COVID-19 Stroke Apical Lung Examination Study 2: a national prospective CTA biomarker study of the lung apices, in patients presenting with suspected acute stroke (COVID SALES 2)

BACKGROUND

Apical ground-glass opacification (GGO) identified on CT angiography (CTA) performed for suspected acute stroke was developed in 2020 as a coronavirus-disease-2019 (COVID-19) diagnostic and prognostic biomarker in a retrospective study during the first wave of COVID-19.

OBJECTIVE

To prospectively validate whether GGO on CTA performed for suspected acute stroke is a reliable COVID-19 diagnostic and prognostic biomarker and whether it is reliable for COVID-19 vaccinated patients.

METHODS

In this prospective, pragmatic, national, multi-center validation study performed at 13 sites, we captured study data consecutively in patients undergoing CTA for suspected acute stroke from January-March 2021. Demographic and clinical features associated with stroke and COVID-19 were incorporated. The primary outcome was the likelihood of reverse-transcriptase-polymerase-chain-reaction swab-test-confirmed COVID-19 using the GGO biomarker. Secondary outcomes investigated were functional status at discharge and survival analyses at 30 and 90 days. Univariate and multivariable statistical analyses were employed.

RESULTS

CTAs from 1,111 patients were analyzed, with apical GGO identified in 8.5 % during a period of high COVID-19 prevalence. GGO showed good inter-rater reliability (Fleiss κ = 0.77); and high COVID-19 specificity (93.7 %, 91.8-95.2) and negative predictive value (NPV; 97.8 %, 96.5-98.6). In subgroup analysis of vaccinated patients, GGO remained a good diagnostic biomarker (specificity 93.1 %, 89.8-95.5; NPV 99.7 %, 98.3-100.0). Patients with COVID-19 were more likely to have higher stroke score (NIHSS (mean +/- SD) 6.9 +/- 6.9, COVID-19 negative, 9.7 +/- 9.0, COVID-19 positive; p = 0.01), carotid occlusions (6.2 % negative, 14.9 % positive; p = 0.02), and larger infarcts on presentation CT (ASPECTS 9.4 +/- 1.5, COVID-19 negative, 8.6 +/- 2.4, COVID-19 positive; p = 0.00). After multivariable logistic regression, GGO (odds ratio 15.7, 6.2-40.1), myalgia (8.9, 2.1-38.2) and higher core body temperature (1.9, 1.1-3.2) were independent COVID-19 predictors. GGO was associated with worse functional outcome on discharge and worse survival after univariate analysis. However, after adjustment for factors including stroke severity, GGO was not independently predictive of functional outcome or mortality.

CONCLUSION

Apical GGO on CTA performed for patients with suspected acute stroke is a reliable diagnostic biomarker for COVID-19, which in combination with clinical features may be useful in COVID-19 triage.

Solvent directed morphogenesis of a peptidic-benzimidazolium dipodal receptor: ratiometric detection and catalytic degradation of ochratoxin A

Ochratoxin A (OTA) is the most abundant and harmful toxin found in agriculture and processed food. The environment and human health are both harmed by this mycotoxin. As a result, in various scenarios, selective detection and biodegradation of ochratoxin A are essential. The current study reveals the morphogenesis of a peptidic-benzimidazolium dipodal receptor (SS4) and its application as a catalytic and sensing unit for the detection and degradation of OTA in an aqueous medium. Initially, a facile and scalable method was executed to synthesize SS4, and solvent-directed morphogenesis were examined under SEM analysis. Consequently, molecular recognition properties of self-assembled architectures were explored using UV-visible absorption, fluorescence spectroscopy, and atomic force microscopy (AFM). The designed probe showed a ratiometric response for OTA and served as a catalytic unit for the degradation of OTA at a short interval of 25 min. The biodegradation pathway for OTA was accomplished using LC-MS analysis. Furthermore, the reliability of the developed method was checked by determining the spiked concentrations of the OTA in cereals and wine samples. The results obtained are in good agreement with the % recovery and RSD values. The present work provides a robust, selective, and sensitive method of detection and degradation for OTA.

Measurement of the ^{13}C(α, n_{0})^{16}O Differential Cross Section from 0.8 to 6.5 MeV

The cross section of the ^{13}C(α,n)^{16}O reaction is needed for nuclear astrophysics and applications to a precision of 10% or better, yet inconsistencies among 50 years of experimental studies currently lead to an uncertainty of ≈15%. Using a state-of-the-art neutron detection array, we have performed a high resolution differential cross section study covering a broad energy range. These measurements result in a dramatic improvement in the extrapolation of the cross section to stellar energies potentially reducing the uncertainty to ≈5% and resolving long standing discrepancies in higher energy data.

Core-Labeled Reverse Micelle-Based Supramolecular Solvents for Assisted Quick and Sensitive Determination of Amitriptyline in Wastewater

In recent years, the issue of pharmaceutical contaminants in water bodies has emerged as a significant environmental concern owing to the potential negative impacts on both aquatic ecosystems and human health. Consequently, the development of efficient and eco-friendly methods for their determination and removal is of paramount importance. In this context, the development of a surfactant ensemble sensor has been explored for hard-to-sense amphiphilic drug, i.e., amitriptyline. Herein, a pyrene-based amphiphile chemoreceptor was synthesized and characterized through various spectroscopic techniques such as 1H, 13C NMR, single-crystal XRD, FTIR, and ES-mass spectrometry. Then, dodecanoic acid (DA) and a pyrene-based receptor in a THF/water solvent system were used to generate reverse micelle-based self-aggregates of SUPRAS (SUPRAmolecular Solvent). The structural aspects, such as morphology and size, along with the stability of the SUPRAS aggregates were unfolded through spectroscopic and microscopic insights. The present investigation describes a synergistic approach that combines the unique properties of premicellar concentration of supramolecular solvent with the promising potential of pyrene-based receptor for enhanced amitriptyline extraction with simultaneous determination from water (LOD = 12 nM). To evaluate the effectiveness of the developed aggregates in real-world scenarios, experiments were conducted to determine the sensing efficiency among various pharmaceutical pollutants commonly found in water sources. The results reveal that the synergistic nanoensemble exhibits remarkable sensing ability, toward the amitriptyline (AMT) drug outperforming conventional methods.

Deciphering Intermediate Nugent scores: Utility of Real-time PCR for Bacterial Vaginosis diagnosis

PURPOSE

To optimize real-time PCR assays for diagnosis of Bacterial Vaginosis (BV) and determine cut-off loads by ROC analysis for Gardnerella vaginalis, Atopobium vaginae and Lactobacillus spp. as compared to Nugent scoring (Gold standard) in clinical samples.

