Identification of Rice Sheath Blight through Spectral Responses Using Hyperspectral Images

Sheath blight (ShB), caused by Rhizoctonia solani AG1-I, is one of the most important diseases in rice worldwide. The symptoms of ShB primarily develop on leaf sheaths and leaf blades. Hyperspectral remote sensing technology has the potential of rapid, efficient and accurate detection and monitoring of the occurrence and development of rice ShB and other crop diseases. This study evaluated the spectral responses of leaf blade fractions with different development stages of ShB symptoms to construct the spectral feature library of rice ShB based on “three-edge” parameters and narrow-band vegetation indices to identify the disease on the leaves. The spectral curves of leaf blade lesions have significant changes in the blue edge, green peak, yellow edge, red valley, red edge and near-infrared regions. The variables of the normalized index between green peak amplitude and red valley amplitude (Rg − Ro)/(Rg + Ro), the normalized index between the yellow edge area and blue edge area (SDy − SDb)/(SDy + SDb), the ratio index of green peak amplitude and red valley amplitude (Rg/Ro) and the nitrogen reflectance index (NRI) had high relevance to the disease. At the leaf scale, the importance weights of all attributes decreased with the effect of non-infected areas in a leaf by the ReliefF algorithm, with Rg/Ro being the indicator having the highest importance weight. Estimation rate of 95.5% was achieved in the decision tree classifier with the parameter of Rg/Ro. In addition, it was found that the variety degree of absorptive valley, reflection peak and reflecting steep slope was different in the blue edge, green and red edge regions, although there were similar spectral curve shapes between leaf sheath lesions and leaf blade lesions. The significant difference characteristic was the ratio index of the red edge area and green peak area (SDr/SDg) between them. These results can provide the basis for the development of a specific sensor or sensors system for detecting the ShB disease in rice.

Sex differences in pharmacotherapy and long-term outcomes in patients with ischaemic heart disease and left ventricular dysfunction

Background

Left ventricular dysfunction and ischaemic heart disease are common amongst women, however, women tend to present later and are less likely to receive guideline-directed medical therapy compared to their male counterparts.

Purpose

To investigate if a sex discrepancy exists for optimal medical therapy (OMT) and long-term mortality in a cohort of patients with known ischaemic heart disease (IHD) and left ventricular dysfunction.

Methods

We analysed prospectively collected data from a multicentre registry database collected between 2005–2018 on pharmacotherapy 30-days post percutaneous coronary intervention (PCI) in 13,015 patients with left ventricular ejection fraction (LVEF) <50%. OMT at 30-days was defined as beta-blocker (BB), angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (ACEi/ARB) ± mineralocorticoid receptor antagonist (MRA). Long-term mortality was determined by linkage with the National Death Index, with median follow up of 4.7 (IQR 2.0–8.6) years.

Results

Mean age was 65±12 years; women represented 20.2% (2,634) of the cohort. Women were on average 5 years older, had higher average BMI, higher rates of hypertension, diabetes, renal dysfunction, prior stroke and rheumatoid arthritis. Men were more likely to have sleep apnoea, be current/ex-smokers and to have had prior myocardial infarction, PCI and bypass surgery. Overall, 72.3% (9,411) of patients were on OMT, which was similar between sexes (72.7% in women vs. 72.2% in men, p=0.58). Rates of BB therapy were similar between sexes (85.2% vs. 84.5%, p=0.38), while women were less likely to be on an ACEi/ARB (80.4% vs. 82.4%, p=0.02) and more likely to be on a MRA (12.1% vs. 10.0%, p=0.003). Amongst those with LVEF ≤35% (n=1,652), BB (88.7% vs. 87.3%, p=0.46), ACEi/ARB (83.3% vs. 82.1%, p=0.59) and MRA use (32.5% vs. 33.3%, p=0.78) was comparable. Aspirin use was similar between sexes (95.3% vs. 95.9%, p=0.12), while women were less likely to be on statin therapy (93.5% vs. 95.3%, p<0.001) and a second antiplatelet agent (94.4% vs. 95.6%, p=0.007). On unadjusted analysis women had significantly higher long-term mortality of 25.4% compared to 19.0% for men (p<0.001). Kaplan-Meier analysis out to 14 years demonstrated that men on OMT have the best long-term survival overall and women on sub-OMT have significantly poorer outcomes compared to men on sub-OMT. However, after adjusting for OMT and other comorbidities there was no difference in long-term mortality between sexes (HR 0.99, 95% CI 0.87–1.14, p=0.94).

