Metabolic rewiring promotes anti-inflammatory effects of glucocorticoids.

Glucocorticoids represent the mainstay of therapy for a broad spectrum of immune-mediated inflammatory diseases. However, the molecular mechanisms underlying their anti-inflammatory mode of action have remained incompletely understood1. Here we show that the anti-inflammatory properties of glucocorticoids involve reprogramming of the mitochondrial metabolism of macrophages, resulting in increased and sustained production of the anti-inflammatory metabolite itaconate and consequent inhibition of the inflammatory response. The glucocorticoid receptor interacts with parts of the pyruvate dehydrogenase complex whereby glucocorticoids provoke an increase in activity and enable an accelerated and paradoxical flux of the tricarboxylic acid (TCA) cycle in otherwise pro-inflammatory macrophages. This glucocorticoid-mediated rewiring of mitochondrial metabolism potentiates TCA-cycle-dependent production of itaconate throughout the inflammatory response, thereby interfering with the production of pro-inflammatory cytokines. By contrast, artificial blocking of the TCA cycle or genetic deficiency in aconitate decarboxylase 1, the rate-limiting enzyme of itaconate synthesis, interferes with the anti-inflammatory effects of glucocorticoids and, accordingly, abrogates their beneficial effects during a diverse range of preclinical models of immune-mediated inflammatory diseases. Our findings provide important insights into the anti-inflammatory properties of glucocorticoids and have substantial implications for the design of new classes of anti-inflammatory drugs.

Single cell technologies for monitoring protein secretion heterogeneity.

Cell-to-cell heterogeneity presents challenges across various fields, from biomedicine to bioproduction, where precise cellular responses are vital. While single cell technologies have significantly enhanced our understanding of population heterogeneity, the predominant focus has been on monitoring intracellular compounds. Recognizing the added complexity introduced by the secretion system, in this review, we first provide a systematic overview of the distinct steps necessary for driving protein secretion. We discuss the various sources of noise acting from the synthesized preprotein to the secretory protein released based on a Gram-positive cellular system as a model. We next explore the applicability of single cell technologies for monitoring protein secretion throughout these functional stages. We also emphasize the importance of applying these single cell technologies for monitoring protein secretion during bioproduction.

Tixagevimab/cilgavimab for the prevention of COVID-19 in vaccine-refractory patients with autoimmune diseases: a prospective cohort study.

OBJECTIVES: To investigate the effects of passive immunization with the anti-SARS-CoV-2 monoclonal antibodies tixagevimab/cilgavimab on humoral responses and on COVID-19 outcomes in vaccine-refractory patients with immune-mediated inflammatory diseases (IMID) at high risk of severe COVID-19. METHODS: A prospective cohort study was performed on a cohort of high-risk vaccine-refractory IMID patients treated with a single dose of tixagevimab/cilgavimab (150 mg/150 mg). COVID-19 outcomes as well as serum and salivary anti-SARS-CoV-2 IgG were assessed at baseline and for at least 6 months. Results were compared with an untreated high-risk vaccine-refractory IMID population. Standardised incidence ratios (SIR) of COVID-19 compared with the general population were calculated for both groups. RESULTS: 38 high-risk IMID patients received tixagevimab/cilgavimab and were compared with 114 untreated high-risk IMID controls. Serum anti-Spike IgG increased to 6.6 OD (SD: ±0.8) at day one and remained positive up to month 6 (6.3 ± 1.4 OD). Salivary anti-Spike IgG peaked at month 2 (1.6 ± 1.1 OD)) and decreased from month 3 (0.8 ± 0.3 OD)). No severe or extended infection was observed in the tixagevimab/cilgavimab group. Compared with the general population, the SIR of COVID-19 in treated patients was 0.76 (95% CI: 0.24-1.58) despite the increased risk profile. The SIR of the control group was 1.51 (1.07-2.02), corresponding to a significantly increased incidence. CONCLUSIONS: Passive immunization with tixagevimab/cilgavimab is safe and effective in inducing anti-SARS-CoV-2 immunity and potentially in preventing COVID-19 in high-risk vaccine-refractory IMID patients. These data provide a proof of concept for the use of monoclonal antibodies as a preventative strategy against SARS-CoV-2 in vulnerable populations.

Physical Function of RA patients Tapering Treatment-A Post Hoc Analysis of the Randomized Controlled RETRO Trial.

