Clear Background Research Articles

Intervention and Diagnosis Measures Based on Influencing Factors of Lactose Intolerance

Lactose intolerance (LI) is a common condition that often manifests as an inability to properly consume milk and dairy products, resulting in diarrhea, vomiting, and fever. Dietary treatments at this stage are broadly categorized into two approaches: avoidance or control of lactose intake, and supplementation with additional supplements. However, most of the papers are studies conducted on lactose-intolerant neonates. There are gaps in treatments or palliative programs for adolescent and adult patients. This paper analyzes the classification of different types of LI and the factors affecting them, introduces several diagnostic measures, summarizes the existing treatments, and concludes the possibility of advancing the case of neonatal LI treatment to adolescents and adults. It aims to provide a clear background for future exploration of treatment and mitigation methods for LI, providing more dietary choices and more suitable lifestyles for adolescents and adults with LI. However, there is a lack of discussion on treatments for LI other than dietary modifications, especially the measure of using probiotics, which is an area for future research to focus on.

Searching for heavy neutral leptons at a future muon collider

As the planning stages for a high energy muon collider enter a more concrete era, an important question arises as to what new physics could be uncovered. A TeV-scale muon collider is also a vector boson fusion (VBF) factory with a very clean background, and as such it is a promising environment to look for new physics that couples to the electroweak (EW) sector. In this paper, we explore the ability of a future TeV-scale muon collider to search for Majorana and Dirac heavy neutral leptons (HNLs) produced via EW bosons. Employing a model-independent, conservative approach, we present an estimation of the production and decay rate of HNLs over a mass range between 200 GeV and 9.5 TeV in two benchmark collider proposals with s=3, 10 TeV, as well as an estimation of the dominant Standard Model (SM) background. We find that exclusion limits for the mixing between the HNLs and SM neutrinos can be as low as O(10−6). Additionally, we demonstrate that a TeV-scale muon collider allows for the ability to discriminate between Majorana and Dirac type HNLs for a large range of mixing values. Published by the American Physical Society 2024

Highly accelerated non-contrast-enhanced time-resolved 4D MRA using stack-of-stars golden-angle radial acquisition with a self-calibrated low-rank subspace reconstruction.

To develop a highly accelerated non-contrast-enhanced 4D-MRA technique by combining stack-of-stars golden-angle radial acquisition with a modified self-calibrated low-rank subspace reconstruction. A low-rank subspace reconstruction framework was introduced in radial 4D MRA (SUPER 4D MRA) by combining stack-of-stars golden-angle radial acquisition with control-label k-space subtraction-based low-rank subspace modeling. Radial 4D MRA data were acquired and reconstructed using the proposed technique on 12 healthy volunteers and 1 patient with steno-occlusive disease. The performance of SUPER 4D MRA was compared with two temporally constrained reconstruction methods (golden-angle radial sparse parallel [GRASP] and GRASP-Pro) at different acceleration rates in terms of image quality and delineation of blood dynamics. SUPER 4D MRA outperformed the other two reconstruction methods, offering superior image quality with a clear background and detailed delineation of cerebrovascular structures as well as great temporal fidelity in blood flow dynamics. SUPER 4D MRA maintained excellent performance even at higher acceleration rates. SUPER 4D MRA is a promising technique for highly accelerating 4D MRA acquisition without comprising both temporal fidelity and image quality.

Spectral-based estimation of chlorophyll content and determination of background interference mechanisms in low-coverage rice

The chlorophyll content is a vital indicator of rice growth and nutritional status. However, estimating the rice chlorophyll content using spectral-based techniques at the early tillering stage is challenging because of background interference. Using the energy conservation principle, this study explained the spectral variation and background interference mechanisms of clear, muddy, and green algae-covered backgrounds. We developed mathematical interference models for the three types of backgrounds and determined their interference degree and influence mode. We developed rice chlorophyll content estimation models for unclassified and classified (clear, muddy, and green algae-covered) backgrounds using 12 preprocessing, four wavelength selection, and three modeling methods, and we explored the importance of background classification. Moreover, we found that the optimal chlorophyll content estimation model for the clear background was SS+UVE+CNN, with R2 and RMSE values of 0.786 and 13.191 in the training set and 0.741 and 15.327 in the test set, respectively; that for the muddy background was MSC+GA+CNN, with R2 and RMSE values of 0.914 and 10.425 in the training set and 0.660 and 16.844 in the test set, respectively; and that for the green algae-covered background was DC+GA+CNN, with R2 and RMSE values of 0.904 and 9.111 in the training set and 0.688 and 17.694 in the test set, respectively. Our study could provide valuable insights into reducing and correcting background interference during proximal remote sensing data collection.