Conclusion

From this large multicentre registry, we found similar rates of guideline-directed pharmacotherapy for left ventricular dysfunction between sexes, however women were less likely to be on appropriate IHD secondary prevention. The increased unadjusted long-term mortality amongst women is likely due to differing baseline risk, given that adjusted mortality was similar between sexes.

Kaplan-Meier Survival Analysis

Funding Acknowledgement

Type of funding source: None

Humidity sensor based on a graphene oxide-coated few-mode fiber Mach-Zehnder interferometer

A relative humidity sensor based on a graphene oxide-coated few-mode fiber Mach-Zehnder interferometer (MZI) is proposed in this paper. The MZI was made by splicing a segment of the few-mode fiber (FMF) between two segments of a no-core fiber (NCF) and two segments of a single mode fiber (SMF) located outside the two NCFs. The core and cladding of the FMF acted as interferometric arms, while the NCFs acted as couplers for splitting and recombining light due to mismatch of mode field diameter. The cladding of the FMF was corroded with hydrofluoric acid, and a layer of graphene oxide (GO) film was coated on the corroded cladding of FMF via the natural deposition method. The refractive index of GO varied upon absorption the water molecules. As a result, the phase difference of the MZI varied and the wavelength of the resonant dip shifted with a change in the ambient relative humidity (RH). High humidity sensitivity of 0.191 and 0.061 nm/%RH in the RH range of 30-55% and 55-95%, respectively, were achieved experimentally. The high sensitivity, compact size, and simple manufacturing of the proposed sensor could offer attractive applications in fields of chemical sensors and biochemical detection.

Data for an Advanced Microstructural and Electrochemical Datasheet on 18650 Li-ion Batteries with Nickel-Rich NMC811 Cathodes and Graphite-Silicon Anodes

The data presented here were collected from a commercial LG Chem cylindrical INR18650 MJ1 lithium-ion (Li-ion) battery (approximate nominal specifications: 3.5 Ah, 3.6 V, 12.2 Wh). Electrochemical and microstructural information is presented, the latter collected across several length scales using X-ray computed tomography (CT): from cell to particle. One cell-level tomogram, four assembly-level and two electrode/particle-level 3D datasets are available; all data was collected in the pristine state. The electrochemical data consists of the full current and voltage charge-discharge curves for 400 operational cycles. All data has been made freely available via a repository [10.5522/04/c.4994651] in order to aid in the development of improved computational models for commercially-relevant Li-ion battery materials.

Melatonin activity and receptor expression in endometrial tissue and endometriosis

STUDY QUESTION

Are melatonin receptors (melatonin receptor 1A (MR1A) and melatonin receptor 1B (MR1B)) expressed in human endometrium and endometriotic tissue, and does melatonin affect endometrial cell proliferation?

SUMMARY ANSWER

Melatonin receptors are expressed in human eutopic endometrium, endometriomas and peritoneal lesions, although to different extents, and melatonin treatment attenuated estradiol-induced endometrial epithelial cell proliferation in culture.

WHAT IS KNOWN ALREADY

Melatonin decreased endometriotic lesion volume in a rat model of endometriosis. Melatonin treatment reduced pain scores in and analgesic use by women with endometriosis.

STUDY DESIGN, SIZE, DURATION

Basic science study using human endometrial tissue and an endometrial epithelial cell line.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Measurement of melatonin receptor expression (mRNA and protein) in women with surgically confirmed endometriosis (endometrioma (n = 20) or peritoneal lesion (n = 11) alone) and women without surgical evidence of endometriosis (control, n = 15). Collection of endometrial and endometriotic tissue samples, gynecologic history and demographic information. Quantification of estradiol (1.0 nM) and melatonin (0.1 nM-1.0 μM) ± estradiol-induced endometrial epithelial cell proliferation in cultures of endometrial epithelial cells (CRL-1671) following 24 and 48 hours of culture.

MAIN RESULTS AND THE ROLE OF CHANCE

MR1A and MR1B were localized by immunohistochemistry in glandular epithelial cells of endometrial biopsies from women with and without endometriosis. Both receptors were expressed in eutopic and ectopic endometrial tissue. mRNA expression of MR1A and MR1B was significantly greater in peritoneal lesions than in either endometriomas or eutopic endometrium. However, protein expression of MR1A was decreased in peritoneal lesions compared to control eutopic endometrium, whereas MR1B expression did not differ between the groups. Melatonin (0.1 nM-1.0 μM) treatment inhibited estradiol (1.0 nM)-induced endometrial epithelial cell proliferation at 48 hours but not 24 hours of culture.

