Thinking about default enrollment lowers vaccination intentions and public support in G7 countries.

Policymakers often face a conundrum between being transparent about policies and ensuring that those policies are effective. This challenge is particularly relevant for behavioral nudges, which are not usually disclosed. Rather than avoiding transparency, we suggest that policymakers encourage citizens to reflect on nudges to help them understand their own views and align those views with their behaviors. Using data from an online survey experiment with 24,303 respondents in G7 countries, we examine the impact of reflection on a hypothetical default nudge policy for COVID-19 booster appointments. Contrary to expectations, participants say they would be less likely to get the booster when automatically enrolled compared with a control condition. Similarly, encouraging citizens to think about the status quo (baseline) policy also reduces intentions for boosters. These interventions have no effect on approval of the policy. Further, encouraging people to think about automatic enrollment decreases approval of the policy and further decreases their intentions to get vaccinated. These findings suggest that reflection on a nudge can increase backlash from a nudge and also elicit policy disapproval, thereby aligning policy support with behavioral intentions.

Expression of Chondrogenic Potential Markers in Cultured Chondrocytes from the Human Knee Joint.

OBJECTIVES: While substantial progress has been made in engineering cartilaginous constructs for animal models, further research is needed to translate these methodologies for human applications. Evidence suggests that cultured autologous chondrocytes undergo changes in phenotype and gene expression, thereby affecting their proliferation and differentiation capacity. This study was designed to evaluate the expression of chondrogenic markers in cultured human articular chondrocytes from passages 3 (P3) and 7 (P7), beyond the current clinical recommendation of P3. METHODS: Cultured autologous chondrocytes were passaged from P3 up to P7, and quantitative polymerase chain reaction (qPCR) was used to assess mRNA expression of chondrogenic markers, including collagen type I (COLI), collagen type II (COLII), aggrecan (AGG), bone morphogenetic protein 4 (BMP4), transcription factor SOX-9 (SOX9), proteoglycan 4 (PGR4), and transformation-related protein 53 (p53), between P3 and P7. RESULTS: Except for AGG, no significant differences were found in the expression of markers between passages, suggesting the maintenance of chondrogenic potential in cultured chondrocytes. Differential expression identified between SOX9 and PGR4, as well as between COLI and SOX9, indicates that differences in chondrogenic markers are present between age groups and sexes, respectively. CONCLUSIONS: Overall, expression profiles of younger and male chondrocytes exhibit conversion of mature cartilage characteristics compared to their counterparts, with signs of dedifferentiation and loss of phenotype within-group passaging. These results may have implications in guiding the use of higher passaged chondrocytes for engineering constructs and provide a foundation for clinical recommendations surrounding the repair and treatment of articular cartilage pathology in both sexes.

Enhancing skin lesion classification with advanced deep learning ensemble models: a path towards accurate medical diagnostics.

Skin cancer, including the highly lethal malignant melanoma, poses a significant global health challenge with a rising incidence rate. Early detection plays a pivotal role in improving survival rates. This study aims to develop an advanced deep learning-based approach for accurate skin lesion classification, addressing challenges such as limited data availability, class imbalance, and noise. Modern deep neural network designs, such as ResNeXt101, SeResNeXt101, ResNet152V2, DenseNet201, GoogLeNet, and Xception, which are used in the study and ze optimised using the SGD technique. The dataset comprises diverse skin lesion images from the HAM10000 and ISIC datasets. Noise and artifacts are tackled using image inpainting, and data augmentation techniques enhance training sample diversity. The ensemble technique is utilized, creating both average and weighted average ensemble models. Grid search optimizes model weight distribution. The individual models exhibit varying performance, with metrics including recall, precision, F1 score, and MCC. The "Average ensemble model" achieves harmonious balance, emphasizing precision, F1 score, and recall, yielding high performance. The "Weighted ensemble model" capitalizes on individual models' strengths, showcasing heightened precision and MCC, yielding outstanding performance. The ensemble models consistently outperform individual models, with the average ensemble model attaining a macro-average ROC-AUC score of 96 % and the weighted ensemble model achieving a macro-average ROC-AUC score of 97 %. This research demonstrates the efficacy of ensemble techniques in significantly improving skin lesion classification accuracy. By harnessing the strengths of individual models and addressing their limitations, the ensemble models exhibit robust and reliable performance across various metrics. The findings underscore the potential of ensemble techniques in enhancing medical diagnostics and contributing to improved patient outcomes in skin lesion diagnosis.