Several studies have shown that tapering or stopping disease-modifying anti-rheumatic drugs (DMARDs) in rheumatoid arthritis (RA) patients in sustained remission is feasible. However, tapering/stopping bears the risk of decline in physical function as some patients may relapse and face increased disease activity. Here, we analyzed the impact of tapering or stopping DMARD treatment on the physical function of RA patients. The study was a post hoc analysis of physical functional worsening for 282 patients with RA in sustained remission tapering and stopping DMARD treatment in the prospective randomized RETRO study. HAQ and DAS-28 scores were determined in baseline samples of patients continuing DMARD (arm 1), tapering their dose by 50% (arm 2), or stopping after tapering (arm 3). Patients were followed over 1 year, and HAQ and DAS-28 scores were evaluated every 3 months. The effect of treatment reduction strategy on functional worsening was assessed in a recurrent-event Cox regression model with a study-group (control, taper, and taper/stop) as the predictor. Two-hundred and eighty-two patients were analyzed. In 58 patients, functional worsening was observed. The incidences suggest a higher probability of functional worsening in patients tapering and/or stopping DMARDs, which is likely due to higher relapse rates in these individuals. At the end of the study, however, functional worsening was similar among the groups. Point estimates and survival curves show that the decline in functionality according to HAQ after tapering or discontinuation of DMARDs in RA patients with stable remission is associated with recurrence, but not with an overall functional decline.

Precise and versatile microplate reader-based analyses of biosensor signals from arrayed microbial colonies.

Genetically encoded fluorescent biosensors have emerged as a powerful tool to support phenotypic screenings of microbes. Optical analyses of fluorescent sensor signals from colonies grown on solid media can be challenging as imaging devices need to be equipped with appropriate filters matching the properties of fluorescent biosensors. Toward versatile fluorescence analyses of different types of biosensor signals derived from arrayed colonies, we investigate here the use of monochromator equipped microplate readers as an alternative to imaging approaches. Indeed, for analyses of the LacI-controlled expression of the reporter mCherry in Corynebacterium glutamicum, or promoter activity using GFP as reporter in Saccharomyces cerevisiae, an improved sensitivity and dynamic range was observed for a microplate reader-based analyses compared to their analyses via imaging. The microplate reader allowed us to capture signals of ratiometric fluorescent reporter proteins (FRPs) with a high sensitivity and thereby to further improve the analysis of internal pH via the pH-sensitive FRP mCherryEA in Escherichia coli colonies. Applicability of this novel technique was further demonstrated by assessing redox states in C. glutamicum colonies using the FRP Mrx1-roGFP2. By the use of a microplate reader, oxidative redox shifts were measured in a mutant strain lacking the non-enzymatic antioxidant mycothiol (MSH), indicating its major role for maintaining a reduced redox state also in colonies on agar plates. Taken together, analyses of biosensor signals from microbial colonies using a microplate reader allows comprehensive phenotypic screenings and thus facilitates further development of new strains for metabolic engineering and systems biology.

An AI-Powered Clinical Decision Support System to Predict Flares in Rheumatoid Arthritis: A Pilot Study.

Treat-to-target (T2T) is a main therapeutic strategy in rheumatology; however, patients and rheumatologists currently have little support in making the best treatment decision. Clinical decision support systems (CDSSs) could offer this support. The aim of this study was to investigate the accuracy, effectiveness, usability, and acceptance of such a CDSS-Rheuma Care Manager (RCM)-including an artificial intelligence (AI)-powered flare risk prediction tool to support the management of rheumatoid arthritis (RA). Longitudinal clinical routine data of RA patients were used to develop and test the RCM. Based on ten real-world patient vignettes, five physicians were asked to assess patients' flare risk, provide a treatment decision, and assess their decision confidence without and with access to the RCM for predicting flare risk. RCM usability and acceptance were assessed using the system usability scale (SUS) and net promoter score (NPS). The flare prediction tool reached a sensitivity of 72%, a specificity of 76%, and an AUROC of 0.80. Perceived flare risk and treatment decisions varied largely between physicians. Having access to the flare risk prediction feature numerically increased decision confidence (3.5/5 to 3.7/5), reduced deviations between physicians and the prediction tool (20% to 12% for half dosage flare prediction), and resulted in more treatment reductions (42% to 50% vs. 20%). RCM usability (SUS) was rated as good (82/100) and was well accepted (mean NPS score 7/10). CDSS usage could support physicians by decreasing assessment deviations and increasing treatment decision confidence.