RESULTS

Out of 125 women, 34 were positive, 26 intermediate and 65 negative for BV by Nugent scoring. All three real-time PCR assays were found to be highly sensitive & specific and AUC suggested excellent diagnostic accuracy. An optimal cut-off was >9.45 × 103 copies/ ml, >3.34 × 103 copies/ ml & ≤ 18.63 × 103 copies/ ml for G. vaginalis, A. vaginae and Lactobacillus spp. respectively, in BV positives. Gram staining and qPCR were discordant only in patients with intermediate scores (n = 26) where qPCR identified 15 (57.69%) as positive and 11 (42.3%) as negative.

CONCLUSION

PCR-based molecular BV diagnosis is more accurate and can be used for deciphering intermediate Nugent scores.

Effect of protective coating agents on microleakage and flexural strength of glass ionomer cement and zirconomer. an in vitro study

PURPOSE

The objective of this study was to assess the microleakage and flexural strength of glass ionomer cement (GIC) and modified GIC (Zirconomer) when coated with protective coating agents such as COAT-IT and G-COAT plus.

METHODS

Sixty tooth specimens were grouped into two groups based on the type of restorations (GIC (n = 30) and Zirconomer (n = 30)). The samples were further divided into three subgroups (n = 10) based on the protective coating agent (Petroleum jelly, G-COAT Plus, or COAT IT) applied. This study evaluated the microleakage at the occlusal and cervical margins of class V restoration after being subjected to dye penetration and sectioning. Each specimen was viewed under a 40 × microscope and was given scores based on the depth of dye penetration. They were statistically analyzed using the Kruskal-Wallis test and compared within the groups using the Mann- Whitney Test. In addition, flexural strength was assessed using standardized cuboid (25 × 2 × 2 mm) specimens of restorative materials with and without protective coating agents. The mean flexural strength data of all the subgroups were statistically evaluated using a one-way analysis of variance (ANOVA) and compared within the subgroups using the student t test.

RESULTS

A statistically significant difference was found when occlusal margin microleakage scores were evaluated with G-COAT Plus demonstrating the lowest occlusal margin microleakage when applied over GIC restoration. The increasing order of occlusal margin microleakage scores is as follows: GIC with G-COAT Plus, Zirconomer with COAT-IT, GIC with COAT-IT, GIC, Zirconomer with G-COAT Plus, and Zirconomer. However, the cervical margin microleakage scores revealed no significant difference. While flexural strength was found to be highest for the GIC group coated with G-COAT Plus, it was observed that there was a significant improvement in the flexural strength of both GIC and Zirconomer when coated with either of the protective coating agents.

CONCLUSION

Within the limitations of this in vitro study, it was observed that the application of protective coating agents can significantly reduce the potential microleakage and improve the flexural strength of the restorative material especially when zirconia-reinforced GIC is the restorative material.

Simple turn-on fluorescent chemosensor for ultrafast and highly selective trace-level detection of Cu2+ ions in aqueous solutions

A benzimidazole-based probe, BIPMA (2-(1H-benzo[d]imidazol-2-yl)-N-(pyridin-2-ylmethyl)aniline), was designed and synthesized to detect Cu2+ ions. BIPMA exhibited a fluorescent "turn-on" mechanism when bound to Cu2+ ions in an acetonitrile/water mixture (5:5, v/v, HEPES 10 mM, pH 7.4) owing to the synergistic effect of the chelation-enhanced fluorescence and internal charge-transfer mechanisms. Moreover, the BIPMA probe effectively detected nanomolar-range concentrations (0-400 nM) of Cu2+ ions in an aqueous system with a detection limit of 4.80 nM; this value is significantly lower than that set by the U.S. Environmental Protection Agency (≈20 μM). Additionally, BIPMA showed an ultrafast response to Cu2+ ions, with a maximum intensity achieved 25 s after adding Cu2+. Furthermore, BIPMA detected Cu2+ ions in solutions with a pH range of 5-11, without being influenced by pH, underscoring its applicability under various physiological conditions. Density functional theory studies revealed that internal charge transfer was responsible for emission. Finally, BIPMA effectively detected Cu2+ ions in real water samples and living cells.

Implementing systematic melanoma risk assessment and risk-tailored surveillance in a skin cancer focussed dermatology clinic: A qualitative study of feasibility and acceptability to patients and clinic staff

BACKGROUND

International bodies recommend that melanoma risk assessment should be integrated into skin cancer care provision, but evidence to support implementation is lacking.

AIM

To explore the acceptability and feasibility of implementing personalised melanoma risk assessment and tailored patient education and skin surveillance within routine clinical care.

METHODS

This prospective qualitative implementation study was informed by the Theoretical Framework of Acceptability (TFA). Personalised, systematic melanoma risk assessment was implemented in the dermatology clinic at the Melanoma Institute Australia, Sydney, Australia February-May 2021. Pre- and post-implementation observations and semi-structured interviews with patients and staff were conducted (September 2020-March 2021). Observational notes and interview transcript data were analysed thematically using the TFA as a classifying framework.

RESULTS

A total of 37 h of observations were made, and 29 patients and 12 clinic staff were interviewed. We found that the delivery of personalised melanoma risk estimates did not impact on patient flow through the clinic. Dermatologists reported that the personalised risk information enhanced their confidence in assessing patient risk and recommending tailored surveillance schedules. Most patients reported that the risk assessment and tailored information were a beneficial addition to their care. Among patients whose risk deviated from their expectations, some reported feeling worried, confused or mistrust in the risk information, including those at lower risk who were recommended to decrease surveillance frequency.

CONCLUSIONS

It is feasible and acceptable to patients and clinic staff to calculate and deliver personalised melanoma risk information and tailored surveillance as part of routine clinical care within dermatology clinics.

Modelling the effects of post-FESS middle turbinate synechiae on sinonasal physiology: A computational fluid dynamics study

OBJECTIVE(S)

Chronic rhinosinusitis (CRS) is common and often requires surgical intervention. Surgical failure may lead to persistent symptoms and recalcitrant disease, often secondary to synechiae between the middle turbinate (MT) and lateral nasal wall. Synechiae prevention techniques have been extensively investigated, however evidence for the effect of synechiae on sinonasal physiology is lacking. We aimed to model the effects of MT synechiae on a post-functional endoscopic sinus surgery (FESS) sinonasal cavity using computational fluid dynamics (CFD).

METHODS

DICOM data from a CT-sinus of a healthy 25-year-old female was segmented to create a three-dimensional model. Virtual surgery was performed to simulate a "full-house" FESS procedure. Multiple models were created, each with a single unilateral virtual MT synechia of varying extent. CFD analysis was performed on each model and compared with a post-FESS control model without synechiae. Airflow velocity, humidity and mucosal surface and air temperature values were calculated.

RESULTS

All synechiae models demonstrated aberrant downstream sinonasal airflow. There was reduced ventilation of the ipsilateral frontal, ethmoid and sphenoid sinuses, with a concentrated central "jet" in the middle meatus region. Effects were proportionate to the size of synechiae. The impact on bulk inspired airflow was negligible.