LIMITATIONS, REASONS FOR CAUTION

Beneficial effects of melatonin seen in culture have yet to be comprehensively evaluated in women with endometriosis.

WIDER IMPLICATIONS OF THE FINDINGS

Our data suggest that melatonin may be useful as an adjunct to current endometriosis treatments.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by the Canadian Institutes of Health Research (grant MOP142230 to W.G.F.). A.A.M. is supported by a resident research grant through the Physicians Services Incorporated Foundation. The authors have no conflicts of interest.

[Consideration of surgeons participating in 2019 coronavirus disease emergency medical rescue]

As a newly epidemic, 2019 coronavirus disease (COVID-19) with a concentrated outbreak poses a great challenge to medical treatment. The severe and critical patients are complex complicatied with the psychological problems, and the medical staff are overworked and under tremendous psychological pressure. The surgeon participated in emergency medical rescue could provide professional treatment for the patients combined with surgical diseases, as well as specialized training for the non-surgeon crew, to reduce surgical-related mortality. With the advantages of good team consciousness, strong aseptic concept and good psychological quality, the surgeons can quickly adapt to and carry out rescue work under the premise of good self-protection. Surgeons need to develop critical care management concepts and focus on the critical care support equipment. Some suggestions are put forward for the standardized training of resident surgeons to cultivate compound talents. It is hoped that this article can lead to the thinking of how to participate in the emergency medical rescue of infectious diseases among surgeons and provide some enlightenment for future surgical education.

FRI0530 THE PREVALENCE AND DETERMINANTS OF SLEEP PROBLEMS IN PATIENTS ACROSS RHEUMATIC DISEASES AND THEIR CORRELATION WITH DISEASE INDICES USING THE ROUTINE ASSESSMENT OF PATIENT INDEX DATA 3 (RAPID3) QUESTIONNAIRE

Background:

Sleep problems are common in rheumatology patients. RAPID3 is a patient reported outcome measure (PROM) that efficiently screens for problems with sleep, anxiety or depression in routine care.

Objectives:

To study prevalence and determinants of self-reported sleep problems across rheumatic diseases in Rheumatology clinics in Singapore, and its correlation with disease indices.

Methods:

RAPID3 questionnaire was filled electronically over 6 months. Demographic data and SNOWMED diagnoses codes were matched through hospital electronic medical records. RAPID3 comprised of 3 questions measuring the extent of difficulty getting a good night’s sleep and dealing with anxiety or depression. Significant problems were considered if they had “much difficulty” or were “unable to do” the component. The relationship of sleep with anxiety, depression, physical function (measured by modified health assessment questionnaire, mdHAQ), pain and patient global assessment (using visual analogue scale, VAS), was evaluated using Pearson’s correlation. Factors associated with significant sleep problems were evaluated by logistic regression.

Results:

4078 patients [mean (SD) age 55.8 (16.3) years, 67.9% female, 70.6% Chinese] were invited to participate, of which 2625 (64.4%) responded. SNOMED diagnosis codes were available for 1570 (59.8%) patients- majority had inflammatory arthritides (n= 843, 53.7%) (Figure 1).

Mean mdHAQ was 0.3 (0.5), pain VAS was 2.4 (2.3) and global VAS was 2.6 (2.2). Data on disease duration, clinical features and medications were not available. 39.3%, 27.5% and 23.8% had problems with sleep, anxiety and depression respectively; and 7.3%, 4.5% and 4.3% had significant problems respectively. Sleep moderately correlated with anxiety (r=0.463, p<0.001) and depression (r=0.436, p<0.001) and weakly correlated with mdHAQ (r= 0.289, p<0.001), global (r=0.339, p<0.001) and pain VAS (r= 0.314, p<0.001).

In multivariable logistic regression, significant sleep problems were associated with anxiety (OR 4.733, CI 2.172-10.310, p<0.001), mdHAQ score ≥ 1 (OR 2.920, CI 1.691-5.043, p< 0.001) and pain VAS >3 (OR 1.884, CI 1.093-3.247, p=0.023). Patients with osteoarthritis and fibromyalgia were more likely than those with inflammatory arthritides to have significant sleep problems, though we were unable to adjust for body mass index as data were unavailable (Table 1).