Locality is the strongest predictor of expert performance in image-based differentiation of bacterial and fungal corneal ulcers from India.

PURPOSE: This study sought to identify the sources of differential performance and misclassification error among local (Indian) and external (non-Indian) corneal specialists in identifying bacterial and fungal keratitis based on corneal photography. METHODS: This study is a secondary analysis of survey data assessing the ability of corneal specialists to identify acute bacterial versus fungal keratitis by using corneal photography. One-hundred images of 100 eyes from 100 patients with acute bacterial or fungal keratitis in South India were previously presented to an international cohort of cornea specialists for interpretation over the span of April to July 2021. Each expert provided a predicted probability that the ulcer was either bacterial or fungal. Using these data, we performed multivariable linear regression to identify factors predictive of expert performance, accounting for primary practice location and surrogate measures to infer local fungal ulcer prevalence, including locality, latitude, and dew point. In addition, Brier score decomposition was used to determine experts' reliability ("calibration") and resolution ("boldness") and were compared between local (Indian) and external (non-Indian) experts. RESULTS: Sixty-six experts from 16 countries participated. Indian practice location was the only independently significant predictor of performance in multivariable linear regression. Resolution among Indian experts was significantly better (0.08) than among non-Indian experts (0.01; P < 0.001), indicating greater confidence in their predictions. There was no significant difference in reliability between the two groups ( P = 0.40). CONCLUSION: Local cornea experts outperformed their international counterparts independent of regional variability in tropical risk factors for fungal keratitis. This may be explained by regional characteristics of infectious ulcers with which local corneal specialists are familiar.

Planar Polymer Membranes Accommodate Functional Self-Assembly of Inserted Resorcinarene Nanocapsules.

Solid-supported polymer membranes (SSPMs) offer great potential in material and life sciences due to their increased mechanical stability and robustness compared to solid-supported lipid membranes. However, there is still a need for expanding the functionality of SSPMs by combining them with synthetic molecular assemblies. In this study, SSPMs served as a flexible matrix for the insertion of resorcinarene monomers and their self-assembly into functional hexameric resorcinarene capsules. Resorcinarene capsules provide a large cavity with affinity specifically for cationic and polyhydroxylated molecules. While the capsules are stable in apolar organic solvents, they disassemble when placed in polar solvents, which limits their application. Here, a solvent-assisted approach was used for copolymer membrane deposition on solid support and simultaneous insertion of the resorcinarene monomers. By investigation of the molecular factors and conditions supporting the codeposition of the copolymer and resorcinarene monomers, a stable hybrid membrane was formed. The hydrophobic domain of the membrane played a crucial role by providing a sufficiently thick and apolar layer, allowing for the self-assembly of the capsules. The capsules were functional inside the membranes by encapsulating cationic guests from the aqueous environment. The amount of resorcinarene capsules in the hybrid membranes was quantified by a combination of quartz-crystal microbalance with dissipation and liquid chromatography-mass spectrometry, while the membrane topography and layer composition were analyzed by atomic force microscopy and neutron reflectometry. Functional resorcinarene capsules inside SSPMs can serve as dynamic sensors and potentially as cross-membrane transporters, thus holding great promise for the development of smart surfaces.

Implementation of optical coherence tomography in retinopathy of prematurity screening.

PURPOSE OF REVIEW: In this review, we explore the investigational applications of optical coherence tomography (OCT) in retinopathy of prematurity (ROP), the insights they have delivered thus far, and key milestones for its integration into the standard of care. RECENT FINDINGS: While OCT has been widely integrated into clinical management of common retinal diseases, its use in pediatric contexts has been undermined by limitations in ergonomics, image acquisition time, and field of view. Recently, investigational handheld OCT devices have been reported with advancements including ultra-widefield view, noncontact use, and high-speed image capture permitting real-time en face visualization. These developments are compelling for OCT as a more objective alternative with reduced neonatal stress compared to indirect ophthalmoscopy and/or fundus photography as a means of classifying and monitoring ROP. SUMMARY: OCT may become a viable modality in management of ROP. Ongoing innovation surrounding handheld devices should aim to optimize patient comfort and image resolution in the retinal periphery. Future clinical investigations may seek to objectively characterize features of peripheral stage and explore novel biomarkers of disease activity.

