryl concentrations (1, 2, 3, 4, and 5 ppb), the variable importance in projection (VIP) method combined with partial least squares regression (PLSR) and attained the coefficient of determination (R²) values of 0.994, 0.989, and 0.978 along with minimum root mean square error (RMSE) values of 0.112, 0.190, and 0.278 ppb for the prediction datasets. Furthermore, PLS-DA was able to distinguish between pure and adulterated samples with the highest classification accuracy of 100 % for a standard solution, and mango juice and 94.4 % for milk samples. Considering this, we can conclude that the SERS Au Nanogap substrate can rapidly and effectively detect carbaryl pesticides quantitatively and qualitatively in mango juice and milk.

Surface waves and crustal structure on Mars

We detected surface waves from two meteorite impacts on Mars. By measuring group velocity dispersion along the impact-lander path, we obtained a direct constraint on crustal structure away from the InSight lander. The crust north of the equatorial dichotomy had a shear wave velocity of approximately 3.2 kilometers per second in the 5- to 30-kilometer depth range, with little depth variation. This implies a higher crustal density than inferred beneath the lander, suggesting either compositional differences or reduced porosity in the volcanic areas traversed by the surface waves. The lower velocities and the crustal layering observed beneath the landing site down to a 10-kilometer depth are not a global feature. Structural variations revealed by surface waves hold implications for models of the formation and thickness of the martian crust.

Non-destructive measurement of total phenolic compounds in Arabidopsis under various stress conditions

Quantifying the phenolic compounds in plants is essential for maintaining the beneficial effects of plants on human health. Existing measurement methods are destructive and/or time consuming. To overcome these issues, research was conducted to develop a non-destructive and rapid measurement of phenolic compounds using hyperspectral imaging (HSI) and machine learning. In this study, the Arabidopsis was used since it is a model plant. They were grown in controlled and various stress conditions (LED lights and drought). Images were captured using HSI in the range of 400-1,000 nm (VIS/NIR) and 900-2,500 nm (SWIR). Initially, the plant region was segmented, and the spectra were extracted from the segmented region. These spectra were synchronized with plants' total phenolic content reference value, which was obtained from high-performance liquid chromatography (HPLC). The partial least square regression (PLSR) model was applied for total phenolic compound prediction. The best prediction values were achieved with SWIR spectra in comparison with VIS/NIR. Hence, SWIR spectra were further used. Spectral dimensionality reduction was performed based on discrete cosine transform (DCT) coefficients and the prediction was performed. The results were better than that of obtained with original spectra. The proposed model performance yielded R 2-values of 0.97 and 0.96 for calibration and validation, respectively. The lowest standard errors of predictions (SEP) were 0.05 and 0.07 mg/g. The proposed model out-performed different state-of-the-art methods. These demonstrate the efficiency of the model in quantifying the total phenolic compounds that are present in plants and opens a way to develop a rapid measurement system.

Maternal autonomic responsiveness is attenuated in healthy pregnancy: a phase rectified signal averaging analysis

Autonomic regulation is essential in enabling a healthy pregnancy. In fact, several pregnancy complications are associated with autonomic dysfunction. Better understanding of the maternal autonomic state during healthy pregnancy may aid in the early detection of such complications. One aspect of autonomic regulation is autonomic responsiveness, which can by assessed by phase rectified signal averaging (PRSA). While other areas of research have found blunted physiological responses in pregnancy, this paper presents the first investigation of maternal autonomic responsiveness as assessed by PRSA. We find significantly reduced rates of responses, as well as an attenuated capacity for heart rate acceleration when comparing pregnant women to non-pregnant controls. We hypothesize that this attenuated autonomic control may serve to protect the mother against her imbalanced autonomic state, as increased sympathetic and decreased parasympathetic modulation accompany healthy pregnancies. Clinical Relevance- Maternal autonomic responsiveness is attenuated in pregnancy in comparison to non-pregnant women. Understanding maternal autonomic state not only improves our knowledge of gestational physiology but also forms the basis for the early detection of pregnancy complications associated with maternal autonomic dysfunction.