CONCLUSION

Post-FESS synechiae between the MT and lateral nasal wall significantly disrupt local downstream sinus ventilation and nasal airflow. These findings may explain the persistent symptoms seen in post-FESS CRS patients with MT synechiae, reinforcing the importance of prevention and adhesiolysis. Larger cohort studies with multiple models of actual post-FESS patients with synechiae are required to validate these findings.

An artificial intelligence algorithm for the classification of sphenoid sinus pneumatisation on sinus computed tomography scans

BACKGROUND

Classifying sphenoid pneumatisation is an important but often overlooked task in reporting sinus CT scans. Artificial intelligence (AI) and one of its key methods, convolutional neural networks (CNNs), can create algorithms that can learn from data without being programmed with explicit rules and have shown utility in radiological image classification.

OBJECTIVE

To determine if a trained CNN can accurately classify sphenoid sinus pneumatisation on CT sinus imaging.

METHODS

Sagittal slices through the natural ostium of the sphenoid sinus were extracted from retrospectively collected bone-window CT scans of the paranasal sinuses for consecutive patients over 6 years. Two blinded Otolaryngology residents reviewed each image and classified the sphenoid sinus pneumatisation as either conchal, presellar or sellar. An AI algorithm was developed using the Microsoft Azure Custom Vision deep learning platform to classify the pattern of pneumatisation.

RESULTS

Seven hundred eighty images from 400 patients were used to train the algorithm, which was then tested on a further 118 images from 62 patients. The algorithm achieved an accuracy of 93.2% (95% confidence interval [CI] 87.1-97.0), 87.3% (95% CI 79.9-92.7) and 85.6% (95% CI 78.0-91.4) in correctly identifying conchal, presellar and sellar sphenoid pneumatisation, respectively. The overall weighted accuracy of the CNN was 85.9%.

CONCLUSION

The CNN described demonstrated a moderately accurate classification of sphenoid pneumatisation subtypes on CT scans. The use of CNN-based assistive tools may enable surgeons to achieve safer operative planning through routine automated reporting allowing greater resources to be directed towards the identification of pathology.

Portable Sensor Array for On-Site Detection and Discrimination of Pesticides and Herbicides Using Multivariate Analysis

Modern agricultural practice relies heavily on pesticides and herbicides to increase crop productivity, and consequently, their residues have a negative impact on the environment and public health. Thus, keeping these issues in account, herein we developed an azodye-based chromogenic sensor array for the detection and discrimination of pesticides and herbicides in food and soil samples, utilizing machine learning approaches such as hierarchical clustering analysis, principal component analysis, linear discriminant analysis (LDA), and partial least square regression (PLSR). The azodye-based sensor array was developed in combination with various metal ions owing to their different photophysical properties, which led to distinct patterns toward various pesticides and herbicides. The obtained distinct patterns were recognized and processed through automated multivariate analysis, which enables the selective and sensitive identification and discrimination of various target analytes. Further, the qualitative and quantitative determination of target analytes were performed using LDA and PLSR; the results obtained show a linear correlation with varied concentrations of target analytes with R2 values from 0.89 to 0.96, the limit of detection from 5.3 to 11.8 ppm with a linear working range from 1 to 30 μM toward analytes under investigation. Further, the developed sensor array was successfully utilized for the discrimination of a binary mixture of pesticide (chlorpyrifos) and herbicide (glyphosate).

A Deep Learning Algorithm to Identify Anatomical Landmarks on Computed Tomography of the Temporal Bone

BACKGROUND

Petrous temporal bone cone-beam computed tomography scans help aid diagnosis and accurate identification of key operative landmarks in temporal bone and mastoid surgery. Our primary objective was to determine the accuracy of using a deep learning convolutional neural network algorithm to augment identification of structures on petrous temporal bone cone-beam computed tomography. Our secondary objective was to compare the accuracy of convolutional neural network structure identification when trained by a senior versus junior clinician.

METHODS

A total of 129 petrous temporal bone cone-beam computed tomography scans were obtained from an Australian public tertiary hospital. Key intraoperative landmarks were labeled in 68 scans using bounding boxes on axial and coronal slices at the level of the malleoincudal joint by an otolaryngology registrar and board-certified otolaryngologist. Automated structure identification was performed on axial and coronal slices of the remaining 61 scans using a convolutional neural network (Microsoft Custom Vision) trained using the labeled dataset. Convolutional neural network structure identification accuracy was manually verified by an otolaryngologist, and accuracy when trained by the registrar and otolaryngologist labeled datasets respectively was compared.

RESULTS

The convolutional neural network was able to perform automated structure identification in petrous temporal bone cone-beam computed tomography scans with a high degree of accuracy in both axial (0.958) and coronal (0.924) slices (P < .001). Convolutional neural network accuracy was proportionate to the seniority of the training clinician in structures with features more difficult to distinguish on single slices such as the cochlea, vestibule, and carotid canal.

CONCLUSION

Convolutional neural networks can perform automated structure identification in petrous temporal bone cone-beam computed tomography scans with a high degree of accuracy, with the performance being proportionate to the seniority of the training clinician. Training of the convolutional neural network by the most senior clinician is desirable to maximize the accuracy of the results.

Local and systemic inflammatory response to the intrauterine infusion of enzymes during estrus in water buffaloes with subclinical endometritis

Our objective was to determine the effects of intrauterine infusion of proteolytic enzymes in buffaloes with subclinical endometritis (SCE) at estrus on the resolution of endometrial inflammation and reproductive performance. Buffaloes at spontaneous estrus (E1) were screened for SCE by endometrial cytology to identify SCE (≥5% PMN, n = 22) and non-SCE (<5% PMNs, n = 14) animals. All buffaloes underwent uterine ultrasonographic examination, low volume uterine lavage (cytokines and acute phase proteins) and blood sampling (cytokines and acute-phase proteins) at E1. On the same day (E1), SCE buffaloes were randomly selected either for intrauterine infusion of proteolytic enzymes (ENY, n = 11) or saline (PC, n = 11). Buffaloes without SCE were kept as untreated control (NC; n = 14). All buffaloes were re-examined and re-sampled during subsequent estrus (E2), inseminated during the following estrus (E3), and assessed for fertility related outcomes. Proteolytic infusion resulted a reduction in uterine PMN (P < 0.01) in SCE buffaloes. The concentrations of interleukin (IL)-1β and tumor necrosis factor (TNF)-α in uterus, and TNF-α and IL-10 in serum were higher (P < 0.01) at E1 in buffaloes with SCE (PC and ENY) compared to NC. After treatment, uterine IL-1β and TNF-α (P = 0.02), and serum TNF-α and IL-10 were lower within the animals of ENY group (P < 0.01). Before treatment, buffaloes with SCE had higher concentrations (P < 0.01) of serum and uterine amyloid-A and haptoglobin, which decreased (P < 0.01) after treatment in the ENY group. None of the fertility outcomes differ between the treatment groups. In conclusion, intrauterine infusion of proteolytic enzymes reduced endometrial inflammation; however, did not improve reproductive outcomes.

