OME-Zarr: a cloud-optimized bioimaging file format with international community support

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself-OME-Zarr-along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain-the file format that underlies so many personal, institutional, and global data management and analysis tasks.

OME-Zarr: a cloud-optimized bioimaging file format with international community support

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself -- OME-Zarr -- along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.

Optimization of anastomotic technique and gastric conduit perfusion with hyperspectral imaging and machine learning in an experimental model for minimally invasive esophagectomy

INTRODUCTION

Esophagectomy is the mainstay of esophageal cancer treatment, but anastomotic insufficiency related morbidity and mortality remain challenging for patient outcome. Therefore, the objective of this work was to optimize anastomotic technique and gastric conduit perfusion with hyperspectral imaging (HSI) for total minimally invasive esophagectomy (MIE) with linear stapled anastomosis.

MATERIAL AND METHODS

A live porcine model (n = 58) for MIE was used with gastric conduit formation and simulation of linear stapled side-to-side esophagogastrostomy. Four main experimental groups differed in stapling length (3 vs. 6 cm) and simulation of anastomotic position on the conduit (cranial vs. caudal). Tissue oxygenation around the anastomotic simulation site was evaluated using HSI and was validated with histopathology.

RESULTS

The tissue oxygenation (ΔStO₂) after the anastomotic simulation remained constant only for the short stapler in caudal position (-0.4 ± 4.4%, n.s.) while it was impaired markedly in the other groups (short-cranial: -15.6 ± 11.5%, p = 0.0002; long-cranial: -20.4 ± 7.6%, p = 0.0126; long-caudal: -16.1 ± 9.4%, p < 0.0001). Tissue samples from avascular stomach as measured by HSI showed correspondent eosinophilic pre-necrotic changes in 35.7 ± 9.7% of the surface area.

CONCLUSION

Tissue oxygenation at the site of anastomotic simulation of the gastric conduit during MIE is influenced by stapling technique. Optimal oxygenation was achieved with a short stapler (3 cm) and sufficient distance of the simulated anastomosis to the cranial end of the gastric conduit. HSI tissue deoxygenation corresponded to histopathologic necrotic tissue changes. The experimental model with HSI and ML allow for systematic optimization of gastric conduit perfusion and anastomotic technique while clinical translation will have to be proven.

Plasma membrane topography governs the 3D dynamic localization of IgM B cell antigen receptor clusters

B lymphocytes recognize bacterial or viral antigens via different classes of the B cell antigen receptor (BCR). Protrusive structures termed microvilli cover lymphocyte surfaces, and are thought to perform sensory functions in screening antigen-bearing surfaces. Here, we have used lattice light-sheet microscopy in combination with tailored custom-built 4D image analysis to study the cell-surface topography of B cells of the Ramos Burkitt's Lymphoma line and the spatiotemporal organization of the IgM-BCR. Ramos B-cell surfaces were found to form dynamic networks of elevated ridges bridging individual microvilli. A fraction of membrane-localized IgM-BCR was found in clusters, which were mainly associated with the ridges and the microvilli. The dynamic ridge-network organization and the IgM-BCR cluster mobility were linked, and both were controlled by Arp2/3 complex activity. Our results suggest that dynamic topographical features of the cell surface govern the localization and transport of IgM-BCR clusters to facilitate antigen screening by B cells.

AB1175 EFFECTS OF THE COVID-19 DISEASE ON AXIAL SPONDYLOARTHRITIS DISEASE FLARE

Background

Rheumatological disease flares may be seen after many infections. However, our knowledge for the post-COVID axial spondyloarthritis (SpA) flares and its related factors is limited.

Objectives

We aimed to evaluate disease activity and factors that may be associated with disease activity in axial SpA patients in post-COVID period.

Methods

We retrospectively assessed the axial SpA patients who have had COVID-19 disease confirmed by a positive SARS-CoV-2 polymerized chain reaction (PCR) test result. Demographics, comorbid diseases, active medical treatments for SpA and information regarding COVID-19 clinical courses were collected from medical records. PCR positive patients were reached via telephone and Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) scored for pre- and post-COVID SpA symptoms. An increase of ≥2 points in the BASDAI score was defined as flare, and SpA groups with and without flare were compared. Factors predicting SpA flare were also analyzed by the logistic regression analysis.