Anaemia in the first trimester and poor physiological plasma expansion during pregnancy negatively impact foetal weight and newborn anthropometrics: An observational cohort study in Tanzania.

OBJECTIVES: Anaemia during pregnancy is a major health challenge affecting pregnancy outcome worldwide. The objectives of this study were to investigate the impact of severe-moderate anaemia in the first trimester, as well as changes in haemoglobin during pregnancy among non-anaemic women, on foetal weight, placental blood flow and newborn anthropometrics. METHODS: In a prospective cohort study, 346 women residing in rural Tanzania were followed throughout pregnancy with serial ultrasound and newborn anthropometrics assessed within 24 h of delivery. Associations between placental blood flow, foetal weight and newborn anthropometrics with either first trimester severe-moderate anaemia (haemoglobin≤9.5 g/dL) or changes in haemoglobin from the first to the third trimester among non-anaemic women, were assessed by mixed model regression and multiple linear regression, adjusting for maternal and foetal co-variables. Foetal weights and birthweight were converted to z-scores using a population based sex-specific weight reference. RESULTS: Severe-moderate anaemia in the first trimester was associated with significantly reduced foetal weight z-scores (adjusted mean difference (aMD) -0.44 (95% CI -0.81, -0.07)) and newborn anthropometric indices (birth weight z-score aMD -0.55 (-0.9, -0.13), abdominal circumference aMD -11 mm (95% CI -20, -3)). There were no association between first trimester severe-moderate anaemia and placental blood flow. Among women who were non-anaemic in the first trimester, women with the least reduction in haemoglobin (Δ ≥ -0.3 g/dL) delivered significantly smaller newborns (birthweight z-score aMD -0.55 (-0.91, -0.20), abdominal circumference aMD -10 mm (95% CI -17, -3), compared to women with the greatest reduction (Δ haemoglobin ≤ -1.4 g/dL)). CONCLUSIONS: Severe-moderate anaemia in early pregnancy was associated with smaller newborn anthropometrics which was reflected in smaller mean foetal weights in the second and third trimester. Furthermore, among women who were non-anaemic in the first trimester, there was an association between smaller newborn anthropometrics and limited haemoglobin decrease during pregnancy, possibly reflecting insufficient plasma expansion.

Uncovering mechanisms of interorganelle lipid transport by enzymatic mass tagging.

Lipid trafficking is critical for the biogenesis and expansion of organelle membranes. Lipid transport proteins (LTPs) have been proposed to facilitate lipid transport at contact sites between organelles. Despite the fundamental importance of LTPs in cell physiology, our knowledge on the mechanisms of interorganelle lipid distribution remains poor due to the scarcity of assays to monitor lipid flux in vivo. In this review, we highlight the recent development of a versatile method named METALIC (Mass tagging-Enabled Tracking of Lipids in Cells), which uses a combination of enzymatic mass tagging and mass spectrometry to track lipid flux between organelles inside living cells. We discuss the methodology, its distinct advantages, limitations as well as its potential to unearth the pipelines of lipid transport and LTP function in vivo.

Public support for more stringent vaccine policies increases with vaccine effectiveness.

Under what conditions do citizens support coercive public policies? Although recent research suggests that people prefer policies that preserve freedom of choice, such as behavioural nudges, many citizens accepted stringent policy interventions like fines and mandates to promote vaccination during the COVID-19 pandemic-a pattern that may be linked to the unusually high effectiveness of COVID-19 vaccines. We conducted a large online survey experiment (N = 42,417) in the Group of Seven (G-7) countries investigating the relationship between a policy's effectiveness and public support for stringent policies. Our results indicate that public support for stringent vaccination policies increases as vaccine effectiveness increases, but at a modest scale. This relationship flattens at higher levels of vaccine effectiveness. These results suggest that intervention effectiveness can be a significant predictor of support for coercive policies but only up to some threshold of effectiveness.