Caring for carers: A virtual psychosocial supervision intervention to improve the quality and sustainability of mental health and psychosocial support in humanitarian contexts

Introduction

Mental health and psychosocial support (MHPSS) staff in humanitarian settings have limited access to clinical supervision and are at high risk of experiencing burnout. We previously piloted an online, peer-supervision program for MHPSS professionals working with displaced Rohingya (Bangladesh) and Syrian (Turkey and Northwest Syria) communities. Pilot evaluations demonstrated that online, peer-supervision is feasible, low-cost, and acceptable to MHPSS practitioners in humanitarian settings.

Objectives

This project will determine the impact of online supervision on i) the wellbeing and burnout levels of local MHPSS practitioners, and ii) practitioner technical skills to improve beneficiary perceived service satisfaction, acceptability, and appropriateness.

Methods

MHPSS practitioners in two contexts (Bangladesh and Turkey/Northwest Syria) will participate in 90-minute group-based online supervision, fortnightly for six months. Sessions will be run on zoom and will be co-facilitated by MHPSS practitioners and in-country research assistants. A quasi-experimental multiple-baseline design will enable a quantitative comparison of practitioner and beneficiary outcomes between control periods (12-months) and the intervention. Outcomes to be assessed include the Kessler-6, Harvard Trauma Questionnaire and Copenhagen Burnout Inventory and Client Satisfaction Questionnaire-8.

Results

A total of 80 MHPSS practitioners will complete 24 monthly online assessments from May 2022. Concurrently, 1920 people receiving MHPSS services will be randomly selected for post-session interviews (24 per practitioner).

Conclusions

This study will determine the impact of an online, peer-supervision program for MHPSS practitioners in humanitarian settings. Results from the baseline assessments, pilot evaluation, and theory of change model will be presented.

Disclosure

No significant relationships.

Comparative Determination of Phenolic Compounds in Arabidopsis thaliana Leaf Powder under Distinct Stress Conditions Using Fourier-Transform Infrared (FT-IR) and Near-Infrared (FT-NIR) Spectroscopy

The increasing interest in plant phenolic compounds in the past few years has become necessary because of their several important physicochemical properties. Thus, their identification through non-destructive methods has become crucial. This study carried out comparative non-destructive measurements of Arabidopsis thaliana leaf powder sample phenolic compounds using Fourier-transform infrared and near-infrared spectroscopic techniques under six distinct stress conditions. The prediction analysis of 600 leaf powder samples under different stress conditions (LED lights and drought) was performed using PLSR, PCR, and NAS-based HLA/GO regression analysis methods. The results obtained through FT-NIR spectroscopy yielded the highest correlation coefficient (Rp2) value of 0.999, with a minimum error (RMSEP) value of 0.003 mg/g, based on the PLSR model using the MSC preprocessing method, which was slightly better than the correlation coefficient (Rp2) value of 0.980 with an error (RMSEP) value of 0.055 mg/g for FT-IR spectroscopy. Additionally, beta coefficient plots present spectral differences and the identification of important spectral signatures sensitive to the phenolic compounds in the measured powdered samples. Thus, the obtained results demonstrated that FT-NIR spectroscopy combined with partial least squares regression (PLSR) and suitable preprocessing method has a solid potential for non-destructively predicting phenolic compounds in Arabidopsis thaliana leaf powder samples.

Evolving Patterns of Hyperfluorescent Fundus Autofluorescence Accompany Retinal Atrophy in the Rat and Mimic Atrophic Age-Related Macular Degeneration

Purpose

Complex two-dimensional (2D) patterns of hyperfluorescent short-wave fundus autofluorescence (FAF) at the border of geographic atrophy (GA) can predict its expansion in patients with late non-exudative “dry” AMD. However, preclinical models do not phenocopy this important feature of disease. We sought to describe the spatiotemporal changes in hyperfluorescent FAF patterns that occur following acute oxidative stress, potentially in association with GA expansion.