Results

A total of 48 axial SpA patients were included in our study, 65% of them male and the mean±SD age was 42.3±8.6 years. Post-COVID SpA flare was seen in 38% patients. Demographic, clinical, medical features of the SpA patients and COVID-19 disease severity were similar between Flare and No flare groups. In comparison of the COVID-19 symptoms, although most of the COVID-19 related symptoms were similar between two groups, the frequency of the back pain and diarrhea were higher in the Flare group than No flare group. But in multivariate analysis, only history of the inflammatory bowel disease had an increased risk for post-COVID SpA flare (Table 1).

Table 1.

Results from adjusted logistic regression model of the spondyloarthritis flare

VariablesEnter MethodBackward:Conditional MethodOR95% CIpOR95% CIpSmoking0.1250.013-1.2330.075Multimorbidity0.2440.047-1.2560.091Inflammatory bowel disease33.2211.236-892.7200.03734.3821.571-752.4620.025Fever1.5820.334-7.4860.563Arthralgia3.4380.233-50.6300.368Back pain1.0540.080-13.8950.968

OR: Odds ratio, CI: Confidence Interval

Conclusion

The presence of inflammatory bowel disease statistically significant related post-COVID SpA flares. In addition, diarrhea and back pain symptoms in COVID-19 disease may be stimulating factors for SpA flares but we found no effect of rheumatological therapies.

Disclosure of Interests

None declared

AB1142 EFFECTS OF SULFASALAZINE USED IN AXIAL SPONDYLOARTHRITIS ON COVID-19 OUTCOMES: REAL-LIFE DATA FROM A SINGLE CENTER

Background

Compared to biologic-agents, little is known about effects of sulfasalazine used for axial spondyloarthritis(AxSpA) on COVID-19 outcomes.

Objectives

So, we aimed to understand the impact of sulfasalazine on COVID-19 in AxSpA patients.

Methods

This was a retrospective study from a single center which included 2344 AxSpA patients. We analyzed 219 of 406 confirmed COVID-19 patients from March 2020 to July 2021. The primary outcome was COVID-19 severity in terms of COVID-19 pneumonia, hospitalization rate and length of hospitalization. Analyses were stratified according to use of sulfasalazine and/or biologic-agents.

Results

Most of the patients were male(59%) with a mean age of 45.0 years. Peripheral arthritis was present in 35% and uveitis in 15%. In total, sulfasalazine was used in 42% and biologic-agent in 42%. COVID-19 pneumonia detected in 16%, hospitalization required in 14% and median(IQR) duration of hospitalization was 10(8) days. Two patients died due to COVID-19. The sulfasalazine users had higher age, more frequent COVID-19 pneumonia, hospitalization and longer hospitalization. After biologic-agent users were excluded, the sulfasalazine group had again longer hospitalization. When patients regrouped as sulfasalazine monotherapy, sulfasalazine+biologic and biologic monotherapy, in pairwise comparisons, sulfasalazine monotherapy group had a higher frequency of COVID-19 pneumonia than biologic monotherapy group(p=0.008).

Conclusion

Although sulfasalazine seemed to be related with increased rates of COVID-19 pneumonia and hospitalization, this impact diminished after exclusion of biologic-agent users. Sulfasalazine monotherapy and sulfasalazine+biologic therapy might be associated with development of COVID-19 pneumonia, compared to biologic monotherapy. Our results imply sulfasalazine may be related with worse disease course AxSpA patients with COVID-19.

Disclosure of Interests

None declared

Expression of a human cDNA in moss results in spliced mRNAs and fragmentary protein isoforms

Production of biopharmaceuticals relies on the expression of mammalian cDNAs in host organisms. Here we show that the expression of a human cDNA in the moss Physcomitrium patens generates the expected full-length and four additional transcripts due to unexpected splicing. This mRNA splicing results in non-functional protein isoforms, cellular misallocation of the proteins and low product yields. We integrated these results together with the results of our analysis of all 32,926 protein-encoding Physcomitrella genes and their 87,533 annotated transcripts in a web application, physCO, for automatized optimization. A thus optimized cDNA results in about twelve times more protein, which correctly localizes to the ER. An analysis of codon preferences of different production hosts suggests that similar effects occur also in non-plant hosts. We anticipate that the use of our methodology will prevent so far undetected mRNA heterosplicing resulting in maximized functional protein amounts for basic biology and biotechnology.

AB0157 PREVALENCE OF SARCOPENIA AND CLINICAL IMPLICATIONS IN NEWLY DIAGNOSED RHEUMATOID ARTHRITIS PATIENTS

Background:

The aim of this study is to determine the frequency of sarcopenia at the time of diagnosis in RA patients, evaluate the effects of sarcopenia on RA disease activity, prognosis and examine the factors that may be associated with sarcopenia.