Sperm proteomic landscape is altered in breeding bulls with greater sperm DNA fragmentation index.

Although, it is well understood that sperm DNA damage is associated with infertility, the molecular details of how damaged sperm DNA affects fertility are not fully elucidated. Since sperm proteins play an important role in fertilization and post-fertilization events, the present study aimed to identify the sperm proteomic alterations in bulls with high sperm DNA Fragmentation Index (DFI%). Semen from Holstein-Friesian crossbred breeding bulls (n = 50) was subjected to Sperm Chromatin Structure Assay. Based on DFI%, bulls were classified into either high- (HDFI; n = 6), or low-DFI (LDFI; n = 6) and their spermatozoa were subjected to high throughput proteomic analysis. Liquid chromatography and mass spectrometry analysis identified 4567 proteins in bull spermatozoa. A total of 2660 proteins were found common to both the groups, while 1193 and 714 proteins were unique to HDFI and LDFI group, respectively. A total of 265 proteins were up regulated and 262 proteins were down regulated in HDFI group. It was found that proteins involved in capacitation [heparin binding (molecular function), ERK1 and ERK2 cascade (biological process), PI3K-Akt signalling (pathway), Jak-STAT signalling (pathway)], spermatogenesis [TLR signalling (pathway), gamete generation (biological process)] and DNA repair mechanism (biological process) were significantly altered in the bulls with high DFI%.

Identification and preliminary characterization of conserved uncharacterized proteins from Chlamydomonas reinhardtii, Arabidopsis thaliana, and Setaria viridis.

The rapid accumulation of sequenced plant genomes in the past decade has outpaced the still difficult problem of genome-wide protein-coding gene annotation. A substantial fraction of protein-coding genes in all plant genomes are poorly annotated or unannotated and remain functionally uncharacterized. We identified unannotated proteins in three model organisms representing distinct branches of the green lineage (Viridiplantae): Arabidopsis thaliana (eudicot), Setaria viridis (monocot), and Chlamydomonas reinhardtii (Chlorophyte alga). Using similarity searching, we identified a subset of unannotated proteins that were conserved between these species and defined them as Deep Green proteins. Bioinformatic, genomic, and structural predictions were performed to begin classifying Deep Green genes and proteins. Compared to whole proteomes for each species, the Deep Green set was enriched for proteins with predicted chloroplast targeting signals predictive of photosynthetic or plastid functions, a result that was consistent with enrichment for daylight phase diurnal expression patterning. Structural predictions using AlphaFold and comparisons to known structures showed that a significant proportion of Deep Green proteins may possess novel folds. Though only available for three organisms, the Deep Green genes and proteins provide a starting resource of high-value targets for further investigation of potentially new protein structures and functions conserved across the green lineage.

Exploring Optically Stable Reddish-Orange Fluorescent Magnetic Pigment (0.90)Y2O3:(0.10-x)Eu3+:(x)Bi3+ for Anti-counterfeiting Applications.

The (0.90)Y2O3:(0.10-x)Eu3+:(x)Bi3+ nanophosphors (0.00 ≤ x ≤ 0.06) are synthesised using chemical combustion citrate route and characterized via X-ray diffraction, Raman spectroscopy, Fourier transform infrared spectroscopy, UV- visible and photoluminescence spectroscopy. The scanning electron micrographs indicate that the grain size of the phosphors ranges between 40 to 50 nm. The photoluminescence (PL) spectra, acquired under the excitation wavelength of 365 nm of ultraviolet light, show emission peaks at wavelengths 580 nm, 586-598 nm, 610 nm, 629-661 nm and 686-695 nm corresponding to the 5D0 → 7FJ electronic transitions of the Eu3+ ion with J = 0, 1, 2, 3 and 4, respectively. The most intense PL spectra at 611 nm (5D0 → 7F2), showcasing reddish-orange emission, indicate a higher concentration of Eu3+ ions in asymmetric sites within the Y2O3 host matrix. The presence of the distinct electronic transitions of Eu3+ in PL spectra acclaims that Bi3+ ions transfer their energy efficiently to Eu3+ ions in the matrix. Physical and chemical tests are being conducted on nanophosphors with Bi3+ substitutional doping of x = 0.02 and x = 0.04, both demonstrating intense PL emission. Magnetisation measurements suggest the soft magnetic nature of the nanophosphors, attributing it to the presence of Eu3+ ions in the 7F2 state. The highest PL intensity is seen in the nanophosphor (x = 0.04) with substitutional doping of 6% of Eu3+ and 4% of Bi3+ in Y2O3. This nanophosphor also demonstrates excellent optical stability in the investigated conditions and exhibits soft magnetic behaviour, positioning it as a promising material for incorporation as a fluorescent magnetic pigment in security ink applications. These features serve to prevent counterfeiting of secured documents both optically and magnetically.