Methods

Sprague Dawley rats (n = 54) received systemic sodium iodate (25–45 mg/kg, n = 90 eyes) or saline (n = 18 eyes) and underwent serial full fundus imaging by confocal scanning laser ophthalmoscopy, including blue FAF and delayed near-infrared analysis. Composite images of the fundus were assembled, and the 2D patterns were described qualitatively and quantitatively. A subset of eyes underwent tissue analysis, and four underwent optical coherence tomography (OCT) imaging.

Results

Reproducibly changing, complex patterns of hyperfluorescent FAF emerge at the borders of toxin-induced damage; however, in the absence of GA expansion, they percolate inward within the region of retinal pigment epithelium loss, evolving, maturing, and senescing in situ over time. Unexpectedly, the late FAF patterns most closely resemble the diffuse tricking form of clinical disease. A five-stage classification system is presented.

Conclusions

Longitudinal, full-fundus imaging of outer retinal atrophy in the rat eye identifies evolving, complex patterns of hyperfluorescent FAF that phenocopy aspects of disease.

Translational Relevance

This work provides a novel tool to assess hyperfluorescent FAF in association with progressive retinal atrophy, a therapeutic target in late AMD.

Assessment of prescribing pattern of drugs and completeness of prescriptions as per the World Health Organization prescribing indicators in various Indian tertiary care centers: A multicentric study by Rational Use of Medicines Centers-Indian Council of Medical Research network under National Virtual Centre Clinical Pharmacology activity

OBJECTIVE

The rational use of medicines as per the World Health Organization (WHO) should be practiced globally. However, data regarding the completeness of the prescriptions and their rational use is lacking from developing countries like India. Thus, the aim of this study was to assess the prescribing patterns of drugs and completeness of prescriptions as per WHO core drug use and complementary indicators to provide real-life examples for the Indian Council of Medical Research (ICMR) online prescribing skill course for medical graduates.

METHODS

Prescriptions of the patients, fulfilling inclusion criteria, attending Outpatient Departments of various specialties of tertiary care hospitals, were collected by thirteen ICMR Rational use of medicines centers located in tertiary care hospitals, throughout India. Prescriptions were evaluated for rational use of medicines according to the WHO guidelines and for appropriateness as per standard treatment guidelines using a common protocol approved by local Ethics committees.

RESULTS

Among 4838 prescriptions, an average of about three drugs (3.34) was prescribed to the patients per prescription. Polypharmacy was noted in 83.05% of prescriptions. Generic drugs were prescribed in 47.58% of the prescriptions. Further, antimicrobials were prescribed in 17.63% of the prescriptions and only 4.98% of prescriptions were with injectables. During the prescription evaluation, 38.65% of the prescriptions were incomplete due to multiple omissions such as dose, duration, and formulation.

CONCLUSION

Most of the parameters in the present study were out of the range of WHO-recommended prescribing indicators. Therefore, effective intervention program, like training, for the promotion of rational drug use practice was recommended to improve the prescribing pattern of drugs and the quality of prescriptions all over the country.

A Study of the Recent Trends of Immunology: Key Challenges, Domains, Applications, Datasets, and Future Directions

The human immune system is very complex. Understanding it traditionally required specialized knowledge and expertise along with years of study. However, in recent times, the introduction of technologies such as AIoMT (Artificial Intelligence of Medical Things), genetic intelligence algorithms, smart immunological methodologies, etc., has made this process easier. These technologies can observe relations and patterns that humans do and recognize patterns that are unobservable by humans. Furthermore, these technologies have also enabled us to understand better the different types of cells in the immune system, their structures, their importance, and their impact on our immunity, particularly in the case of debilitating diseases such as cancer. The undertaken study explores the AI methodologies currently in the field of immunology. The initial part of this study explains the integration of AI in healthcare and how it has changed the face of the medical industry. It also details the current applications of AI in the different healthcare domains and the key challenges faced when trying to integrate AI with healthcare, along with the recent developments and contributions in this field by other researchers. The core part of this study is focused on exploring the most common classifications of health diseases, immunology, and its key subdomains. The later part of the study presents a statistical analysis of the contributions in AI in the different domains of immunology and an in-depth review of the machine learning and deep learning methodologies and algorithms that can and have been applied in the field of immunology. We have also analyzed a list of machine learning and deep learning datasets about the different subdomains of immunology. Finally, in the end, the presented study discusses the future research directions in the field of AI in immunology and provides some possible solutions for the same.