Objectives:

To determine the frequency of sarcopenia at the time of diagnosis in rheumatoid arthritis (RA) patients, assessing disease activity and factors that may be associated with sarcopenia and observe effects of treatment on sarcopenia.

Methods:

A prospective study was conducted on RA patients with newly diagnosed. Patients were evaluated twice, at the time of diagnosis and three months after the initiation of treatment. Demographic data, anthropometric measurements, disease activity scores and sarcopenia status were recorded. Sarcopenia was evaluated with grip strength and bioelectric impedance. The results were also compared with healthy volunteers.

Results:

Hand grip strength (p<0.001), skeletal muscle mass (p=0.009) and skeletal muscle mass index (p=0.032) were found to be reduced in RA patients compared to the control group. The frequency of sarcopenia in RA at onset of diagnosis was found to be 31.5%. There was a significant decrease in the rate of sarcopenia after three months of treatment (31.5% versus 8.7%; p=0.046).

Conclusion:

Sarcopenia was found in approximately one third of the patients with newly diagnosed RA in our study. With treatment, sarcopenia improved significantly. RA patients should be evaluated in terms of sarcopenia besides evaluating joint and extra-articular findings at the time of diagnosis. Early detection and treatment planning may improve the quality of life.

Figure 1.

Distribution of skeletal muscle mass index (SMMI) and prevalence of sarcopenia in RA and control groups

Table 1.

Demographics, clinical features, anthropometric measurements and disease activity scores of sarcopenic and non-sarcopenic RA patients

RA without sarcopenian=37RA with sarcopenian=17pAge, mean (SD), years47,3 (12,8)58,0 (16)0,011*Gender, female, n (%)27 (73)9 (52,9)0,215Marital status, married, n (%)34 (91,9)13 (76,5)0,258Tobacco consumption, n (%) Active smoker10 (27)5 (29,4)0,086 Ex-smoker8 (21,6)8 (47,1) Never smoker19 (51,4)4 (23,5)Alcohol consumption, n (%) Active drinker2 (5,4)2 (11,8)0,244 Ex-drinker0 (0,0)1 (5,9) Never drinker35 (94,6)14 (82,4)Occupation, n (%) Worker15 (40,5)12 (70,6)0,060Height, mean (SD), meter1,6 (0,1)1,6 (0,1)0,664Weight, mean (SD), kg80,6 (17,7)65,3 (8,6)<0,001*BMI, mean (SD), kg/m231,4 (7,3)24,9 (3,2)<0,001*Obese, n (%)20 (54,1)2 (11,8)0,006*Waist circumference, mean (SD), cm97,1 (14,2)89,3 (12,8)0,058Hip circumference, mean (SD), cm108,1 (12,7)96,6 (5,1)0,001*Calf circumference, mean (SD), cm35,4 (5,1)29,6 (4,0)<0,001*Triceps skin thickness, median (min-max), mm22 (8-36)15 (6-31)0,022*Loss of muscle strength, n (%) Right10 (27,0)9 (52,9)0,076 Left12 (32,4)10 (58,8)0,081Dominant hand, right, n (%)33 (89,2)13 (76,5)0,418SMM, mean (SD)25,1 (5,8)21,9 (4,7)0,049*SMMI, mean (SD)9,6 (1,5)8,2 (1,2)<0,001*DAS 28 - CRP, median (min-max)4,4 (1,7-6,5)4,4 (2,4-6,3)0,860SDAI, median (min-max)36,1 (8,8-113)31,1 (17,1-113)0,668CDAI, median (min-max)23 (0-48)23 (6-39)0,993PrGA, median (min-max)6 (0-9)5 (2-10)0,627PtGA, median (min-max)8 (0-10)7 (4-10)0,666Presence of morning stiffness, n (%)32 (86,5)14 (82,4)0,999Swollen joint count, median (min-max)2 (0-10)4 (0-9)0,423Tender joint count, median (min-max)6 (0-20)7 (0-18)0,911

Disclosure of Interests:

None declared

AB0314 SEMAPHORIN 3A LEVELS IN LUPUS WITH AND WITHOUT SECONDARY ANTIPHOSPHOLIPID ANTIBODY SYNDROME AND RENAL INVOLVEMENT

Background:

In this study, we aimed to evaluate sema3A levels in SLE patients with and without renal involvementor secondary antiphospholipid antibody syndrome (APS), to further elucidate the contribution ofsema3A in etiopathogenesis these conditions

Objectives:

Aim of this study is to evaluate sema3A levels in systemic lupus erythematosus patients (SLE) with and without renal involvement and secondary antiphospholipid antibody syndrome (APS).