FIX Protocol: The Backbone of Financial Trading

The Financial Information exchange, commonly known as the FIX protocol, is a key component in the trading market infrastructure. Hence, this paper delivers a clear background on the FIX protocol: its structure, role, and its importance in the financial markets space. In this paper, we look at the background and development of the FIX protocol as well as the functions and usefulness of this protocol in the conducting of trading electronically. Sect. 2 from the literature survey of various studies and application of the FIX protocol in conjunction with distinct financial markets. The 'Methodology' subchapter explains how this FIX protocol functions practically at the level of messages' formatting, sessions' employing, and an application of data protection measures. Last of all, the conclusion and recommendation, as well as findings on the effects of FIX protocol on trading efficiency, market transparency, and such costs, are also provided. The conclusion provides a brief resume of the papers and notes the outlook of the implication of the FIX protocol considering the ever-expanding digital frontiers in the financial sector.

Exploration for sorting serum exosome as a measure of spinal cord injury severity

This study aimed to extract exosomes from the serum of rats with spinal cord injury and explore their potential as indicators for assessing the severity of spinal cord injury. Control rats were compared with rats in the mild and severe injury groups. Exosomes were isolated from rat serum using an optimized threshold condition with an ultra-high-speed flow cell sorter. Nanoparticle tracking analysis (NTA) was performed to determine the size distribution of exosomes, transmission electron microscopy (TEM) was used to observe the morphology of exosomes, and Western blot analysis was conducted to assess the expression of CD63(cluster of differentiation antigen 63) and CD9(cluster of differentiation antigen 9) proteins on the surface of exosomes. NanoFlow cytometry was utilized to evaluate the expression of CD63 and CD9. The optimal threshold condition for flow cytometry of exosomes was determined to be 0.002. Exosomes exhibited a cup-shaped morphology with a clean background. The percentages of exosomes in the control, mild injury, and severe injury groups were determined to be 6.4 × 1011 particles/mL, 6.2 × 1011 particles/mL, and 2.3 × 1011 particles/mL, respectively. The mean sizes of exosomes were 129.25 nm ± 18.3, 117.93 nm ± 39.9, and 116.38 nm ± 36.5, respectively. The percentages of CD9 were 15.5% ± 0.037, 10.4% ± 0.082, and 7.4% ± 0.051, while the percentages of CD63 were 1.2% ± 0.025, 2.6% ± 0.067, and 1.5% ± 0.038 for the control, mild injury, and severe injury groups, respectively. Comparison analysis revealed that the diameter of exosomes in rat serum ranged from 80 nm to 150 nm. The percentage of exosomes decreased, and CD9 expression significantly decreased as the severity of spinal cord injury increased. Flow cytometry allows for the isolation of exosomes from serum with high purity and uniform particle size. The percentage of serum exosomes and the expression of CD9 may serve as potential diagnostic indicators for spinal cord injury models.

Cytomorphologic comparison of upper urinary tract urothelial carcinomas and renal cell carcinomas on urine cytology.