Improving Constraints on Planetary Interiors With PPs Receiver Functions

Seismological constraints obtained from receiver function (RF) analysis provide important information about the crust and mantle structure. Here, we explore the utility of the free-surface multiple of the P-wave (PP) and the corresponding conversions in RF analysis. Using earthquake records, we demonstrate the efficacy of PPs-RFs before illustrating how they become especially useful when limited data is available in typical planetary missions. Using a transdimensional hierarchical Bayesian deconvolution approach, we compute robust P-to-S (Ps)- and PPs-RFs with InSight recordings of five marsquakes. Our Ps-RF results verify the direct Ps converted phases reported by previous RF analyses with increased coherence and reveal other phases including the primary multiple reverberating within the uppermost layer of the Martian crust. Unlike the Ps-RFs, our PPs-RFs lack an arrival at 7.2 s lag time. Whereas Ps-RFs on Mars could be equally well fit by a two- or three-layer crust, synthetic modeling shows that the disappearance of the 7.2 s phase requires a three-layer crust, and is highly sensitive to velocity and thickness of intra-crustal layers. We show that a three-layer crust is also preferred by S-to-P (Sp)-RFs. While the deepest interface of the three-layer crust represents the crust-mantle interface beneath the InSight landing site, the other two interfaces at shallower depths could represent a sharp transition between either fractured and unfractured materials or thick basaltic flows and pre-existing crustal materials. PPs-RFs can provide complementary constraints and maximize the extraction of information about crustal structure in data-constrained circumstances such as planetary missions.

A catalogue of Indian Arctiinae (Erebidae, Lepidoptera)

We present a catalogue of 673 species and nine subspecies of Indian Arctiinae in 175 genera which represents 6.11% of the global Arctiinae. Out of 673 species, a monogeneric tribe Amerilini is represented by four species (0.59 % of Indian Arctiinae and 6.06 % of global Amerilini), Arctiini are known by 180 species in 38 genera (26.74 % of Indian Arctiinae and 2.73% of global Arctiini), Lithosiini comprise 419 species in 128 genera (62.25% of Indian Arctiinae and 13.30% of global Lithosiini), and Syntomini account for 70 species in eight genera (10.40 % of Indian Arctiinae and 5.83% of global Syntomini). Information related to type localities, records from India with respective literature references, and the genus/ species synonyms is provided. Brief summaries for the four tribes of Indian Arctiinae, stating their Indian genus and species diversities, diagnostic characters of imagines are also provided. Furthermore, we present data on the distribution of the Arctiinae within the biogeographic zones of India. In addition, a brief analysis of the research history of Indian Arctiinae illustrates the general patterns of when and by whom the Indian species were described.

A catalogue of Nolidae Bruand, 1846 from India (Lepidoptera, Noctuoidea)

The present catalogue is the first rsum of the family Nolidae Bruand, 1846 recorded in India comprising 354 species under 98 genera of 6 subfamilies, including four new records to India: Casminola seminigra (Hampson, 1896), Evonima ronkaygabori Han Hu, 2019, Meganola suffusata (Wileman West, 1929) and Nola euryzonata (Hampson, 1900). The Indian Nolidae represents 16.2 % of the global species (2,179 species) of Nolidae. The information on the type locality, type depository, sex of the type (wherever available), first reference, synonymy, host plants (wherever available) and distribution within as well as outside India for each of the included species is provided. Some clarifications regarding type locality, type depository along with new distributional records within Indian states are also given with 72 images of adults.