Methods:

SLE patients were grouped according to presence of secondary APS or renal involvement. The control group consisted of age-matched, non-smoker, healthy volunteers. Sema3A levels were compared among groups. All SLE patients were regrouped according to presence of thrombotic events, miscarriages and proteinuria and sema3A levels were investigated. Finally, sema3A levels of all SLE patients as a single group were compared to controls.

Results:

The mean sema3A values were 16.16±2.84 ng/dL in the control group, 11.28±5.23 ng/dL in SLE patients without nephritis and APS, 9.05±5.65 ng/dL in SLE with APS group, and 8.53±5.11 ng/dL in lupus nephritis group. When all three patient groups were examined as a single group, mean sema3A value was significantly lower than that of the control group. Sema3A was reduced in SLE patients with thromboembolism and/or miscarriage.

Conclusion:

Sema3A levels were lower in all patient groups compared to the control group. Moreover, the reduced sema3A levels in patients with a history of thromboembolism and/or miscarriage suggests that sema3A may play an important role in the pathogenesis of vasculopathy

Table 1.

Comparison of sema3A levels between SLE patient groups and control subjects

Patient groupsGroup A (N=20)Group B (N=20)Group C (N=19)Control (N=19)pSema3A, ng/dL, mean ± SD9.05 ± 5.6511.28 ± 5.238.53 ± 5.1116.16 ± 2.84Group A vscontrol<0.001Group B vscontrol<0.001Group C vscontrol<0.001Group A vs B = 0.203Group A vs C = 0.766Group B vs C = 0.106All patients (N=59)Control (N=19)<0.0019.64 ± 5.3816.16 ± 2.84Patients with thrombotic events and/or miscarriages (N=31)Patients without thrombotic events and/or miscarriages (N=48)0.0329.96 ± 5.1112.33 ± 5.84Patients with proteinuria and/or thrombotic events and/or miscarriages (N=45)Patients without proteinuria and/or thrombotic events and/or miscarriages (N=34)<0.0019.05 ± 5.0914.91± 4.50

Disclosure of Interests:

None declared

Automated and semi-automated enhancement, segmentation and tracing of cytoskeletal networks in microscopic images: A review

Cytoskeletal filaments are structures of utmost importance to biological cells and organisms due to their versatility and the significant functions they perform. These biopolymers are most often organised into network-like scaffolds with a complex morphology. Understanding the geometrical and topological organisation of these networks provides key insights into their functional roles. However, this non-trivial task requires a combination of high-resolution microscopy and sophisticated image processing/analysis software. The correct analysis of the network structure and connectivity needs precise segmentation of microscopic images. While segmentation of filament-like objects is a well-studied concept in biomedical imaging, where tracing of neurons and blood vessels is routine, there are comparatively fewer studies focusing on the segmentation of cytoskeletal filaments and networks from microscopic images. The developments in the fields of microscopy, computer vision and deep learning, however, began to facilitate the task, as reflected by an increase in the recent literature on the topic. Here, we aim to provide a short summary of the research on the (semi-)automated enhancement, segmentation and tracing methods that are particularly designed and developed for microscopic images of cytoskeletal networks. In addition to providing an overview of the conventional methods, we cover the recently introduced, deep-learning-assisted methods alongside the advantages they offer over classical methods.

A NanoFE simulation-based surrogate machine learning model to predict mechanical functionality of protein networks from live confocal imaging

Sub-cellular mechanics plays a crucial role in a variety of biological functions and dysfunctions. Due to the strong structure-function relationship in cytoskeletal protein networks, light can be shed on their mechanical functionality by investigating their structures. Here, we present a data-driven approach employing a combination of confocal live imaging of fluorescent tagged protein networks, in silico mechanical experiments and machine learning to investigate this relationship. Our designed image processing and nanoFE mechanical simulation framework resolves the structure and mechanical behaviour of cytoskeletal networks and the developed gradient boosting surrogate models linking network structure to its functionality. In this study, for the first time, we perform mechanical simulations of Filamentous Temperature Sensitive Z (FtsZ) complex protein networks with realistic network geometry depicting its skeletal functionality inside organelles (here, chloroplasts) of the moss Physcomitrella patens. Training on synthetically produced simulation data enables predicting the mechanical characteristics of FtsZ network purely based on its structural features (R2⩾0.93), therefore allowing to extract structural principles enabling specific mechanical traits of FtsZ, such as load bearing and resistance to buckling failure in case of large network deformation.