Compared to urothelial carcinomas (UCs), the cytomorphology of renal cell carcinomas (RCCs) is underdescribed. This study aims to investigate whether UCs and RCCS of the upper urinary tract can be differentiated cytologically, and to identify distinguishing cytomorphological features. Consecutive urine cytology specimens with atypical/C3, suspicious/C4 or malignant/C5 diagnoses matched with a nephrectomy or ureterectomy specimen with UC or RCC over a 15-year period were reviewed for cellularity, architecture, background composition and cytomorphologic features. Totally 132 specimens were retrieved, comprising 24 RCCs and 108 UCs. Clear cell RCC (CCRCC) (n = 18) was the most common RCC. Urine cytology specimens from UC showed a trend of higher cellularity (p = 0.071) against RCC and was significant in subgroup analysis with CCRCC (p < .001). Epithelial structures in sheets, tubules, and papillae were exclusive in specimens of UC (p < .05). For background features, squamous cells were more common for RCC (p = .006) including CCRCC (p = .003), whereas polymorphs (p = .011) and necrotic material (p = .010) were associated with UC. Average nuclear size was larger and nuclear size variation (p < .001) and nuclear-cytoplasmic ratio (p = .001) were greater in UC (p = .001) than RCC. Comparing RCC to high-grade UCs only, nuclear-cytoplasmic ratio maintained statistical significance (p = .006) while average nuclear size showed a trend (p = .063). A clean background free of tumor necrosis and polymorphs, and the lack of complex tumor fragments favors RCC. UCs also display larger nuclear size, higher nuclear size variation and nuclear-cytoplasmic ratio. These cytomorphological features with corroboration of clinical/radiological findings, can aid in raising a diagnosis of RCC.

Unveiling a Novel Antidote for Deoxynivalenol Contamination: Isolation, Identification, Whole Genome Analysis and In Vivo Safety Evaluation of Lactobacillus rhamnosus MY-1.

Deoxynivalenol (DON) is a global contaminant found in crop residues, grains, feed, and animal and human food. Biodegradation is currently the best solution for addressing DON pollution. However, efficient detoxification bacteria or enzymes that can be applied in complex matrices are lacking. The aim of this study was to isolate a DON-detoxifying probiotic strain with a high degradation rate, a good safety profile, and a clear genetic background. One hundred and eight bacterial strains were isolated from 300 samples collected from a school farm and surrounding livestock farms. A new DON-degrading strain, Lactobacillus rhamnosus MY-1 (L. rhamnosus MY-1), with a degradation rate of 93.34% after 48 h and a comprehensive degradation method, was identified. Then, MY-1 at a concentration of 1 × 108 CFU/mL was administered to mice in a chronic intoxication experiment for 28 days. The experimental group showed significantly higher weight gain and exhibited good production performance compared to the control group. The length of the ileal villi in the experimental group was significantly longer than that in the control group. The expression of pro-inflammatory cytokines decreased, while the expression of anti-inflammatory factors increased in the experimental group. Whole-genome analysis revealed that most of the MY-1 genes were involved in carbohydrate metabolism and membrane transport, with a cluster of secondary metabolite genes encoding antimicrobial properties. In summary, this study successfully identified a Lactobacillus strain with good safety performance, high DON degradation efficiency, and a clear genetic background, providing a new approach for the treatment of DON contamination.

Feasible and economic DIY procedures of a hand-held fluorescence detector set-FluorDetector to assist laboratory course development.

Fluorescence-related experimental techniques play an important role in biochemistry, molecular biology, and cell biology. However, fluorescence-related experiments are rarely included in the laboratory courses of most Chinese universities. This is mainly due to the conflict between large class size (50-60 students in one room) and funding/space limitations to purchase and accommodate enough fluorescence detection equipment. Here, we proposed feasible and economical Do It Yourself (DIY) procedures of a hand-held fluorescence detector set-FluorDetector to support the development of laboratory courses. Tested on several samples, clear fluorescence signals could be directly observed by FluorDetector and photographed with a smartphone. In addition, FluorDetector was able to turn a conventional stereomicroscope into a fluorescence stereomicroscope, detecting fluorescence signals with clean background. FluorDetector is easy to make with a 3D printer, with an extremely low cost ($200 each) when compared with a commercial fluorescence microscope or fluorescence stereomicroscope, and almost as sensitive as a microplate reader in measuring fluorescence. Therefore, FluorDetector is a possible strategy to solve the problem and help to integrate fluorescence-related experimental modules in laboratory courses.