Taxonomic review of the Miltochrista pudibunda (Snellen) species-group (Lepidoptera: Erebidae: Arctiinae) with description of a new species

The Miltochrista pudibunda (Snellen, 1880) species-group is reviewed. A new synonym is established: M. pudibunda = M. irregularis Rothschild, 1913, syn. nov. The species previously treated by authors (since Hampson (1900)) as M. pudibunda is described as new: M. berdepsebunda sp. nov. A lectotype female is designated for Miltochrista irregularis Rothschild, 1913. Adults together with male and female genitalia of all species of the group are illustrated, diagnoses are provided for each species.

On the taxonomy of the Prabhasa / Zadadra generic complex with descriptions of two new genera and two new species (Lepidoptera, Erebidae, Arctiinae, Lithosiini)

In the present paper, two new genera of the Prabhasa Moore, 1878 / Zadadra Moore, 1878 generic complex are described: Dentadra gen. nov. (Type species: Prabhasa flavicosta Moore, 1878) and Prabadra gen. nov. (Type species: Prabadra occidentalis sp. nov.). Additionally, two new species are described: Prabadra occidentalis sp. nov. (NE India and N Thailand) and Zadadra confusa sp. nov. (Nepal, NE India, Bhutan and W China). The new synonymy is established: Zadadra distorta Moore, 1872 = Zadadra neodistorta Joshi, Kirti N. Singh, 2015, syn. nov. Two new combinations are established: Dentadra flavicosta (Moore, 1878), comb. nov. and Prabadra monastyrskii (Dubatolov, 2012), comb. nov. The lectotype is designated for Lithosia distorta Moore, 1872. Adults, male and female genitalia are illustrated. A checklist of the Prabhasa / Zadadra generic complex is provided.

Glycosyltransferases: the multifaceted enzymatic regulator in insects

Glycosyltransferases (GTs) catalyse the reaction of glyco-conjugation of various biomolecules by transferring the saccharide moieties from an activated nucleotide sugar to nucleophilic glycosyl acceptor. In insects, GTs show diverse temporal and site-specific expression patterns and thus play significant roles in forming the complex biomolecular structures that are necessary for insect survival, growth and development. Several insects exhibit GT-mediated detoxification as a key defence strategy against plant allelochemicals and xenobiotic compounds, as well as a mechanism for pesticide cross-resistance. Also, these enzymes act as crucial effectors and modulators in various developmental processes of insects such as eye development, UV shielding, cuticle formation, epithelial development and other specialized functions. Furthermore, many of the known insect GTs have been shown to play a fundamental role in other physiological processes like body pigmentation, cuticular tanning, chemosensation and stress response. This review provides a detailed overview of the multifaceted functionality of insect GTs and summarizes numerous case studies associated with it.

Left ventricular function and clinical heart failure after myocardial infarction revascularized with percutaneous coronary intervention - comparison between STEMI and NSTEMI in modern practice

Funding Acknowledgements

Type of funding sources: None.

Introduction

Left ventricular systolic dysfunction (LVSD) is a common consequence of myocardial infarction (MI). Data from historic series identified LVSD in up to 60% of patients post-MI. However, in modern practice, with high-sensitivity cardiac biomarkers leading to early detection of MI and widespread use of early revascularization, the prevalence of LVSD in the acute phase of MI and its impact on subsequent clinical heart failure remains unknown.

Purpose

To ascertain the prevalence of LVSD on pre-discharge echocardiography and its impact on subsequent clinical heart failure after type 1 MI treated with percutaneous coronary intervention (PCI) in a UK tertiary cardiac centre.

Methods

A retrospective electronic patient records review of consecutive patients with type 1 MI treated with PCI between January 2016 - December 2017. Patients treated conservatively or with surgical revascularization were excluded.