Association analysis of Vascular Endothelial Growth Factor-A (VEGF-A) polymorphism in rheumatoid arthritis using computational approaches.

Rheumatoid arthritis (RA), is marked by joint inflammation leading to pannus formation which results in cartilage destruction promoting bone erosion. The pathological hallmark of RA includes synovial hyperplasia and synovial angiogenesis. Active tissue neovascularization is observed in RA. Vascular endothelial Growth factor A (VEGFA), an endothelial cell-specific proangiogenic molecule is triggered by hypoxic cells and its levels are upregulated in RA. The aim of this study was to investigate functional and pathogenic VEGFA variants and to identify the impact of point mutation in VEGFA's interaction with VEGFR2 and how these polymorphisms affect the susceptibility and severity of RA. We investigated impact of these point mutations on the stability of VEGFA using various computational tools. These mutations were further identified by conservational profile as they are highly involved as structural and functional mutations. Furthermore, these selected variants were modelled and docked against targeted domain regions IGD2 and IGD3 of VEGFR2. Further molecular dynamic simulations were performed using Gromacs. Out of 168 nsSNPS, 19 were highlighted as highly pathogenic using insilico prediction tools. InterPro and ConSurf revealed domains and conserved variants respectively. After stability analysis, we concluded that almost all the mutations were responsible for decreasing the protein stability. HOPE predicted that all the selected damaging nsSNPs were present in the domain which is essential for the functioning of VEGFA protein. Constructed Ramachandran plot and ERRAT validated the quality of all the models. Based on the interactions predicted by STRING database, we performed Protein-Protein docking between VEGFA and VEGFR2. We found few conserved interactions and new polar contacts among wild-type and mutants with VEGFR2. From the simulations, we concluded that mutant R108Q was the most stabilizing mutant among all others whereas R82Q, C86Y, and R108W complexed with VEGFR2 were comparatively less stabilizing as compared to the wild type. This study provides insight into pathogenic nsSNPs that can affect VEGFA protein structure and function. These high-risk variants must be taken into consideration for genetic screening of patients suffering from RA.

A SOX9-B7x axis safeguards dedifferentiated tumor cells from immune surveillance to drive breast cancer progression.

How dedifferentiated stem-like tumor cells evade immunosurveillance remains poorly understood. We show that the lineage-plasticity regulator SOX9, which is upregulated in dedifferentiated tumor cells, limits the number of infiltrating T lymphocytes in premalignant lesions of mouse basal-like breast cancer. SOX9-mediated immunosuppression is required for the progression of in situ tumors to invasive carcinoma. SOX9 induces the expression of immune checkpoint B7x/B7-H4 through STAT3 activation and direct transcriptional regulation. B7x is upregulated in dedifferentiated tumor cells and protects them from immunosurveillance. B7x also protects mammary gland regeneration in immunocompetent mice. In advanced tumors, B7x targeting inhibits tumor growth and overcomes resistance to anti-PD-L1 immunotherapy. In human breast cancer, SOX9 and B7x expression are correlated and associated with reduced CD8+ T cell infiltration. This study, using mouse models, cell lines, and patient samples, identifies a dedifferentiation-associated immunosuppression mechanism and demonstrates the therapeutic potential of targeting the SOX9-B7x pathway in basal-like breast cancer.

PolyID: Artificial Intelligence for Discovering Performance-Advantaged and Sustainable Polymers.