Comparison of plane-to-sky contrast and detection range performance in the visible, short-wave infrared, mid-wave infrared, and long-wave infrared bands

Recent advances in uncrewed aerial vehicle (UAV) technology have the potential to benefit diverse civil, commercial, scientific, and defense projects. Many applications would benefit from beyond visual line-of-sight (BVLOS) operations. Such operations require automated safety systems that allow uncrewed aircraft to avoid collisions with both crewed and uncrewed aircraft. Electro-optical and infrared (EO/IR) sensors are commonly employed by aircraft collision avoidance systems. This study compares plane-to-sky contrast in the VIS (0.4 to 0.7 µm), SWIR (1 to 1.7 µm), MWIR (3 to 5 µm), and LWIR (8 to 14 µm) to determine which band is most sensitive to an aircraft signal against a clear sky background. Contrast in the two reflective bands (VIS and SWIR) is determined in terms of equivalent reflectivity, and contrast in the two emissive bands (MWIR and LWIR) is determined in terms of equivalent blackbody temperature. Sensitivity data are then used alongside resolution specifications to estimate the detection performance at-range using the night vision integrated performance model (NVIPM). The results are extrapolated to a maritime atmosphere using MODTRAN. An analysis of the range performance and recommendations on band selection are provided for reference in the design of EO/IR systems for aircraft collision avoidance. Future research may study the band performance at night and against other backgrounds (e.g. clouds, ocean, ground terrain).

Recent Advances and Multiple Strategies of Monoterpenoid Overproduction in Saccharomyces cerevisiae and Yarrowia lipolytica.

Monoterpenoids are an important subclass of terpenoids that play important roles in the energy, cosmetics, pharmaceuticals, and fragrances fields. With the development of biotechnology, microbial synthesis of monoterpenoids has received great attention. Yeasts such Saccharomyces cerevisiae and Yarrowia lipolytica are emerging as potential hosts for monoterpenoids production because of unique advantages including rapid growth cycles, mature gene editing tools, and clear genetic background. Recently, advancements in metabolic engineering and fermentation engineering have significantly enhanced the accumulation of monoterpenoids in cell factories. First, this review introduces the biosynthetic pathway of monoterpenoids and comprehensively summarizes the latest production strategies, which encompass enhancing precursor flux, modulating the expression of rate-limited enzymes, suppressing competitive pathway flux, mitigating cytotoxicity, optimizing substrate utilization, and refining the fermentation process. Subsequently, this review introduces four representative monoterpenoids. Finally, we outline the future prospects for efficient construction cell factories tailored for the production of monoterpenoids and other terpenoids.

RCDNet: An Interpretable Rain Convolutional Dictionary Network for Single Image Deraining.

As common weather, rain streaks adversely degrade the image quality and tend to negatively affect the performance of outdoor computer vision systems. Hence, removing rains from an image has become an important issue in the field. To handle such an ill-posed single image deraining task, in this article, we specifically build a novel deep architecture, called rain convolutional dictionary network (RCDNet), which embeds the intrinsic priors of rain streaks and has clear interpretability. In specific, we first establish a rain convolutional dictionary (RCD) model for representing rain streaks and utilize the proximal gradient descent technique to design an iterative algorithm only containing simple operators for solving the model. By unfolding it, we then build the RCDNet in which every network module has clear physical meanings and corresponds to each operation involved in the algorithm. This good interpretability greatly facilitates an easy visualization and analysis of what happens inside the network and why it works well in the inference process. Moreover, taking into account the domain gap issue in real scenarios, we further design a novel dynamic RCDNet, where the rain kernels can be dynamically inferred corresponding to input rainy images and then help shrink the space for rain layer estimation with few rain maps, so as to ensure a fine generalization performance in the inconsistent scenarios of rain types between training and testing data. By end-to-end training such an interpretable network, all involved rain kernels and proximal operators can be automatically extracted, faithfully characterizing the features of both rain and clean background layers and, thus, naturally leading to better deraining performance. Comprehensive experiments implemented on a series of representative synthetic and real datasets substantiate the superiority of our method, especially on its well generality to diverse testing scenarios and good interpretability for all its modules, compared with state-of-the-art single image derainers both visually and quantitatively. Code is available at https://github.com/hongwang01/DRCDNet.