Fabrication of FRET based nano sensor from biomass-derived fluorescent carbon quantum dots and naphthalimide for ratiometric detection of nitric oxide: To examine nitrite levels in meat samples

Nitric oxide (NO) is a ubiquitous, gaseous, free radical signaling molecule which plays a key role in physiological and pathological processes. Literature reports revealed that the conventional methods such as colorimetry, electron paramagnetic resonance (EPR), electrochemical etc. to detect NO are costly, time consuming and lack resolution, particularly in aqueous or biological system. Thus, in this context, herein we have developed covalently linked biomass derived carbon quantum dots (CQDs) and naphthalimide based nano sensor system for FRET based ratiometric detection of nitric oxide (NO) in pure aqueous media. The CQDs derived from orange peels were characterized using UV-visible absorption, fluorescence spectroscopy, PXRD, TEM, FT-IR and zeta potential studies. Further, the obtained CQDs were functionalized with amine functionality, and subsequently linked with naphthalimide derivative (5) using terephthaldehyde through covalent bond formation. The conjugation of naphthalimide (5) and functionalized CQDs was studied using DLS, zeta potential, FT-IR and time resolved fluorescence spectroscopy. The excitation of developed nano sensor system at λ_ex 360 nm results in fluorescence emission at λ_em 530 nm which establishes the FRET pair between the CQDs and naphthalimide unit. However, in the presence of NO, the observed FRET pair abolishes due to the cleavage of NO susceptible imine bond. The developed sensor demonstrates high selectivity towards NO with limit of detection (LOD) and limit of quantification (LOQ) of 15 nM and 50 nM respectively. Further, the developed sensor system was also utilized for indirect detection of nitrite (NO₂^-) in food samples for food safety and monitoring.

Frequency-Dependent Squeezed Vacuum Source for the Advanced Virgo Gravitational-Wave Detector

In this Letter, we present the design and performance of the frequency-dependent squeezed vacuum source that will be used for the broadband quantum noise reduction of the Advanced Virgo Plus gravitational-wave detector in the upcoming observation run. The frequency-dependent squeezed field is generated by a phase rotation of a frequency-independent squeezed state through a 285 m long, high-finesse, near-detuned optical resonator. With about 8.5 dB of generated squeezing, up to 5.6 dB of quantum noise suppression has been measured at high frequency while close to the filter cavity resonance frequency, the intracavity losses limit this value to about 2 dB. Frequency-dependent squeezing is produced with a rotation frequency stability of about 6 Hz rms, which is maintained over the long term. The achieved results fulfill the frequency dependent squeezed vacuum source requirements for Advanced Virgo Plus. With the current squeezing source, considering also the estimated squeezing degradation induced by the interferometer, we expect a reduction of the quantum shot noise and radiation pressure noise of up to 4.5 dB and 2 dB, respectively.

The role of dexmedetomidine in post cranioplasty refractory status epilepticus

Cranioplasty, specifically a repair of the skull defect resulting from a previous decompressive craniectomy, is a relatively simple procedure associated with a minimal rate of complications. Even though seizures are seen in up to 30% of the patients postoperatively, status epilepticus is not commonly described. Cerebral oedema, ischaemia and neuro-inflammation have been reported as putative causes of seizures in this population. Here, we report a case of refractory status epilepticus unresponsive to standard anti-epileptic and anaesthetic agents. The use of dexmedetomidine helped terminate the episode and led to a favourable outcome. Most of the standard anti-epileptic and anaesthetic agents act through potentiation of GABAergic transmission or sodium channel blockade and postsynaptic adrenoceptor activation by dexmedetomidine may help potentiate their effect. Further studies are needed to investigate its anticonvulsant effect on post-traumatic brain injury and elaborate on optimal dosage.

Exploring genetic diversity of wild and related tetraploid wheat species Triticum turgidum and Triticum timopheevii

INTRODUCTION

The domestication bottleneck has reduced genetic diversity inwheat, necessitating the use of wild relatives in breeding programs. Wild tetraploid wheat are widely used in the breeding programs but with morphological characters, it is difficult to distinguish these, resulting in misclassification/mislabeling or duplication of accessions in the Gene bank.

OBJECTIVES

The study aims to exploreGenotyping by sequencing (GBS) to characterize wild and domesticated tetraploid wheat accessions to generate a core set of accessions to be used in the breeding program.

METHODS

TASSEL-GBS pipeline was used for SNP discovery, fastStructure was used to determine the population structure and PowerCore was used to generate a core sets. Nucleotide diversity matrices of Nie's and F-statistics (FST) index were used to determine the center of genetic diversity.

RESULTS

We found 65 % and 47 % duplicated accessions in Triticum timopheevii and T. turgidum respectively. Genome-wide nucleotide diversity and FST scan uncovered a lower intra and higher inter-species differentiation. Distinct FST regions were identified in genomic regions belonging to domestication genes: non-brittle rachis (Btr1) and vernalization (VRN-1).Our results suggest that Israel, Jordan, Syria, and Lebanonas the hub of genetic diversity of wild emmer;Turkey, and Georgia for T. durum; and Iraq, Azerbaijan, and Armenia for theT. timopheevii. Identified core set accessions preserved more than 93 % of the available genetic diversity. Genome wide association study (GWAS) indicated the potential chromosomal segment for resistance to leaf rust in T. timopheevii.

CONCLUSION

The present study explored the potential of GBS technology in data reduction while maintaining the significant genetic diversity of the species. Wild germplasm showed more differentiation than domesticated accessions, indicating the availability of sufficient diversity for crop improvement. With reduced complexity, the core set preserves the genetic diversity of the gene bank collections and will aid in a more robust characterization of wild germplasm.

A Computer Vision Algorithm to Classify Pneumatization of the Mastoid Process on Temporal Bone Computed Tomography Scans

BACKGROUND

Pneumatization of the mastoid process is variable and of significance to the operative surgeon. Surgical approaches to the temporal bone require an understanding of pneumatization and its implications for surgical access. This study aims to determine the feasibility of using deep learning convolutional neural network algorithms to classify pneumatization of the mastoid process.

METHODS

De-identified petrous temporal bone images were acquired from a tertiary hospital radiology picture archiving and communication system. A binary classification mode in the pretrained convolutional neural network was used to investigate the utility of convolutional neural networks in temporal bone imaging. False positive and negative images were reanalyzed by the investigators and qualitatively assessed to consider reasons for inaccuracy.