A necessary transformation for a sustainable economy is the transition from fossil-derived plastics to polymers derived from biomass and waste resources. While renewable feedstocks can enhance material performance through unique chemical moieties, probing the vast material design space by experiment alone is not practically feasible. Here, we develop a machine-learning-based tool, PolyID, to reduce the design space of renewable feedstocks to enable efficient discovery of performance-advantaged, biobased polymers. PolyID is a multioutput, graph neural network specifically designed to increase accuracy and to enable quantitative structure-property relationship (QSPR) analysis for polymers. It includes a novel domain-of-validity method that was developed and applied to demonstrate how gaps in training data can be filled to improve accuracy. The model was benchmarked with both a 20% held-out subset of the original training data and 22 experimentally synthesized polymers. A mean absolute error for the glass transition temperatures of 19.8 and 26.4 °C was achieved for the test and experimental data sets, respectively. Predictions were made on polymers composed of monomers from four databases that contain biologically accessible small molecules: MetaCyc, MINEs, KEGG, and BiGG. From 1.4 × 106 accessible biobased polymers, we identified five poly(ethylene terephthalate) (PET) analogues with predicted improvements to thermal and transport performance. Experimental validation for one of the PET analogues demonstrated a glass transition temperature between 85 and 112 °C, which is higher than PET and within the predicted range of the PolyID tool. In addition to accurate predictions, we show how the model's predictions are explainable through analysis of individual bond importance for a biobased nylon. Overall, PolyID can aid the biobased polymer practitioner to navigate the vast number of renewable polymers to discover sustainable materials with enhanced performance.

Effect of different concentrations of titanium and silver nanoparticles on maxillofacial silicone MDX4-4210 on cell viability, tear bond strength, and shore strength: An in vitro study.

Aim: The aim was to evaluate and compare the cell viability, tear bond strength, and shore hardness of MDX4-4210 silicone reinforced with titanium dioxide and silver nanoparticles in 1%, 2%, and 3%. Settings and Design: The study design involves in vitro comparative study. Materials and Methods: MDX4-4210 silicone incorporated with 1%, 2%, and 3% by weight of silver and titanium dioxide nanoparticles. A total of 112 specimens were prepared and grouped into 7, with 16 specimens in each group. Group 1 - control, Groups 2, 3, and 4 were 1%, 2%, and 3% silver, respectively. Groups 5, 6, and 7 were 1%, 2%, and 3% titanium dioxide nanoparticles, respectively. Cell viability was tested by MTT ASSAY on MG63 cell lines, tear bond strength was tested by peeling force in universal testing machine, and Shore A hardness was tested in durometer. Statistical Analysis Used: The cell viability values were statistically analysed using one-way analysis of variance, and Tukey honestly significant difference test, tear bond strength and shore hardness values were analysed using Mann-Whitney test. Results: Based on the MTT ASSAY test, 1% silver nanoparticles incorporated MDX4-4210 silicone showed maximum cell viability of 42.10%, whereas minimum cell viability was 18.06% for 3% of titanium dioxide-reinforced silicone. The mean value of tear bond strength of 1% silver and 1% titanium dioxide nanoparticles reinforced room temperature vulcanized maxillofacial silicone were 62.81 ± 3.637 N/m and 59.69 ± 5.313 N/m and the mean value of shore hardness of room temperature vulcanized of 1% silver and 1% titanium dioxide nanoparticles reinforced room temperature vulcanized maxillofacial silicone were 38.06 ± 1.237 and 36.75 ± 1.291. Conclusion: Cell viability of 1% silver nanoparticles reinforced MDX4-4210 silicone was higher in comparison to the other groups, and tear bond strength and shore hardness were significantly higher in 1% silver nanoparticles reinforced silicone compared to 1% titanium nanoparticles reinforced MDX4-4210 silicone.

Beyond Participation: Evaluating the Role of Patients in Designing Oncology Clinical Trials.

Historically, subject matter experts and healthcare professionals have played a pivotal role in driving oncology clinical trials. Although patients have been key participants, their deliberate and active contribution to the design and decision-making process has been limited. This scoping review aimed to examine the existing literature to scope the extent of active patient engagement in the design of oncology clinical trials and its corresponding influence on trial outcomes. We conducted a systematic search using two databases, namely MEDLINE (Ovid) and EMBASE, to identify relevant studies exploring patient engagement in cancer-related clinical research design. We identified seven studies that met the eligibility criteria. The studies highlighted the benefits of active patient involvement, such as improved recruitment strategies, and the attainment of more patient-centered trial outcomes. The influence of patient involvement varied from tangible developments like patient-friendly resources to indirect impacts like improved patient experiences and potentially higher adherence to trial intervention. The future of clinical trials should prioritize patients' values and perspectives, with regulatory bodies fostering these practices through clear guidelines. As the concept of patient centricity takes root in oncology research, the involvement of patients should evolve beyond mere participation.