Antibodies against citrullinated proteins of IgA isotype are associated with progression to rheumatoid arthritis in individuals at-risk.

OBJECTIVE: Events triggering disease outbreak in individuals at-risk for rheumatoid arthritis (RA at-risk) remain unclear, and the role of the various anticitrullinated protein antibody (ACPA) isotypes in this process is still to be established. We aimed to investigate the prevalence of IgA ACPA in RA at-risk individuals, their role in the transition from the RA at-risk status to RA and their dynamics during this transition. METHODS: Cross-sectional measurement of serum IgA1 and IgA2 ACPA levels was conducted in healthy controls, RA at-risk individuals and patients with RA and compared with the frequency of RA development in at risk individuals during a follow-up of 14 months. In addition, longitudinal measurements of serum IgA1 and IgA2 ACPA levels prior to, at and after the onset of RA were performed. RESULTS: Approximately two-thirds of RA at-risk individuals were positive for serum IgA1 and IgA2 ACPA in levels comparable to IgG ACPA positive patients with RA. IgA1, but not IgA2 ACPA positivity was associated with the transition from the RA at-risk state to RA within the following 14 months. Interestingly, during this transition process, IgA1 ACPA levels declined at RA onset and also thereafter during the early phase of RA. This decline was confirmed in a second, independent cohort. CONCLUSION: Both IgA1 and IgA2 ACPA are present in RA at-risk individuals, but only IgA1 ACPA are associated with the progression to RA. The observed decline in serum IgA1 ACPA levels before the onset of RA might indicate starting barrier leakiness prior to disease outbreak.

Non-invasive metabolic profiling of inflammation in joints and entheses by multispectral optoacoustic tomography.

OBJECTIVE: To explore the metabolic characteristics of arthritis and enthesitis using multispectral opto-acoustic tomography (MSOT), a technology using near-infrared multispectral laser to stimulate tissues and detect the emitted acoustic energy, enabling non-invasive quantification of tissue components in vivo based on differential absorbance at multiple wavelengths. METHODS: We performed a cross-sectional study in patients with RA or PsA and healthy controls (HCs). Participants underwent clinical, ultrasonographic and MSOT examination of MCP and wrist joints as well as the entheses of the common extensor tendon at the lateral humeral epicondyles and of the patellar, quadriceps and Achilles tendon. MSOT-measured haemoglobin (Hb), oxygen saturation, collagen and lipid levels were quantified and scaled mean differences between affected and unaffected joints and entheses were calculated as defined by clinical examination or ultrasonography using linear mixed effects models. RESULTS: We obtained 1535 MSOT and 982 ultrasonography scans from 87 participants (34 PsA, 17 RA, 36 HCs). Entheseal tenderness was not associated with significant metabolic changes, whereas enthesitis-related sonographic changes were associated with increased total Hb, oxygen saturation and collagen content. In contrast, the presence of arthritis-related clinical and sonographic findings showed increased Hb levels, reduced oxygen saturation and reduced collagen content. Synovial hypertrophy was associated with increased lipid content in the joints. CONCLUSION: MSOT allows determination of distinct metabolic differences between arthritis and enthesitis in a non-invasive setting in humans in vivo.

Efficacy and drug persistence of baricitinib monotherapy is similar to combination therapy in patients with active RA: a prospective observational study.

BACKGROUND: Baricitinib (BARI) is approved for the treatment of rheumatoid arthritis (RA) after failure of conventional synthetic and biologic disease modifying anti-rheumatic drugs (cs/bDMARDs) in combination with methotrexate (MTX) or as monotherapy. However, real-world data are scarce regarding efficacy and drug persistence for BARI monotherapy (BARI-mono) versus its combination with MTX (BARI-combo). OBJECTIVE: To evaluate efficacy and drug persistence of BARImono compared with BARI-combo in routine clinical practice METHODS: Patients with RA who were switched to BARI were included in a prospective, monocentric cohort. Demographics, clinical outcomes, adverse events and medication were prospectively recorded every 3 months. Clinical efficacy was measured by DAS-28 ESR while drug persistence was measured as the time on drug. We estimated least-square mean DAS-28 scores over time using linear mixed effects models including time-group interactions. Kaplan-Meier method was used to estimate BARI survival and probability of remission over time. RESULTS: 139 patients (98 women; aged 58.4 (12.8) years; mean disease duration of 9.7 years) were included between 2017 and 2021. 46 patients received BARI-combo, 93 patients received BARI-mono. Mean DAS-28 ESR were not significantly but only numerically different between both groups at baseline and multiple timepoints over follow-up. DAS-28 ESR remission was attained at least once upto 48 weeks in 62% and 51% patients in BARI-combo versus BARI-mono group (log-rank p=0.64). Drug persistence was high (69 vs 67% at 48 weeks and 62% vs 56% at 96 weeks) and similar in BARI-combo-treated and BARI-mono-treated patients. b/ts DMARD naïve patients had lower mean DAS-28 scores over the follow-up and attained DAS-28 ESR remission earlier than patients with inadequate response to b/ts DMARDs (p=0.11). BARI was discontinued in 11/139 patients (7.9%) due to adverse effects. CONCLUSION: In routine practice, BARI is effective as monotherapy in case of MTX intolerance with overall high drug persistence rates. No new safety signals were observed.