Results

1000 consecutive patients were identified and 948/1000 who had an inpatient echocardiogram prior to discharge were included in this analysis – 413 ST elevation MI (STEMI) and 535 non-ST elevation (NSTEMI). Median door to balloon time for STEMI was 42 minutes (IQR 28-79). Median time from symptom onset to intervention for NSTEMI was 3 days (IQR 1-6). LVSD was defined as left ventricular ejection fraction (LVEF) <50% on transthoracic echocardiogram carried out during the hospital episode. LVSD was significantly more prevalent in patients with STEMI compared to NSTEMI (37.4% vs 17.3%, p < 0.001). Median LVEF was significantly lower in the STEMI population (55%, IQR 45-60) compared to patients with NSTEMI (60%, IQR 54-65), p < 0.001. However, rates of clinical heart failure at index presentation with MI did not vary significantly between STEMI and NSTEMI patients (6.1% vs 4.9%, p = 0.414). In stepwise multivariate regression models: age, peak troponin and previous coronary artery bypass grafting were predictors of LVEF, whereas LVEF and previous MI were predictors of clinical heart failure

Patients with LVSD on pre-discharge echocardiography had significantly higher rates of 30-day readmission with heart failure (2.9% vs 0.7%, p = 0.017), 30-day all-cause mortality (6.1% vs 2%, p = 0.001), 30-day cardiac mortality (5.7% vs 1%, p < 0.001) and 2-year all-cause mortality (5.7% vs 1.6%, p = 0.001). However, at 2-years, there was no difference in hospital readmission with heart failure (0.8% vs 0.3%, p = 0.276). There were no significant differences between STEMI and NSTEMI patients for these endpoints.

Conclusions

Early revascularisation with PCI has led to a reduction in the prevalence of early LVSD post-MI compared to historical data. However, the presence of LVSD remains a powerful predictor of adverse clinical outcomes. Despite lower rates of LVSD on pre-discharge echocardiography in patients with NSTEMI compared with STEMI, the incidence of subsequent clinical heart failure is similar. This however may be underestimated due to survival bias.

A randomized controlled trial studying the effect of maternal hyperoxygenation on fetal heart rate in suspected fetal distress

OBJECTIVE

To investigate the effect of maternal hyperoxygenation on fetal heart rate (FHR) when applied for suspected fetal distress during the second stage of term labor.

APPROACH

A single-center randomized controlled trial was conducted in a tertiary care hospital in The Netherlands. Participants were included during the second stage of labor in case of an intermediary or abnormal FHR pattern. Patients were randomized to receive either 100% oxygen at 10 l/min until delivery, or conventional care without additional oxygen. The primary outcome was the change in FHR pattern before and after the onset of the study, measured as the change in depth and duration of FHR decelerations. Secondary outcome measures were features based on phase-rectified signal averaging (PRSA), baseline assignability, and deceleration characteristics of the FHR pattern.

MAIN RESULTS

Between March 2016 and April 2018, 117 women were included. The FHR pattern could be analyzed for 71 participants, the other 46 women delivered before the end of the post time-frame. A 2.3% reduction in depth and duration of FHR decelerations was found after maternal hyperoxygenation, compared to a 10% increase in the control group (p = 0.24). Maternal hyperoxygenation had a significantly positive effect on PRSA metrics, with a decrease in PRSA-acceleration capacity (p = 0.03) and PRSA-deceleration capacity (p = 0.02) in the intervention group compared to the control group.

SIGNIFICANCE

The difference in depth and duration of decelerations after the start of the study was not significantly different between both study groups. A statistically significant positive effect on PRSA-deceleration capacity and PRSA-acceleration capacity was found after maternal hyperoxygenation, which might be associated with a positive effect on neonatal outcome.

Mapping genes for phosphorus utilization and correlated traits using a 4k SNP linkage map in Japanese quail (Coturnix japonica)

A large F2 cross with 920 Japanese quail was used to map QTL for phosphorus utilization, calcium utilization, feed per gain and body weight gain. In addition, four bone ash traits were included, because it is known that they are genetically correlated with the focal trait of phosphorus utilization. Trait recording was done at the juvenile stage of the birds. The individuals were genotyped genome-wide for about 4k SNPs and a linkage map constructed, which agreed well with the reference genome. QTL linkage mapping was performed using multimarker regression analysis in a line cross model. Single marker association mapping was done within the mapped QTL regions. The results revealed several genome-wide significant QTL. For the focal trait phosphorus utilization, a QTL on chromosome CJA3 could be detected by linkage mapping, which was substantiated by the results of the SNP association mapping. Four candidate genes were identified for this QTL, which should be investigated in future functional studies. Some overlap of QTL regions for different traits was detected, which is in agreement with the corresponding genetic correlations. It seems that all traits investigated are polygenic in nature with some significant QTL and probably many other small-effect QTL that were not detectable in this study.