RESULTS

The overall accuracy of the model was 0.954. At a probability threshold of 65%, the sensitivity of the model was 0.860 (95% CI 0.783-0.934) and the specificity was 0.989 (95% CI 0.960-0.999). The positive predictive value was 0.973 (95% CI 0.904-0.993) and the negative predictive value was 0.935 (95% CI 0.901-0.965). The false positive rate was 0.006. The F1 number was 0.926 demonstrating a high accuracy for the model.

CONCLUSION

The temporal bone is a complex anatomical region of interest to otolaryngologists. Surgical planning requires high-resolution computed tomography scans, the interpretation of which can be augmented with machine learning. This initial study demonstrates the feasibility of utilizing machine learning algorithms to discriminate anatomical variation with a high degree of accuracy. It is hoped this will lead to further investigation regarding more complex anatomical structures in the temporal bone.

Automated Segmentation of Intracranial Thrombus on NCCT and CTA in Patients with Acute Ischemic Stroke Using a Coarse-to-Fine Deep Learning Model

BACKGROUND AND PURPOSE

Identifying the presence and extent of intracranial thrombi is crucial in selecting patients with acute ischemic stroke for treatment. This article aims to develop an automated approach to quantify thrombus on NCCT and CTA in patients with stroke.

MATERIALS AND METHODS

A total of 499 patients with large-vessel occlusion from the Safety and Efficacy of Nerinetide in Subjects Undergoing Endovascular Thrombectomy for Stroke (ESCAPE-NA1) trial were included. All patients had thin-section NCCT and CTA images. Thrombi contoured manually were used as reference standard. A deep learning approach was developed to segment thrombi automatically. Of 499 patients, 263 and 66 patients were randomly selected to train and validate the deep learning model, respectively; the remaining 170 patients were independently used for testing. The deep learning model was quantitatively compared with the reference standard using the Dice coefficient and volumetric error. The proposed deep learning model was externally tested on 83 patients with and without large-vessel occlusion from another independent trial.

RESULTS

The developed deep learning approach obtained a Dice coefficient of 70.7% (interquartile range, 58.0%-77.8%) in the internal cohort. The predicted thrombi length and volume were correlated with those of expert-contoured thrombi (r = 0.88 and 0.87, respectively; P < .001). When the derived deep learning model was applied to the external data set, the model obtained similar results in patients with large-vessel occlusion regarding the Dice coefficient (66.8%; interquartile range, 58.5%-74.6%), thrombus length (r = 0.73), and volume (r = 0.80). The model also obtained a sensitivity of 94.12% (32/34) and a specificity of 97.96% (48/49) in classifying large-vessel occlusion versus non-large-vessel occlusion.

CONCLUSIONS

The proposed deep learning method can reliably detect and measure thrombi on NCCT and CTA in patients with acute ischemic stroke.

Quantitative and qualitative analysis of ochratoxin-A using fluorescent CQDs@DNA-based nanoarchitecture assembly to monitor food safety and quality

Ochratoxin A (OTA), a mycotoxin formed by various fungi, such as Aspergillus and Penicillium species, is dangerous to human health. Thus, to circumvent the risk of OTA ingestion, the recognition and quantification of OTA levels are of great significance. A perusal of the literature has revealed that the integration of DNA/Carbon Quantum Dot (CQD)-based hybrid systems may exhibit the unique electronic and optical properties of nanomaterials/nanoarchitecture and consequent recognition properties. Herein, we developed the CQDs@DNA-based hybrid nanoarchitecture system for the selective detection of OTA, which exhibits modulation in the emission spectrum after interaction with OTA, with a significant binding constant (K_a = 3.5 × 10⁵ M^-1), a limit of detection of 14 nM, limit of quantification of 47 nM and working range of 1-10 μM. The mechanism for sensing the OTA has been corroborated using fluorescence, UV-visible absorption spectroscopy, and FTIR techniques, demonstrating the binding mode of CQD@DNA hybrid nano-architecture assembly with OTA. Further, we demonstrated the sensing ability of developed CQDs@DNA-based nanoarchitecture assembly towards the quantification of OTA in real food monitoring analysis for real-time applications, which makes this developed nanoarchitecture assembly the potential candidate to conveniently monitor food safety and quality for human health.

Convolutional Neural Networks in ENT Radiology: Systematic Review of the Literature

INTRODUCTION

Convolutional neural networks (CNNs) represent a state-of-the-art methodological technique in AI and deep learning, and were specifically created for image classification and computer vision tasks. CNNs have been applied in radiology in a number of different disciplines, mostly outside otolaryngology, potentially due to a lack of familiarity with this technology within the otolaryngology community. CNNs have the potential to revolutionize clinical practice by reducing the time required to perform manual tasks. This literature search aims to present a comprehensive systematic review of the published literature with regard to CNNs and their utility to date in ENT radiology.

METHODS

Data were extracted from a variety of databases including PubMED, Proquest, MEDLINE Open Knowledge Maps, and Gale OneFile Computer Science. Medical subject headings (MeSH) terms and keywords were used to extract related literature from each databases inception to October 2020. Inclusion criteria were studies where CNNs were used as the main intervention and CNNs focusing on radiology relevant to ENT. Titles and abstracts were reviewed followed by the contents. Once the final list of articles was obtained, their reference lists were also searched to identify further articles.

RESULTS

Thirty articles were identified for inclusion in this study. Studies utilizing CNNs in most ENT subspecialties were identified. Studies utilized CNNs for a number of tasks including identification of structures, presence of pathology, and segmentation of tumors for radiotherapy planning. All studies reported a high degree of accuracy of CNNs in performing the chosen task.

CONCLUSION

This study provides a better understanding of CNN methodology used in ENT radiology demonstrating a myriad of potential uses for this exciting technology including nodule and tumor identification, identification of anatomical variation, and segmentation of tumors. It is anticipated that this field will continue to evolve and these technologies and methodologies will become more entrenched in our everyday practice.

Evaluating the generalizability of deep learning image classification algorithms to detect middle ear disease using otoscopy

To evaluate the generalizability of artificial intelligence (AI) algorithms that use deep learning methods to identify middle ear disease from otoscopic images, between internal to external performance. 1842 otoscopic images were collected from three independent sources: (a) Van, Turkey, (b) Santiago, Chile, and (c) Ohio, USA. Diagnostic categories consisted of (i) normal or (ii) abnormal. Deep learning methods were used to develop models to evaluate internal and external performance, using area under the curve (AUC) estimates. A pooled assessment was performed by combining all cohorts together with fivefold cross validation. AI-otoscopy algorithms achieved high internal performance (mean AUC: 0.95, 95%CI: 0.80-1.00). However, performance was reduced when tested on external otoscopic images not used for training (mean AUC: 0.76, 95%CI: 0.61-0.91). Overall, external performance was significantly lower than internal performance (mean difference in AUC: -0.19, p ≤ 0.04). Combining cohorts achieved a substantial pooled performance (AUC: 0.96, standard error: 0.01). Internally applied algorithms for otoscopy performed well to identify middle ear disease from otoscopy images. However, external performance was reduced when applied to new test cohorts. Further efforts are required to explore data augmentation and pre-processing techniques that might improve external performance and develop a robust, generalizable algorithm for real-world clinical applications.