Table 1.

Determinants of significant disturbances in sleep in patients with rheumatic diseases

VariablesUnivariableMultivariableOdds ratio (95% CI)p-valueOdds ratio (95% CI)p-valueGenderFemale1.79 (1.245-2.57)0.0021.49 (0.86-2.59)0.16EthnicityChineseRefRefMalay1.04 (0.62-1.73)0.890.73 (0.33-1.61)0.43Indian1.59 (1.03-2.44)0.040.97 (0.49-1.90)0.92Others1.05 (0.62-1.77)0.870.92 (0.43-2.00)0.84Age (years)1.00 (1.00-1.01)0.36--mdHAQ ≥16.25 (4.46-8.75)<0.0012.92 (1.69-5.04)0.001Pain VAS >34.15 (3.07-5.61)<0.0011.88 (1.09-3.25)0.02Global VAS > 34.25 (3.13-5.76)<0.0011.63 (0.95-2.80)0.07Significant anxiety15.99 (10.71- 23.89)<0.0014.73 (2.17-10.31)<0.001Significant depression15.58 (10.35-23.45)<0.0013.02 (1.29-7.10)0.11Primary rheuma-tological diagnosisInflammatory arthritidesRefRefConnective tissue diseases1.18 (0.73-1.90)0.510.9 (0.51-1.59)0.71Crystal arthritides1.06 (0.48-2.33)0.880.83 (0.34-2.03)0.68Osteoarthritis3.09 (1.31-7.32)0.012.96 (1.19-7.36)0.02Fibromyalgia9.05 (2.04-40.05)0.0049.62 (2.11-43.84)0.003Others1.63 (0.82-3.29)0.171.20 (0.58-2.47)0.63

Conclusion:

Sleep problems are common in rheumatology patients and correlate significantly with disease indices and psychological distress. Rheumatologists should routinely screen for sleep difficulties, especially in patients with osteoarthritis and fibromyalgia.

References: -

Acknowledgments:

Nil.

Disclosure of Interests:

Charlotte Tan: None declared, Peter Cheung: None declared, Manjari Lahiri Grant/research support from: Manjari Lahiri is the site principal investigator for the Singapore National Biologics Register, which is a multi-pharmaceutical funded register, in which industry sponsors provide support through the Chapter of Rheumatologists, Singapore. Dr Lahiri does not personally receive any remuneration.

Data on the theoretical X-Ray attenuation and transmissions for lithium-ion battery cathodes

This article reports the data required for planning attenuation-based X-ray characterisation e.g. X-ray computed tomography (CT), of lithium-ion (Li-ion) battery cathodes. The data reported here is to accompany a co-submitted manuscript (10.1016/j.matdes.2020.108585 [1]) which compares two well-known X-ray attenuation data sources: Henke et al. and Hubbell et al., and applies methodology reported by Reiter et al. to extend this data towards the practical characterisation of prominent cathode materials. This data may be used to extend beyond the analysis reported in the accompanying manuscript, and may aid in the applications for other materials, not limited to Li-ion batteries.

Characteristics of patients with C1 esterase inhibitor deficiency: a single center study

Summary

Hereditary angioedema (HAE) is a primary complement factor deficiency, characterized by recurrent submucosal/subcutaneous swelling episodes. SERPING1 gene defects encoding C1 esterase inhibitor (C1INH) are responsible from the disease. Fifteen patients with HAE are retrospectively evaluated in this study. All patients (n = 15) had HAE type I, 13 were from the same family, other two from two different families. Median age at onset of symptoms was 7 years (2-20); median age on diagnosis, 12 (0,5-41) and median delay in diagnosis, 3 years (0-33). Clinical symptoms were extremity edema(92,3%), facial edema(46%), abdominal pain (46%), genital edema (46%), and laryngeal edema (23%). Some patients suffered from recurrent abdominal pain, had been empirically given colchicine with familial mediterranean fever (FMF) when they admitted. One presented with bullous skin eruption, soon after developed extremity edema. Both resolved spontaneously after C1INH concentrate therapy. Two females suffered from recurrent genital edema after sexual activity. One patient experienced compartment syndrome-like swelling of extremity after playing football. One patient diagnosed with panic attack due to fear of death by asphyxiation, and was diagnosed with HAE disease. A nonsense mutation in exon 8, a missense mutation in exon 2 in SERPING1 gene was present in Family 1 and another patient (P14) from the other family, respectively. Sporadic/autosomal dominant inheritance ratio was 2/3 in the families present in our series. Patients with HAE presents with a large spectrum of symptoms. In mediterranean countries, patients with abdominal attacks may be misdiagnosed with FMF. Thus, health-care professionals should be alert, and put HAE in the first line of differential diagnoses when the disease symptoms are present. Consequently, morbidity/mortality will decrease with effective treatment options.