Evaluation and comparison of MODIS and MISR aerosol products with ground-based monitoring stations in the Amazon Basin

This study evaluates the long-term accuracy of six daily aerosol optical depth (AOD) datasets derived from the Moderate Resolution Imaging Spectroradiometers (MODIS) Dark Target (DT) at 3 and 10 km resolution, Deep Blue (DB), combined DT and DB datasets (DTB) and MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms and the Multi-angle Imaging SpectroRadiometer (MISR) Version 23, by comparing them with ground-based AOD observations in 18 Aerosol Robotic Network (AERONET) sites over the Amazon basin between 2000 and 2022. The AOD retrieval accuracy was also assessed under varying seasons, aerosol loading, particle size, elevation and land cover type. Overall results showed that Terra and Aqua-MODIS DB and MISR algorithms perform better, with about 88% of AOD retrievals within the expected error range. However, MISR presented a systematic high negative bias. MODIS DT 3 km overestimated AOD values and indicated unsatisfactory retrieval accuracy in almost all scenarios. MODIS and MISR retrievals showed improved performance under low aerosol loading, whereas Aqua-MODIS MAIAC under intermediate conditions (AOD>0.2). MISR indicated a large dependence on a coarse mode-dominated environment with considerable negative bias. Terra-MODIS MAIAC retrievals exhibited a smaller dependence for aerosol particle size distribution, while Terra-MODIS DB performed better for fine mode and Aqua-MODIS DB for coarse dominance. MAIAC also performed well under polluted scenarios in the dry season in contrast to the majority of satellite-based AOD retrievals, which showed good agreement under clean background conditions in the wet season. Almost all satellite-based retrievals showed higher uncertainty under extremely high altitudes (>3000 m) followed by non-satisfactory correlation and significant biases. Additionally, almost all satellite-based AOD retrievals indicated poor performance as vegetation coverage increases. On the contrary, MISR showed higher accuracy under forest type. In general, MODIS and MISR retrieval accuracy demonstrated distinct levels of dependencies that require further improvement in the Amazon Basin.

Comparative Study of Modified Ultrafast Papanicolaou and Standard Papanicolaou Staining Technique for the Assessment of Cervical Smears

Introduction: Cervical invasive carcinoma is one of the most frequent cancers in the world, and it can be prevented with screening. The papanicolaou (Pap) smear is the most common screening procedure. Pap staining, as it is now done, is costly, requires a large amount of alcohol, and takes a long time. Materials and Methods: A total of 170 patients were recruited. One hundred and sixty-six patients, considering eligibility criteria, undergoing Pap smear test. Eligibility criteria: Age: 18–49 years females, who did not have a total hysterectomy done, who consented to participate in the study. Each patient had two smears taken on glass slides. Standard Pap smears were fixed for at least 15 min in 95% ethanol. The other smear was air-dried before being fixed with alcohol formalin and stained with modified ultrafast Pap (MUFP) stain. A comparison of two different techniques was made on the basis of cytomorphological features. Results: In studied smears, a clean background was seen in 18.24% and 14.12% of the cases in Pap stain and MUFP, respectively. Kappa analysis found a good correlation between Pap stain and MUFP (kappa: 0.81, P &lt; 0.01). Crisp chromatin was seen in 89.41% and 67.65% of MUFP and Pap staining, respectively. About 88.82% of MUFP stains showed optimal cytoplasmic details and the same was revealed by 81.18% of Pap stains. MUFP has a better quality index (QI) as compared to Pap staining as no case in MUFP had QI of &lt; 0.80 with a statistically significant difference as P &lt; 0.05. Conclusion: MUFP is a simple, user-friendly, affordable, and less time-consuming alternative in low-resource areas in comparison to the traditional technique for mass cervical cancer screening.