Intensity and longevity of SARS-CoV-2 vaccination response in patients with immune-mediated inflammatory disease: a prospective cohort study.

Background: Concerns have been raised about the reduced immunogenicity of vaccines against SARS-CoV-2 in patients with immune-mediated inflammatory diseases and the higher risk of breakthrough infections. The objective of our study was to investigate the intensity and longevity of SARS-CoV-2 vaccination responses in patients with immune-mediated inflammatory diseases, and to assess the effects of diagnosis, treatment, and adapted vaccination schedules. Methods: SARS-CoV-2 IgG antibody response after SARS-CoV-2 vaccination was measured over time in a large prospective cohort of healthy controls and participants with immune-mediated inflammatory diseases (attending or admitted to affiliated centres) between Dec 15, 2020, and Dec 1, 2021. Cohort participants with immune-mediated inflammatory diseases and control participants with no diagnosis of immune-mediated inflammatory diseases, were eligible for this analysis. Demographic data and disease-specific data were collected using a questionnaire. Humoral response was compared across treatment and disease groups, and with respect to the receipt of additional vaccinations. SARS-CoV-2 antibody response was measured by ELISA using optical density ratio units and modelled over time with age and sex adjustment using mixed-effects models. Using these models, marginal mean antibody titres and marginal risks of a poor response (optical density ratio <1·1) were calculated for each week starting from week 8 after the first vaccination to week 40. Findings: Among 5076 individuals registered, 2535 participants with immune-mediated inflammatory diseases (mean age 55·0 [15·2] years; 1494 [58·9%] women and 1041 [41·1%] men) and 1198 healthy controls (mean age 40·7 [13·5] years; 554 [46·2%] women and 644 [53·8%] men) were included in this analysis. Mean antibody titres were higher in healthy controls compared with people with immune-mediated inflammatory diseases at all timepoints, with a peak antibody response in healthy controls (mean optical density ratio 12·48; 95% CI 11·50-13·53) of more than twice that in participants with immune-mediated inflammatory diseases (5·50; 5·23-5·77; mean difference 6·98; 5·92-8·04). A poor response to vaccination was observed in participants with immune-mediated inflammatory diseases who were taking B-cell inhibitors (peak mean difference from healthy controls 11·68; 10·07-13·29) and T-cell inhibitors (peakmean difference from healthy controls 10·43; 8·33-12·53). Mean differences in antibody responses between different immune-mediated inflammatory diseases were small. Participants with immune-mediated inflammatory diseases who were given a third vaccine dose had higher mean antibody titres than did healthy controls vaccinated with two vaccine doses at 40 weeks after the initial vaccination (mean difference 1·34; 0·01-2·69). Interpretation: People with immune-mediated inflammatory diseases show a lower and less durable SARS-CoV-2 vaccination response and are at risk of losing humoral immune protection. Adjusted vaccination schedules with earlier booster doses or more frequent re-doses, or both, could better protect people with immune-mediated inflammatory diseases. Funding: Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, European Research Council, Innovative Medicine Initiative, Friedrich-Alexander-Universität Erlangen-Nürnberg, Else Kröner-Memorial Foundation.

Single-Photon Counting with Semiconductor Resonant Tunneling Devices.