Predicting grain protein content of field-grown winter wheat with satellite images and partial least square algorithm

Remote sensing has been used as an important means of modern crop production monitoring, especially for wheat quality prediction in the middle and late growth period. In order to further improve the accuracy of estimating grain protein content (GPC) through remote sensing, this study analyzed the quantitative relationship between 14 remote sensing variables obtained from images of environment and disaster monitoring and forecasting small satellite constellation system equipped with wide-band CCD sensors (abbreviated as HJ-CCD) and field-grown winter wheat GPC. The 14 remote sensing variables were normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), optimized soil-adjusted vegetation index (OSAVI), nitrogen reflectance index (NRI), green normalized difference vegetation index (GNDVI), structure intensive pigment index (SIPI), plant senescence reflectance index (PSRI), enhanced vegetation index (EVI), difference vegetation index (DVI), ratio vegetation index (RVI), Rblue (reflectance at blue band), Rgreen (reflectance at green band), Rred (reflectance at red band) and Rnir (reflectance at near infrared band). The partial least square (PLS) algorithm was used to construct and validate the multivariate remote sensing model of predicting wheat GPC. The research showed a close relationship between wheat GPC and 12 remote sensing variables other than Rblue and Rgreen of the spectral reflectance bands. Among them, except PSRI and Rblue, Rgreen and Rred, other remote sensing vegetation indexes had significant multiple correlations. The optimal principal components of PLS model used to predict wheat GPC were: NDVI, SIPI, PSRI and EVI. All these were sensitive variables to predict wheat GPC. Through modeling set and verification set evaluation, GPC prediction models' coefficients of determination (R2) were 0.84 and 0.8, respectively. The root mean square errors (RMSE) were 0.43% and 0.54%, respectively. It indicated that the PLS algorithm model predicted wheat GPC better than models for linear regression (LR) and principal components analysis (PCA) algorithms. The PLS algorithm model's prediction accuracies were above 90%. The improvement was by more than 20% than the model for LR algorithm and more than 15% higher than the model for PCA algorithm. The results could provide an effective way to improve the accuracy of remotely predicting winter wheat GPC through satellite images, and was conducive to large-area application and promotion.

Rapid Recognition of Field-Grown Wheat Spikes Based on a Superpixel Segmentation Algorithm Using Digital Images

Wheat spike number, which could be rapidly and accurately estimated by the image processing technology, serves as the basis for crop growth monitoring and yield prediction. In this research, simple linear iterative clustering (SLIC) was performed for superpixel segmentation of the digital images of field-grown wheat. Firstly, certain characteristic color parameters were extracted and analyzed from the digital images, and the classifiers with the highest accuracy were chosen for subsequent image classification. Next, the main body of wheat spike was extracted through a series of morphological transformation and estimate was performed for each region. Backbone of the head was extracted, and the number of inflection points of backbone was detected. Then the wheat spike number was determined by combining the estimate of inflection points of backbone and the estimate for each region. Finally, the wheat spike number estimate was verified under four nitrogen fertilizer levels. The results were as follows: (1) Super green value (Eg) and normalized red green index (Dgr) were used as classification features to recognize wheat spikes, soil and leaves; (2) compared with pixel-based image processing, wheat spike recognition effect was much better after superpixel segmentation, as the main body of wheat spike extracted was more clear and morphology more intact; and (3) wheat plants had better growth under high nitrogen fertilizer level, and the accuracy of wheat spike number estimation was also the highest, which was 94.01%. The growth status was the worst under no nitrogen fertilizer application, and the accuracy of wheat spikes number estimation was also the lowest, which was only 80.8%. After excluding the no nitrogen condition, the accuracy of wheat spikes number estimation among mixed samples with more uniform growth status was up to 93.8%, which was an increase by 10.1% than before the exclusion. Wheat spikes number estimate based on superpixel segmentation and color features was a rapid and accurate method that was applicable to the field environment. However, this method was not recommended for use when the growth status of wheat was poor or of high heterogeneity. The findings provided reference for field-grown wheat yield estimate.