Microwave-assisted and methanol/acetic acid-free method for rapid staining of proteins in SDS-PAGE gels

We describe a microwave-assisted, methanol and acetic acid-free, inexpensive method for rapid staining of SDS-PAGE proteins. Only citric acid, benzoic acid, and Coomassie brilliant blue G-250 (CBG) were used. Microwave irradiation reduced the detection duration, and proteins in a clear background were visualized within 30 min of destaining, after 2 min of fixing and 12 min of staining. By using this protocol, comparable band intensities were obtained to the conventional methanol/acetic acid method.

Fluorine-19 labeling of the tryptophan residues in the G protein-coupled receptor NK1R using the 5-fluoroindole precursor in Pichia pastoris expression.

In NMR spectroscopy of biomolecular systems, the use of fluorine-19 probes benefits from a clean background and high sensitivity. Therefore, 19F-labeling procedures are of wide-spread interest. Here, we use 5-fluoroindole as a precursor for cost-effective residue-specific introduction of 5-fluorotryptophan (5F-Trp) into G protein-coupled receptors (GPCRs) expressed in Pichia pastoris. The method was successfully implemented with the neurokinin 1 receptor (NK1R). The 19F-NMR spectra of 5F-Trp-labeled NK1R showed one well-separated high field-shifted resonance, which was assigned by mutational studies to the "toggle switch tryptophan". Residue-selective labeling thus enables site-specific investigations of this functionally important residue. The method described here is inexpensive, requires minimal genetic manipulation and can be expected to be applicable for yeast expression of GPCRs at large.

FMRNet: Image Deraining via Frequency Mutual Revision

The wavelet transform has emerged as a powerful tool in deciphering structural information within images. And now, the latest research suggests that combining the prowess of wavelet transform with neural networks can lead to unparalleled image deraining results. By harnessing the strengths of both the spatial domain and frequency space, this innovative approach is poised to revolutionize the field of image processing. The fascinating challenge of developing a comprehensive framework that takes into account the intrinsic frequency property and the correlation between rain residue and background is yet to be fully explored. In this work, we propose to investigate the potential relationships among rain-free and residue components at the frequency domain, forming a frequency mutual revision network (FMRNet) for image deraining. Specifically, we explore the mutual representation of rain residue and background components at frequency domain, so as to better separate the rain layer from clean background while preserving structural textures of the degraded images. Meanwhile, the rain distribution prediction from the low-frequency coefficient, which can be seen as the degradation prior is used to refine the separation of rain residue and background components. Inversely, the updated rain residue is used to benefit the low-frequency rain distribution prediction, forming the multi-layer mutual learning. Extensive experiments demonstrate that our proposed FMRNet delivers significant performance gains for seven datasets on image deraining task, surpassing the state-of-the-art method ELFormer by 1.14 dB in PSNR on the Rain100L dataset, while with similar computation cost. Code and retrained models are available at https://github.com/kuijiang94/FMRNet.

Transient Glimpses: Unveiling Occluded Backgrounds through the Spike Camera

The de-occlusion problem, involving extracting clear background images by removing foreground occlusions, holds significant practical importance but poses considerable challenges. Most current research predominantly focuses on generating discrete images from calibrated camera arrays, but this approach often struggles with dense occlusions and fast motions due to limited perspectives and motion blur. To overcome these limitations, an effective solution requires the integration of multi-view visual information. The spike camera, as an innovative neuromorphic sensor, shows promise with its ultra-high temporal resolution and dynamic range. In this study, we propose a novel approach that utilizes a single spike camera for continuous multi-view imaging to address occlusion removal. By rapidly moving the spike camera, we capture a dense stream of spikes from occluded scenes. Our model, SpkOccNet, processes these spikes by integrating multi-view spatial-temporal information via long-short-window feature extractor (LSW) and employs a novel cross-view mutual attention-based module (CVA) for effective fusion and refinement. Additionally, to facilitate research in occlusion removal, we introduce the S-OCC dataset, which consists of real-world spike-based data. Experimental results demonstrate the efficiency and generalization capabilities of our model in effectively removing dense occlusions across diverse scenes. Public project page: https://github.com/Leozhangjiyuan/SpikeDeOcclusion.