Optical quantum information science and technologies require the capability to generate, control, and detect single or multiple quanta of light. The need to detect individual photons has motivated the development of a variety of novel and refined single-photon detectors (SPDs) with enhanced detector performance. Superconducting nanowire single-photon detectors (SNSPDs) and single-photon avalanche diodes (SPADs) are the top-performer in this field, but alternative promising and innovative devices are emerging. In this review article, we discuss the current state-of-the-art of one such alternative device capable of single-photon counting: the resonant tunneling diode (RTD) single-photon detector. Due to their peculiar photodetection mechanism and current-voltage characteristic with a region of negative differential conductance, RTD single-photon detectors provide, theoretically, several advantages over conventional SPDs, such as an inherently deadtime-free photon-number resolution at elevated temperatures, while offering low dark counts, a low timing jitter, and multiple photon detection modes. This review article brings together our previous studies and current experimental results. We focus on the current limitations of RTD-SPDs and provide detailed design and parameter variations to be potentially employed in next-generation RTD-SPD to improve the figure of merits of these alternative single-photon counting devices. The single-photon detection capability of RTDs without quantum dots is shown.

Digital models in biotechnology: Towards multi-scale integration and implementation.

Industrial biotechnology encompasses a large area of multi-scale and multi-disciplinary research activities. With the recent megatrend of digitalization sweeping across all industries, there is an increased focus in the biotechnology industry on developing, integrating and applying digital models to improve all aspects of industrial biotechnology. Given the rapid development of this field, we systematically classify the state-of-art modelling concepts applied at different scales in industrial biotechnology and critically discuss their current usage, advantages and limitations. Further, we critically analyzed current strategies to couple cell models with computational fluid dynamics to study the performance of industrial microorganisms in large-scale bioprocesses, which is of crucial importance for the bio-based production industries. One of the most challenging aspects in this context is gathering intracellular data under industrially relevant conditions. Towards comprehensive models, we discuss how different scale-down concepts combined with appropriate analytical tools can capture intracellular states of single cells. We finally illustrated how the efforts could be used to develop digitals models suitable for both cell factory design and process optimization at industrial scales in the future.

Visualizing the pH in Escherichia coli Colonies via the Sensor Protein mCherryEA Allows High-Throughput Screening of Mutant Libraries.

Cytoplasmic pH in bacteria is tightly regulated by diverse active mechanisms and interconnected regulatory processes. Many processes and regulators underlying pH homeostasis have been identified via phenotypic screening of strain libraries for nongrowth at low or high pH values. Direct screens with respect to changes of the internal pH in mutant strain collections are limited by laborious methods, which include fluorescent dyes and radioactive probes. Genetically encoded biosensors equip single organisms or strain libraries with an internal sensor molecule during the generation of the strain. Here, we used the pH-sensitive mCherry variant mCherryEA as a ratiometric pH biosensor. We visualized the internal pH of Escherichia coli colonies on agar plates by the use of a GelDoc imaging system. Combining this imaging technology with robot-assisted colony picking and spotting allowed us to screen and select mutants with altered internal pH values from a small transposon mutagenesis-derived E. coli library. Identification of the transposon (Tn) insertion sites in strains with altered internal pH levels revealed that the transposon was inserted into trkH (encoding a transmembrane protein of the potassium uptake system) or rssB (encoding the adaptor protein RssB, which mediates the proteolytic degradation of the general stress response regulator RpoS), two genes known to be associated with pH homeostasis and pH stress adaptation. This successful screening approach demonstrates that the pH sensor-based analysis of arrayed colonies on agar plates is a sensitive approach for the rapid identification of genes involved in pH homeostasis or pH stress adaptation in E. coli. IMPORTANCE Phenotypic screening of strain libraries on agar plates has become a versatile tool to understand gene functions and to optimize biotechnological platform organisms. Screening is supported by genetically encoded biosensors that allow to easily measure intracellular processes. For this purpose, transcription factor-based biosensors have emerged as the sensor type of choice. Here, the target stimulus initiates the activation of a response gene (e.g., a fluorescent protein), followed by transcription, translation, and maturation. Due to this mechanistic principle, biosensor readouts are delayed and cannot report the actual intracellular state of the cell in real time. To capture rapid intracellular processes adequately, fluorescent reporter proteins are extensively applied. However, these sensor types have not previously been used for phenotypic screenings. To take advantage of their properties, we established here an imaging method that allows application of a rapid ratiometric sensor protein for assessing the internal pH of colonies in a high-throughput manner.

Resonant Tunneling Diodes: Mid-Infrared Sensing at Room Temperature.