Recent Advances in Recognition Receptors for Electrochemical Biosensing of Mycotoxins-A Review

Mycotoxins are naturally occurring toxic secondary metabolites produced by fungi in cereals and foodstuffs during the stages of cultivation and storage. Electrochemical biosensing has emerged as a rapid, efficient, and economical approach for the detection and quantification of mycotoxins in different sample media. An electrochemical biosensor consists of two main units, a recognition receptor and a signal transducer. Natural or artificial antibodies, aptamers, molecularly imprinted polymers (MIP), peptides, and DNAzymes have been extensively employed as selective recognition receptors for the electrochemical biosensing of mycotoxins. This article affords a detailed discussion of the recent advances and future prospects of various types of recognition receptors exploited in the electrochemical biosensing of mycotoxins.

Inter-rater agreement between 13 otolaryngologists to diagnose otitis media in Aboriginal and Torres Strait Islander children using a telehealth approach

INTRODUCTION

Telehealth programs are important to deliver otolaryngology services for Aboriginal and Torres Strait Islander children living in rural and remote areas, where distance and access to specialists is a critical factor.

OBJECTIVE

To evaluate the inter-rater agreement and value of increasing levels of clinical data (otoscopy with or without audiometry and in-field nurse impressions) to diagnose otitis media using a telehealth approach.

DESIGN

Blinded, inter-rater reliability study.

SETTING

Ear health and hearing assessments collected from a statewide telehealth program for Indigenous children living in rural and remote areas of Queensland, Australia.

PARTICIPANTS

Thirteen board-certified otolaryngologists independently reviewed 80 telehealth assessments from 65 Indigenous children (mean age 5.7 ± 3.1 years, 33.8% female).

INTERVENTIONS

Raters were provided increasing tiers of clinical data to assess concordance to the reference standard diagnosis: Tier A) otoscopic images alone, Tier B) otoscopic images plus tympanometry and category of hearing loss, and Tier C) as B plus static compliance, canal volume, pure-tone audiometry, and nurse impressions (otoscopic findings and presumed diagnosis). For each tier, raters were asked to determine which of the four diagnostic categories applied: normal aerated ear, acute otitis media (AOM), otitis media with effusion (OME), and chronic otitis media (COM).

MAIN OUTCOME MEASURES

Proportion of agreement to the reference standard, prevalence-and-bias adjusted κ coefficients, mean difference in accuracy estimates between each tier of clinical data.

RESULTS

Accuracy between raters and the reference standard increased with increased provision of clinical data (Tier A: 65% (95%CI: 63-68%), κ = 0.53 (95%CI: 0.48-0.57); Tier B: 77% (95%CI: 74-79%), 0.68 (95%CI: 0.65-0.72); C: 85% (95%CI: 82-87%), 0.79 (95%CI: 0.76-0.82)). Classification accuracy significantly improved between Tier A to B (mean difference:12%, p < 0.001) and between Tier B to C (mean difference: 8%, p < 0.001). The largest improvement in classification accuracy was observed between Tier A and C (mean difference: 20%, p < 0.001). Inter-rater agreement similarly improved with increasing provision of clinical data.

CONCLUSIONS

There is substantial agreement between otolaryngologists to diagnose ear disease using electronically stored clinical data collected from telehealth assessments. The addition of audiometry, tympanometry and nurse impressions significantly improved expert accuracy and inter-rater agreement, compared to reviewing otoscopic images alone.

Studies on Structural Changes of modified MWCNTs: Material for Electrochemical Monitoring of Antiviral Drug in Human Serum Samples

<p style="margin:0cm;text-align:justify;line-height:200%"><span style="color:black">The development of a universal approach for precisely tuning the electrochemical characteristics of conducting carbon nanotubes for tracking harmful agents in the human body with high selectivity and sensitivity remains a challenge. Herein, we describe a simplistic, versatile, and&nbsp;general approach to the construction of functionalized electrochemical material. The design of electrochemical material consists of (i) modification of multiwalled carbon nanotubes (MWCNT) with dipodal naphthyl-based dipodal urea (KR-1) through non-covalent functionalization (KR-1@MWCNT) which enhances the dispersibility of MWCNT and hence conductivity, (ii) complexation of KR-1@MWCNT with Hg²⁺ accelerate the electron transfer in the material which amplify the detection response of functionalized material (<italic>i.e.,</italic> <bold>Hg/KR-1@MWCNT</bold>) towards various thymidine analogues.&nbsp;Further, the application of functionalized electrochemical material (<bold>Hg/KR-1@MWCNT)</bold> achieves real-time electrochemical monitoring of harmful antiviral drug 5-iodo-2&#39;-iododeoxyuridine (IUdR) levels in human serum albumin for the first time.<o:p></o:p></span></p>.

A high-performance Calix@ZnO based bifunctional nanomaterial for selective detection and degradation of toxic azinphos methyl in environmental samples

One of the key tenets of sustainable agriculture and food safety is the removal of toxic pesticides from the environment. However, developing reliable, affordable, and efficient methods for detecting and degrading pesticides into non-toxic degradable products remains an immediate matter of concern. Herein, we attempt to develop a strategy for the detection as well as degradation of highly toxic phosphorodithioate pesticide, Azinphos methyl (AZM), using hybrid zinc oxide nanoparticles (ZnO NPs). Considering the non-selectivity of bare ZnO and receptor R1, we have fabricated the heterocalixarene-based Calix (R1) over zinc oxide (ZnO) surface in situ via the sol-gel process. The synthesized heterocaliaxrene-modified ZnO (R1@ZnO) NPs show an excellent affinity for the selective and sensitive detection of AZM with a tremendously low limit of detection (68 mg L^-1) and no interference from other pesticides. Degradation of AZM was fully supported by fluorescence spectroscopy, scanning electron microscopy (SEM), ¹H NMR titrations, FTIR spectroscopy, cyclic voltammetry, and mass spectroscopy, which unequivocally confirmed the formation of non-toxic products. According to our findings, R1@ZnO NPs are sustainable nanomaterials that can be employed for environmental remediation since they operate in an aqueous medium.

Anticancer SAR Establishment and α/β-Tubulin Isoforms Specific Targeting: A Detailed Insight of Anticancer potential of 4H-Chromene derivatives

4H-Chromene derivatives are promising anticancer compounds known to bind within the colchicine binding site of tubulin protein. Among these 2-amino-4-phenyl-4H-benzo[h]chromene-3-carbonitrile based 4H-Chromenes scaffold is known to produce a significant impact...