Cytological analysis and structural quantification of FtsZ1-2 and FtsZ2-1 network characteristics in Physcomitrella patens

Although the concept of the cytoskeleton as a cell-shape-determining scaffold is well established, it remains enigmatic how eukaryotic organelles adopt and maintain a specific morphology. The Filamentous Temperature Sensitive Z (FtsZ) protein family, an ancient tubulin, generates complex polymer networks, with striking similarity to the cytoskeleton, in the chloroplasts of the moss Physcomitrella patens. Certain members of this protein family are essential for structural integrity and shaping of chloroplasts, while others are not, illustrating the functional diversity within the FtsZ protein family. Here, we apply a combination of confocal laser scanning microscopy and a self-developed semi-automatic computational image analysis method for the quantitative characterisation and comparison of network morphologies and connectivity features for two selected, functionally dissimilar FtsZ isoforms, FtsZ1-2 and FtsZ2-1. We show that FtsZ1-2 and FtsZ2-1 networks are significantly different for 8 out of 25 structural descriptors. Therefore, our results demonstrate that different FtsZ isoforms are capable of generating polymer networks with distinctive morphological and connectivity features which might be linked to the functional differences between the two isoforms. To our knowledge, this is the first study to employ computational algorithms in the quantitative comparison of different classes of protein networks in living cells.

Computational 3D imaging to quantify structural components and assembly of protein networks

Traditionally, protein structures have been described by the secondary structure architecture and fold arrangement. However, the relatively novel method of 3D confocal microscopy of fluorescent-protein-tagged networks in living cells allows resolving the detailed spatial organization of these networks. This provides new possibilities to predict network functionality, as structure and function seem to be linked at various scales. Here, we propose a quantitative approach using 3D confocal microscopy image data to describe protein networks based on their nano-structural characteristics. This analysis is constructed in four steps: (i) Segmentation of the microscopic raw data into a volume model and extraction of a spatial graph representing the protein network. (ii) Quantifying protein network gross morphology using the volume model. (iii) Quantifying protein network components using the spatial graph. (iv) Linking these two scales to obtain insights into network assembly. Here, we quantitatively describe the filamentous temperature sensitive Z protein network of the moss Physcomitrella patens and elucidate relations between network size and assembly details. Future applications will link network structure and functionality by tracking dynamic structural changes over time and comparing different states or types of networks, possibly allowing more precise identification of (mal) functions or the design of protein-engineered biomaterials for applications in regenerative medicine.

STATEMENT OF SIGNIFICANCE

Protein networks are highly complex and dynamic structures that play various roles in biological environments. Analyzing the detailed spatial structure of these networks may lead to new insight into biological functions and malfunctions. Here, we propose a tool set that extracts structural information at two scales of the protein network and allows therefore to address questions such as "how is the network built?" or "how networks grow?".

Smoking and gingivitis: focus on inducible nitric oxide synthase, nitric oxide and basic fibroblast growth factor

BACKGROUND

Periodontal disease pathogenesis has been associated with smoking. Gingivitis is a mild and reversible form of periodontal disease and it tends to progress to periodontitis only in susceptible individuals. In the present study, we aimed to examine the impact of smoking on host responses in gingivitis and to evaluate and compare the inducible nitric oxide synthase (iNOS) activity in gingival tissue and NO and basic fibroblast growth factor (bFGF) levels in the gingival crevicular fluid of patients with gingivitis and healthy individuals.

MATERIAL AND METHODS

Forty-one participants were assigned to the gingivitis-smoker (n = 13), gingivitis (n = 13), healthy-smoker (n = 7) and healthy groups (n = 8). Clinical indices were recorded; gingival biopsy and gingival crevicular fluid samples were obtained from papillary regions. iNOS expression was evaluated by immunohistochemical staining. The immunoreactive cells were semiquantitatively assessed. For the quantitative determination of nitrite and nitrate in gingival crevicular fluid, the NO assay kit was used. The amount of bFGF in gingival crevicular fluid was determined by enzyme-linked immunosorbent assay.

RESULTS

The gingivitis-smoker group demonstrated a stronger iNOS expression than the non-smoker gingivitis group. iNOS expression intensity was lower in the non-smoker healthy group compared to that in healthy-smokers. No significant gingival crevicular fluid NO and bFGF level changes were observed between groups. Among patients with gingivitis, a positive correlation was detected between gingival crevicular fluid NO and bFGF levels (r = 0.806, p = 0.001).

CONCLUSIONS

Our data suggest that smoking has significant effects on iNOS expression but not on gingival crevicular fluid NO or bFGF levels in healthy and patients with gingivitis. However, our results suggest that bFGF might be involved in the regulation of NO production via iNOS.