Resonant tunneling diode photodetectors appear to be promising architectures with a simple design for mid-infrared sensing operations at room temperature. We fabricated resonant tunneling devices with GaInAsSb absorbers that allow operation in the 2-4 µm range with significant electrical responsivity of 0.97 A/W at 2004 nm to optical readout. This paper characterizes the photosensor response contrasting different operational regimes and offering a comprehensive theoretical analysis of the main physical ingredients that rule the sensor functionalities and affect its performance. We demonstrate how the drift, accumulation, and escape efficiencies of photogenerated carriers influence the electrostatic modulation of the sensor's electrical response and how they allow controlling the device's sensing abilities.

Characterization of Serum and Mucosal SARS-CoV-2-Antibodies in HIV-1-Infected Subjects after BNT162b2 mRNA Vaccination or SARS-CoV-2 Infection.

Only limited data are available regarding the immunogenicity of the BNT162b2 mRNA vaccine in HIV-1+ patients. Therefore, we investigated the humoral immune response after BNT162b2-mRNA vaccination or SARS-CoV-2 infection in HIV-1+ patients on antiretroviral therapy compared to HIV-1-uninfected subjects. Serum and saliva samples were analysed by SARS-CoV-2 spike-specific IgG and IgA ELISAs and a surrogate neutralization assay. While all subjects developed anti-spike IgG and IgA and neutralizing antibodies in serum after two doses of BNT162b2 mRNA vaccine, the HIV-1+ subjects displayed significantly lower neutralizing capacity and anti-spike IgA in serum compared to HIV-1-uninfected subjects. Serum levels of anti-spike IgG and neutralizing activity were significantly higher in vaccinees compared to SARS-CoV-2 convalescents irrespective of HIV-1 status. Among SARS-CoV-2 convalescents, there was no significant difference in spike-specific antibody response between HIV-1+ and uninfected subjects. In saliva, anti-spike IgG and IgA antibodies were detected both in vaccinees and convalescents, albeit at lower frequencies compared to the serum and only rarely with detectable neutralizing activity. In summary, our study demonstrates that the BNT162b2 mRNA vaccine induces SARS-CoV-2-specific antibodies in HIV-1-infected patients on antiretroviral therapy, however, lower vaccine induced neutralization activity indicates a lower functionality of the humoral vaccine response in HIV-1+ patients.

Impact of Cytokine Inhibitor Therapy on the Prevalence, Seroconversion Rate, and Longevity of the Humoral Immune Response Against SARS-CoV-2 in an Unvaccinated Cohort.

OBJECTIVE: To investigate the impact of biologic disease-modifying antirheumatic drug (bDMARD) treatment on the prevalence, seroconversion rate, and longevity of the humoral immune response against SARS-CoV-2 in patients with immune-mediated inflammatory diseases (IMIDs). METHODS: Anti-SARS-CoV-2 IgG antibodies were measured in a prospective cohort of health care professional controls and non-health care controls and IMID patients receiving no treatment or receiving treatment with conventional or biologic DMARDs during the first and second COVID-19 waves. Regression models adjusting for age, sex, sampling time, and exposure risk behavior were used to calculate relative risks (RRs) of seropositivity. Seroconversion rates were assessed in participants with polymerase chain reaction (PCR)-positive SARS-CoV-2 infection. Antibody response longevity was evaluated by reassessing participants who tested positive during the first wave. RESULTS: In this study, 4,508 participants (2,869 IMID patients and 1,639 controls) were analyzed. The unadjusted RR (0.44 [95% confidence interval (95% CI) 0.31-0.62]) and adjusted RR (0.50 [95% CI 0.34-0.73]) for SARS-CoV-2 IgG antibodies were significantly lower in IMID patients treated with bDMARDs compared to non-health care controls (P < 0.001), primarily driven by treatment with tumor necrosis factor inhibitors, interleukin-17 (IL-17) inhibitors, and IL-23 inhibitors. Adjusted RRs for untreated IMID patients (1.12 [95% CI 0.75-1.67]) and IMID patients receiving conventional synthetic DMARDs (0.70 [95% CI 0.45-1.08]) were not significantly different from non-health care controls. Lack of seroconversion in PCR-positive participants was more common among bDMARD-treated patients (38.7%) than in non-health care controls (16%). Overall, 44% of positive participants lost SARS-CoV-2 antibodies by follow-up, with higher rates in IMID patients treated with bDMARDs (RR 2.86 [95% CI 1.43-5.74]). CONCLUSION: IMID patients treated with bDMARDs have a lower prevalence of SARS-CoV-2 antibodies, seroconvert less frequently after SARS-CoV-2 infection, and may exhibit a reduced longevity of their humoral immune response.