Surgical Approaches to Cavernous Sinus: A Narrative Review of the Literature with Anatomical Drawings

IIntroduction. The cavernous sinus (CS) is a paired venous sinus in the human brain that is classified as a true dural venous sinus rather than a venous plexus. The entire CS is separated by septa into two small cavities called caves. The CS has a very close resemblance to various key structures present in the head. The CS is a blood compartment that contains ligaments, endothelium, and trabeculae. It is clinically significant because of its position and relationship with several cranial nerves. Clinical implications. For effective management and treatment of CS syndrome, CS thrombosis, carotid-cavernous fistula, and other CS-related problems, CS surgery became necessary. As a result of the lack of sophisticated surgical techniques in the past, CS surgery was exceedingly challenging, complicated, and deadly. The surgery of CSs can benefit from a variety of surgical procedures, including extradural and intradural, endoscopic endonasal, rhomboid, and temporopolar trans cavernous approaches. In this review, numerous surgical procedures for CS are discussed along with their intended uses. Conclusions. A greater understanding of the CS was made possible by the quick modifications and improvements in surgical methods, which aided in neurosurgery procedures.

Machine Learning-Based Analytical Systems: Food Forensics

Despite a large amount of money being spent on both food analyses and control measures, various food-borne illnesses associated with pathogens, toxins, pesticides, adulterants, colorants, and other contaminants pose a serious threat to human health, and thus food safety draws considerable attention in the modern pace of the world. The presence of various biogenic amines in processed food have been frequently considered as the primary quality parameter in order to check food freshness and spoilage of protein-rich food. Various conventional detection methods for detecting hazardous analytes including microscopy, nucleic acid, and immunoassay-based techniques have been employed; however, recently, array-based sensing strategies are becoming popular for the development of a highly accurate and precise analytical method. Array-based sensing is majorly facilitated by the advancements in multivariate analytical techniques as well as machine learning-based approaches. These techniques allow one to solve the typical problem associated with the interpretation of the complex response patterns generated in array-based strategies. Consequently, the machine learning-based neural networks enable the fast, robust, and accurate detection of analytes using sensor arrays. Thus, for commercial applications, most of the focus has shifted toward the development of analytical methods based on electrical and chemical sensor arrays. Therefore, herein, we briefly highlight and review the recently reported array-based sensor systems supported by machine learning and multivariate analytics to monitor food safety and quality in the field of food forensics.

The Impact of Adhesions on Nasal Airflow: A Quantitative Analysis Using Computational Fluid Dynamics

Background

Nasal adhesions (NAs) are a known complication of nasal airway surgery. Even minor NAs can lead to significant postoperative nasal airway obstruction (NAO). Division of such NAs often provides much greater relief than anticipated.

Objective

We examine the impact of NAs at various anatomical sites on nasal airflow and mucosal cooling using computational fluid dynamics (CFD) and multiple test subjects.

Methods

CT scans of healthy adult subjects were used to construct three-dimensional nasal airway computational models. A single virtual 2.5 mm diameter NA was placed at one of five sites commonly seen following NAO surgery within each nasal cavity bilaterally, resulting in 10 NA models and 1 NA-free control for each subject. CFD analysis was performed on each NA model and compared with the subject's NA-free control model.

Results

4 subjects were recruited to create 44 computational models. The NAs caused the airflow streamlines to separate, leading to a statistically significant increase in mucosal temperature immediately downstream to the NAs (wake region). Changes in the mucosal temperature in the wake region of the NAs were most prominent in anteriorly located NAs with a mean increase of 1.62 °C for the anterior inferior turbinate NAs ( P < .001) and 0.63 °C for the internal valve NAs ( P < .001).

Conclusion

NAs result in marked disruption to airflow patterns and reduced mucosal cooling on critical surfaces, particularly in the wake region. Reduced wake region mucosal cooling may be a contributing factor to the exaggerated perception of nasal obstruction experienced by patients with NAs.

Elucidating the Molecular Structure of Hydrophobically Modified Polyethylenimine Nanoparticles and Its Potential Implications for DNA Binding

The structural properties of the polyethylenimine (PEI) polymer are generally tuned and selectively modified to reinforce its potential in a broad spectrum of applied domains of medicine, healthcare, material design, sensing, and electronic optimization. The selective modification of the polymer brings about changes in its interfacial characteristics and behavior. The current work involves the synthesis of naphthalimide conjugated polyethylenimine organic nanoparticles (NPEI-ONPs). The interfacial molecular structure of NPEI-ONPs is explored in an aqueous medium at pH 7.4 using surface tensiometry and sum-frequency generation vibrational spectroscopy (SFG-VS). The hydrophobic functionalization rendered a concentration-dependent surface coverage of NPEI-ONPs, where the SFG-VS analysis exhibited the molecular rearrangement of its hydrophobic groups at the interface. The interaction of NPEI-ONPs with double-stranded DNA (dsDNA) is carried out to observe the relevance of the synthesized nanocomposites in the biomedical domain. The bulk-specific studies (i.e., thermal denaturation, viscometry, zeta (ζ) potential, and ATR-FTIR) reveal the condensation of dsDNA in the presence of NPEI-ONPs, making its structure more compact. The interface-sensitive SFG-VS showcased the impact of the dsDNA and NPEI-ONP interaction on the interfacial molecular behavior of NPEI-ONPs at the air-aqueous interface. Our results exhibit the potential of such hydrophobically functionalized ONPs as promising candidates for developing biomedical sealants, substrate coatings, and other biomedical domains.

Language barriers for primary care access in Europe: a systematic review

Background

A recent increase in migration both inside Europe and from non-European countries has expanded the language profile of many European countries. As a result, there has been a significant increase in barriers to healthcare access experienced by linguistic minority migrants. This systematic review aims to explore language barriers in primary care, focusing on the experiences of linguistic minority migrants living in Europe.

Methods

PubMed, Embase, Scopus and Global Health were searched to identify studies published in English until May 2021. Qualitative and mixed methods studies on either linguistic minority migrants or healthcare workers working with linguistic minority migrants, exploring the impacts of language barriers in a primary care setting published were eligible. The studies were analysed using a Braun and Clarke's thematic analysis approach. Quality of the studies were assessed using the Mixed Methods Appraisal Tool.

Results

16 studies from 14 different European countries were eligible. Participants in the studies included four groups: linguistic minority migrants (n = 11), healthcare workers (n = 10), interpreters (n = 1) and administrative staff (n = 1). Barriers identified included a lack of interpreters, limited cultural competence of practitioners, a lack of practitioner training and knowledge, a lack of accessible information for migrants, difficulties expressing emotions and building patient-practitioner relationships, and risks to women's bodily autonomy resulting from language barriers.