Ischaemic mitral regurgitation: incidence, clinical and angiographic characteristics of 1000 patients with type 1 myocardial infarction undergoing percutaneous coronary intervention

Background

Previous studies of the incidence and severity of mitral regurgitation (MR) following acute myocardial infarction (MI) were limited by the study population (ST-elevation MI only), by diagnostic methods (lack of multiparametric quantification), or by the time-frame of study (late assessment post-MI). The true incidence of ischaemic MR (IMR) immediately following type 1 MI [non-ST-elevation (NSTEMI) and ST-elevation (STEMI)] patients in the modern era of universal early revascularisation remains unclear. Since even mild IMR confers a poor prognosis, factors which promote or protect against the development of MR require further evaluation.

Purpose

To determine the incidence, clinical and angiographic characteristics of patients with IMR following type 1 MI treated with PCI.

Methods

This was a single-centre study of 1000 consecutive, prospectively recruited patients admitted to the Queen Elizabeth Hospital Birmingham with type 1 MI who underwent PCI. Early inpatient transthoracic echocardiography (TTE) was performed by accredited echocardiographers using standard multiparametric quantification.

Results

MR was observed in 294/1000 patients (29.4%) post-MI, graded as mild (76%), moderate (21%) and severe (3%). Median time from symptom onset to PCI was 1 day (IQR 0–4) and to TTE 2 days (IQR 1–3).

Compared to patients without MR (MR-), those with MR (MR+) were older (73±12 years vs 66±13 years; p<0.001), male (75% vs 64%; p<0.001) and more likely to have a history of hypertension (HTN) (63% vs 55%; p=0.0117), heart failure (HF) (3.4% vs 1.1%; p=0.0140) and previous MI (28% vs 20%; p<0.005). MR+ patients more frequently presented with HF (8.5% vs 4.2%; p=0.0075), lower LV ejection fraction (LVEF) (50±14% vs 55±11%; p<0.001) and higher peak high sensitivity troponin T (765ng/L, IQR 170–3032 vs 400ng/L, IQR 51–1966; p<0.0001).

MR+ patients were more likely to have severe disease in the left circumflex (LCx) (50% vs 33%; p<0.0001) or right coronary artery (RCA) (51% vs 43%; p=0.0135). Incidence of severe disease in the left main stem and left anterior descending artery (LAD) did not significantly differ between the two groups.

Incidence of MR was equal (29%) amongst STEMI (126/431) and NSTEMI (168/569) patients. While the time to revascularisation did not affect the prevalence of MR following STEMI (linear regression analysis of door-to-balloon time in MR+ and MR- patients p=0.843), NSTEMI patients were more likely to develop MR if revascularisation was delayed (linear regression analysis of symptom onset to PCI time MR+ vs MR- p=0.061).

Conclusion

Almost 1/3 of patients with type 1 MI undergoing revascularisation have MR evident on pre-discharge TTE. Factors promoting MR include older age, male sex, HTN, HF, larger non-LAD territory infarct, and depressed LVEF. The incidence of MR following STEMIs and NSTEMIs is equal. Earlier revascularisation is unlikely to reduce MR in STEMI patients but may improve MR prevalence following NSTEMI.

Funding Acknowledgement

Type of funding source: None

Risk stratification on echocardiography and outcome in ischaemic mitral regurgitation

Background

Ischaemic mitral regurgitation (IMR) confers a poor prognosis. Transcatheter intervention may improve survival but benefit is likely to depend on severity of IMR relative to LV remodelling following myocardial infarction (MI). In theory, those with “discordant” IMR (significant regurgitant volume without severe LV dilatation or impairment), are expected to benefit most from mitral intervention. While subcategorization may help to inform treatment, there are no data on post-MI patients in this respect.