Three-Dimensional Reconstruction Pre-Training as a Prior to Improve Robustness to Adversarial Attacks and Spurious Correlation.

Ensuring robustness of image classifiers against adversarial attacks and spurious correlation has been challenging. One of the most effective methods for adversarial robustness is a type of data augmentation that uses adversarial examples during training. Here, inspired by computational models of human vision, we explore a synthesis of this approach by leveraging a structured prior over image formation: the 3D geometry of objects and how it projects to images. We combine adversarial training with a weight initialization that implicitly encodes such a prior about 3D objects via 3D reconstruction pre-training. We evaluate our approach using two different datasets and compare it to alternative pre-training protocols that do not encode a prior about 3D shape. To systematically explore the effect of 3D pre-training, we introduce a novel dataset called Geon3D, which consists of simple shapes that nevertheless capture variation in multiple distinct dimensions of geometry. We find that while 3D reconstruction pre-training does not improve robustness for the simplest dataset setting, we consider (Geon3D on a clean background) that it improves upon adversarial training in more realistic (Geon3D with textured background and ShapeNet) conditions. We also find that 3D pre-training coupled with adversarial training improves the robustness to spurious correlations between shape and background textures. Furthermore, we show that the benefit of using 3D-based pre-training outperforms 2D-based pre-training on ShapeNet. We hope that these results encourage further investigation of the benefits of structured, 3D-based models of vision for adversarial robustness.

A national registry-based study of ethnic differences in people with multiple sclerosis in Iran

ObjectiveThe relationship between MS and ethnicity has been understudied in the Middle East compared to the United States and Europe. As Iran as the highest prevalence of MS in the Middle East, we decided to investigate the demographic and clinical differences in people with MS (pwMS) from major ethnicities Iran. MethodsIn a cross-sectional study using data from National Multiple Sclerosis Registry in Iran. PwMS from six provinces were chosen and interviewed for determining their ethnicity. Persians (Fars), Kurds, Lurs, Azeris and Arabs with a clear ethnic background were included. Recorded data from the registry was used to compare the demographic and clinical features. ResultsA total of 4015 pwMS (74.2% female) were included in the study with an average age of 36.76 ± 9.68 years. Persians and Kurds had the highest percentage of pwMS in youngest and oldest age groups, respectively, with 2.9% and 5.7% (p<0.01). The highest average age of onset was seen in Persians (29.47 ± 8.89) and the lowest observed in Mazandaranis (26.82 ± 7.68, p<0.01). Azeris and Kurds had the highest proportions of pwMS diagnosed <18 and >55, at rates of 12% and 1.6%, respectively (p<0.01). There were statistically significant differences in distribution of phenotypes (p<0.01) and time to progression to secondary progressive MS (p<0.01) such that Persians had the highest rate of clinically isolated syndrome (CIS) at 19.3% and Arabs had highest rates of relapsing-remitting MS (86.2%) and secondary progressive MS (16.4%). Lurs, Azeris and Mazandaranis had significantly more patients progressing to secondary-progressive MS <5 years from diagnosis (p<0.01). There was a significant difference in number of relapses between the ethnicities (p<0.01) with Lurs having the highest proportion of participants reporting >4 relapses with 23.0% and Azeris having the highest percentage of pwMS reporting no relapse (53.0%). Kurds had the highest Expanded Disability Status Scale (EDSS) average at 2.93 ± 1.99 and Lurs had the lowest with 1.28 ± 1.25 (p<0.01). The differences in prevalence of positive family history for the whole cohort between ethnicities were significant (P=0.02), ranging from 12.8% in Kurds to 19.6% in Persians. ConclusionWe found Persians to have higher rates of pediatric MS and higher rates of CIS. Kurds and Lurs had higher and lower EDSS scores, respectively. Lurs and Persian had higher annual relapse rates. We also found lower rates of SPMS among Arabs and earlier progression to SPMS in Lurs, Azeris and Mazandaranis. Such differences highlight the importance of the potential role of ethnicities in diagnosis and prognosis of MS, especially considering their observation within the geographical limits of a single country.