Conclusions

Linguistic minority migrants living in Europe face a number of barriers when accessing primary care. These barriers can risk patient safety, reduce the likelihood of seeking healthcare services, and impact patient experiences of healthcare services. There is a need for improved interpreter services, practitioner training, and information accessibility for both migrants and healthcare staff.

Key messages

• Linguistic minority migrants experience significant barriers to primary healthcare access across Europe.

• There is a need for improved interpreter services, practitioner training, and information accessibility for both migrants and healthcare staff.

Flow Patterns and Particle Residence Times in the Oral Cavity during Inhaled Drug Delivery

Pulmonary drug delivery aims to deliver particles deep into the lungs, bypassing the mouth−throat airway geometry. However, micron particles under high flow rates are susceptible to inertial impaction on anatomical sites that serve as a defense system to filter and prevent foreign particles from entering the lungs. The aim of this study was to understand particle aerodynamics and its possible deposition in the mouth−throat airway that inhibits pulmonary drug delivery. In this study, we present an analysis of the aerodynamics of inhaled particles inside a patient-specific mouth−throat model generated from MRI scans. Computational Fluid Dynamics with a Discrete Phase Model for tracking particles was used to characterize the airflow patterns for a constant inhalation flow rate of 30 L/min. Monodisperse particles with diameters of 7 μm to 26 μm were introduced to the domain within a 3 cm-diameter sphere in front of the oral cavity. The main outcomes of this study showed that the time taken for particle deposition to occur was 0.5 s; a narrow stream of particles (medially and superiorly) were transported by the flow field; larger particles > 20 μm deposited onto the oropharnyx, while smaller particles < 12 μm were more disperse throughout the oral cavity and navigated the curved geometry and laryngeal jet to escape through the tracheal outlet. It was concluded that at a flow rate of 30 L/min the particle diameters depositing on the larynx and trachea in this specific patient model are likely to be in the range of 7 μm to 16 μm. Particles larger than 16 μm primarily deposited on the oropharynx.

Nasal Irrigation Delivery in Three Post-FESS Models From a Squeeze-bottle Using CFD

Purpose

Nasal saline irrigation is highly recommended in patients following functional endoscopic sinus surgery (FESS) to aid the postoperative recovery. Post-FESS patients have significantly altered anatomy leading to markedly different flow dynamics from those found in pre-op or non-diseased airways, resulting in unknown flow dynamics.

Methods

This work investigated how the liquid stream disperses through altered nasal cavities following surgery using Computational Fluid Dynamics (CFD). A realistic squeeze profile was determined from physical experiments with a 27-year-old male using a squeeze bottle with load sensors. The administration technique involved a head tilt of 45-degrees forward to represent a head position over a sink. After the irrigation event that lasted 4.5 s, the simulation continued for an additional 1.5 s, with the head orientation returning to an upright position.

Results

The results demonstrated that a large maxillary sinus ostium on the right side allows saline penetration into this sinus. The increased volume of saline entering the maxillary sinus limits the saline volume available to the rest of the sinonasal cavity and reduces the surface coverage of the other paranasal sinuses. The average wall shear stress was higher on the right side than on the other side for two patients. The results also revealed that head position alters the sinuses’ saline residual, especially the frontal sinuses.

Conclusion

While greater access to sinuses is achieved through FESS surgery, patients without a nasal septum limits posterior sinus penetration due to the liquid crossing over to the contralateral cavity and exiting the nasal cavity early.

Search for Subsolar-Mass Binaries in the First Half of Advanced LIGO's and Advanced Virgo's Third Observing Run

We report on a search for compact binary coalescences where at least one binary component has a mass between 0.2  M_{⊙} and 1.0  M_{⊙} in Advanced LIGO and Advanced Virgo data collected between 1 April 2019 1500 UTC and 1 October 2019 1500 UTC. We extend our previous analyses in two main ways: we include data from the Virgo detector and we allow for more unequal mass systems, with mass ratio q≥0.1. We do not report any gravitational-wave candidates. The most significant trigger has a false alarm rate of 0.14  yr^{-1}. This implies an upper limit on the merger rate of subsolar binaries in the range [220-24200]  Gpc^{-3} yr^{-1}, depending on the chirp mass of the binary. We use this upper limit to derive astrophysical constraints on two phenomenological models that could produce subsolar-mass compact objects. One is an isotropic distribution of equal-mass primordial black holes. Using this model, we find that the fraction of dark matter in primordial black holes in the mass range 0.2  M_{⊙}<m_{PBH}<1.0  M_{⊙} is f_{PBH}≡Ω_{PBH}/Ω_{DM}≲6%. This improves existing constraints on primordial black hole abundance by a factor of ∼3. The other is a dissipative dark matter model, in which fermionic dark matter can collapse and form black holes. The upper limit on the fraction of dark matter black holes depends on the minimum mass of the black holes that can be formed: the most constraining result is obtained at M_{min}=1  M_{⊙}, where f_{DBH}≡Ω_{DBH}/Ω_{DM}≲0.003%. These are the first constraints placed on dissipative dark models by subsolar-mass analyses.

Correlation of Nasal Mucosal Temperature and Nasal Patency—A Computational Fluid Dynamics Study

OBJECTIVES

Recent evidence suggests that detection of nasal mucosal temperature, rather than direct airflow detection, is the primary determinant of subjective nasal patency. This study examines the role of nasal mucosal temperature in the perception of nasal patency using in vivo and computational fluid dynamics (CFD) measurements.

METHODS

Healthy adult participants completed Nasal Obstruction Symptom Evaluation (NOSE) and Visual Analogue Scale (VAS) questionnaires. A temperature probe measured nasal mucosal temperature at the vestibule, inferior turbinate, middle turbinate, and nasopharynx bilaterally. Participants underwent a CT scan, used to create a 3D nasal anatomy model to perform CFD analysis of nasal mucosal and inspired air temperature and heat flux along with mucosal surface area where heat flux >50 W/m² (SAHF50).

RESULTS

Eleven participants with a median age of 27 (IQR 24; 48) were recruited. Probe-measured temperature values correlated strongly with CFD-derived values (r = 0.87, p < 0.05). Correlations were seen anteriorly in the vestibule and inferior turbinate regions between nasal mucosal temperature and unilateral VAS (r = 0.42-0.46; p < 0.05), between SAHF50 and unilateral VAS (r = -0.31 to -0.36; p < 0.05) and between nasal mucosal temperature and SAHF50 (r = -0.37 to -0.41; p < 0.05). Subjects with high patency (VAS ≤10) had increased heat flux anteriorly compared with lower patency subjects (VAS >10; p < 0.05).

CONCLUSION

Lower nasal mucosal temperature and higher heat flux within the anterior nasal cavity correlates with a perception of improved unilateral nasal patency in healthy individuals.

LEVEL OF EVIDENCE

4 Laryngoscope, 133:1328-1335, 2023.