Purpose

To determine the incidence of discordant & concordant IMR categorised on echocardiography post-MI and impact on outcomes.

Methods

1000 consecutive patients admitted to our hospital with myocardial infarction who underwent coronary angioplasty were included. Early inpatient TTE was performed by accredited echocardiographers using standard multiparametric quantification.

Using TTE parameters, 4 subgroups were identified (figure) according to the degree of MR relative to LV remodelling. Thresholds were based on European guidelines (± 2SD from normal) and median value among survivors for vena contracta (VC):

– LVEF: 52% (♂), 54% (♀)

– Indexed LV end diastolic volume (LVEDVi): 74ml/m2 (♂), 61ml/m2 (♀)

– Effective regurgitant orifice area (EROA) ≥0.2cm2

– Regurgitant volume (RVol) ≥30ml

– VC ≥0.5cm

Results

MR was seen in 294/1000 patients (29.4%) with a severity of mild (76%), moderate (21%) and severe (3%). Concordant and discordant IMR were each seen in 16/294 (5%) of IMR patients post-MI.

After a mean follow up of 3.2 years, IMR patients had a 3% rate of heart failure (HF) within 1 year and 19% mortality. Non-survivors had significantly worse IMR (PISA 0.65±0.25cm vs 0.54±0.19cm; p=0.033; VC 0.63±0.25cm vs 0.49±0.18cm; p=0.014), worse LV function (LVEF 44±17% vs 51±13%; p<0.001), larger LV (LVEDVi 67±23ml/m2 vs 60±22ml/m2; p=0.032) and larger indexed LA volume (LAVi) (44±22ml vs 35±15ml; p<0.001). Those with concordant IMR had the worst survival (50%) although almost 1 in 5 of those with discordant MR died within the follow up period (19%). Using multivariable Cox regression, significant predictors of mortality included LVEF (p<0.001; HR 0.96, 0.94–0.98) and LAVi (p<0.001; HR 1.02, 1.01–1.03) but not LVEDVi.

Conclusion

1) Significant predictors of mortality in IMR include LA dilatation and decline in LVEF, but not LV dilatation.

2) Although discordant severe IMR is uncommon following MI, mortality if left untreated remains high. Attention should be paid to early selection of this cohort for intervention.

Funding Acknowledgement

Type of funding source: None

Hyperspectral Shortwave Infrared Image Analysis for Detection of Adulterants in Almond Powder with One-Class Classification Method

The widely used techniques for analyzing the quality of powdered food products focus on targeted detection with a low-throughput screening of samples. Owing to potentially significant health threats and large-scale adulterations, food regulatory agencies and industries require rapid and non-destructive analytical techniques for the detection of unexpected compounds present in products. Accordingly, shortwave-infrared hyperspectral imaging (SWIR-HSI) for high throughput authenticity analysis of almond powder was investigated in this study. Two different varieties of almond powder, adulterated with apricot and peanut powder at different concentrations, were imaged using the SWIR-HSI system. A one-class classifier technique, known as data-driven soft independent modeling of class analogy (DD-SIMCA), was used on collected data sets of pure and adulterated samples. A partial least square regression (PLSR) model was further developed to predict adulterant concentrations in almond powder. Classification results from DD-SIMCA yielded 100% sensitivity and 89-100% specificity for different validation sets of adulterated samples. The results obtained from the PLSR analysis yielded a high determination coefficient (R2) and low error values (<1%) for each variety of almond powder adulterated with apricot; however, a relatively higher error rates of 2.5% and 4.4% for the two varieties of almond powder adulterated with peanut powder, which indicates the performance of quantitative analysis model could vary with sample condition, such as variety, originality, etc. PLSR-based concentration mapped images visually characterized the adulterant (apricot) concentration in the almond powder. These results demonstrate that the SWIR-HSI technique combined with the one-class classifier DD-SIMCA can be used effectively for a high-throughput quality screening of almond powder regarding potential adulteration.