Impedance flow cytometry for viability analysis of Corynebacterium glutamicum.

Corynebacterium glutamicum efficiently produces glutamate when growth is inhibited. Analyses of viability in this non-growing state requires time consuming plating and determination of colony forming units. We here establish impedance flow cytometry measurements to assess the viability of non-growing, glutamate producing C. glutamicum cultures within minutes.

A Virtual Reality-Based App to Educate Health Care Professionals and Medical Students About Inflammatory Arthritis: Feasibility Study.

BACKGROUND: Inflammatory arthritides (IA) such as rheumatoid arthritis or psoriatic arthritis are disorders that can be difficult to comprehend for health professionals and students in terms of the heterogeneity of clinical symptoms and pathologies. New didactic approaches using innovative technologies such as virtual reality (VR) apps could be helpful to demonstrate disease manifestations as well as joint pathologies in a more comprehensive manner. However, the potential of using a VR education concept in IA has not yet been evaluated. OBJECTIVE: We evaluated the feasibility of a VR app to educate health care professionals and medical students about IA. METHODS: We developed a VR app using data from IA patients as well as 2D and 3D-visualized pathological joints from X-ray and computed tomography-generated images. This VR app (Rheumality) allows the user to interact with representative arthritic joint and bone pathologies of patients with IA. In a consensus meeting, an online questionnaire was designed to collect basic demographic data (age, sex); profession of the participants; and their feedback on the general impression, knowledge gain, and potential areas of application of the VR app. The VR app was subsequently tested and evaluated by health care professionals (physicians, researchers, and other professionals) and medical students at predefined events (two annual rheumatology conferences and academic teaching seminars at two sites in Germany). To explore associations between categorical variables, the χ2 or Fisher test was used as appropriate. Two-sided P values ≤.05 were regarded as significant. RESULTS: A total of 125 individuals participated in this study. Among them, 56% of the participants identified as female, 43% identified as male, and 1% identified as nonbinary; 59% of the participants were 18-30 years of age, 18% were 31-40 years old, 10% were 41-50 years old, 8% were 51-60 years old, and 5% were 61-70 years old. The participants (N=125) rated the VR app as excellent, with a mean rating of 9.0 (SD 1.2) out of 10, and many participants would recommend use of the app, with a mean recommendation score of 3.2 (SD 1.1) out of 4. A large majority (120/125, 96.0%) stated that the presentation of pathological bone formation improves understanding of the disease. We did not find any association between participant characteristics and evaluation of the VR experience or recommendation scores. CONCLUSIONS: The data show that IA-targeting innovative teaching approaches based on VR technology are feasible.

Advanced machine learning for predicting individual risk of flares in rheumatoid arthritis patients tapering biologic drugs.

BACKGROUND: Biological disease-modifying anti-rheumatic drugs (bDMARDs) can be tapered in some rheumatoid arthritis (RA) patients in sustained remission. The purpose of this study was to assess the feasibility of building a model to estimate the individual flare probability in RA patients tapering bDMARDs using machine learning methods. METHODS: Longitudinal clinical data of RA patients on bDMARDs from a randomized controlled trial of treatment withdrawal (RETRO) were used to build a predictive model to estimate the probability of a flare. Four basic machine learning models were trained, and their predictions were additionally combined to train an ensemble learning method, a stacking meta-classifier model to predict the individual flare probability within 14 weeks after each visit. Prediction performance was estimated using nested cross-validation as the area under the receiver operating curve (AUROC). Predictor importance was estimated using the permutation importance approach. RESULTS: Data of 135 visits from 41 patients were included. A model selection approach based on nested cross-validation was implemented to find the most suitable modeling formalism for the flare prediction task as well as the optimal model hyper-parameters. Moreover, an approach based on stacking different classifiers was successfully applied to create a powerful and flexible prediction model with the final measured AUROC of 0.81 (95%CI 0.73-0.89). The percent dose change of bDMARDs, clinical disease activity (DAS-28 ESR), disease duration, and inflammatory markers were the most important predictors of a flare. CONCLUSION: Machine learning methods were deemed feasible to predict flares after tapering bDMARDs in RA patients in sustained remission.