Dual inhibition of glycolysis and glutaminolysis for synergistic therapy of rheumatoid arthritis.

BACKGROUND: Synovial fibroblasts in rheumatoid arthritis (RAFLS) exhibit a pathological aberration of glycolysis and glutaminolysis. Henceforth, we aimed to investigate if dual inhibition of these pathways by phytobiological compound c28MS has the potential of synergistic therapy for arthritis by targeting both glucose and glutamine metabolism. METHODS: The presence of HK2 and GLS across various cell types and associated gene expression in human synovial cells and a murine model of arthritis was evaluated by scRNA-seq. The metabolic profiling of RAFLS cells was done using H1-nuclear magnetic resonance spectroscopy under glycolytic and glutaminolytic inhibitory conditions by incubating with 3-bromopyruvate, CB839, or dual inhibitor c28MS. FLS functional analysis was conducted under similar conditions. ELISA was employed for the quantification of IL-6, CCL2, and MMP3. K/BxN sera was administered to mice to induce arthritis for in vivo arthritis experiments. RESULTS: scRNA-seq analysis revealed that many fibroblasts expressed Hk2 along with Gls with several genes including Ptgs2, Hif1a, Timp1, Cxcl5, and Plod2 only associated with double-positive fibroblasts, suggesting that dual inhibition can be an attractive target for fibroblasts. Metabolomic and functional analysis revealed that c28MS decreased the aggressive behavior of RAFLS by targeting both upregulated glycolysis and glutaminolysis. c28MS administered in vivo significantly decreased the severity of arthritis in the K/BxN model. CONCLUSION: Our findings imply that dual inhibition of glycolysis and glutaminolysis could be an effective approach for the treatment of RA. It also suggests that targeting more than one metabolic pathway can be a novel treatment approach in non-cancer diseases.

Molecular Link between Glo-1 Expression and Markers of Hyperglycemia and Oxidative Stress in Vascular Complications of Type 2 Diabetes Mellitus.

Chronic hyperglycemia and oxidative stress in Type 2 Diabetes Mellitus trigger cellular dysfunction via the formation of Advanced Glycation End Products (AGEs), resulting in dicarbonyl stress. Glyoxalase-1 (Glo-1) is the main defense against dicarbonyl stress. The aim of this study was to explore any cross-talk between Glo-1 and markers of hyperglycemia and oxidative stress. The siRNA-mediated downregulation of Glo-1 was performed in human microvascular endothelial cell line (HMEC-1). A Glo-1 transgenic rat model was developed. Glo-1 activity, as determined spectrophotometrically, and methylglyoxal were quantified using UPLC-MS/MS and the expression of representative markers of hyperglycemia and oxidative stress was performed using quantitative real-time PCR. A significant increase in the expression of Vascular Cell Adhesion Molecule-1 (VCAM-1) was observed in the case of the siRNA-mediated downregulation of Glo-1 in the microvasculature model under hyperglycemic conditions (p-value < 0.001), as well the as overexpression of Glo-1 in the macrovasculature (p-value = 0.0125). The expression of thioredoxin interacting protein (TXNIP) was found to be significantly upregulated in wildtype diabetic conditions vs. Glo-1 transgenic control conditions (p-value = 0.008), whereas the downregulation of Glo-1 had no impact on TXNIP expression. These findings substantiate the role of VCAM as an important marker of dicarbonyl stress (represented by Glo-1 downregulation), as well as of hyperglycemia, in diabetic vascular complications. Our findings also suggest a potential feedback loop that may exist between Glo-1 and TXNIP, as the highest expression of TXNIP is observed in cases of wildtype diabetic conditions, and the lowest expression of TXNIP is observed when Glo-1 transgene is being expressed in absence of dicarbonyl stress.