Biofilms based on bacteria Pseudomonas veronii (Ps. veronii) and Escherichia coli (E. coli) and yeast Saccharomyces cerevisiae (S. cerevisiae) were used for novel biosensor creation for rapid biochemical oxygen demand (BOD) monitoring. Based on the electrochemical measurement results, it was shown that the endogenous mediator in the matrix of E. coli and Ps. veronii biofilms and ferrocene form a two-mediator system that improves electron transport in the system. Biofilms based on Ps. veronii and E. coli had a high biotechnological potential for BOD assessment; bioreceptors based on such biofilms had high sensitivity (the lower limits of detectable BOD₅ concentrations were 0.61 (Ps. veronii) and 0.87 (E. coli) mg/dm³) and high efficiency of analysis (a measurement time 5–10 min). The maximum biosensor response based on bacterial biofilms has been observed in the pH range of 6.6–7.2. The greatest protective effect was found for biofilms based on E. coli, which has high long-term stability (151 days for Ps. veronii and 163 days for E. coli). The results of the BOD₅ analysis of water samples obtained using the developed biosensors had a high correlation with the results of the standard 5-day method (R² = 0.9820, number of tested samples is 10 for Ps. veronii, and R² = 0.9862, number of tested samples is 10 for E. coli). Thus, biosensors based on Ps. veronii biofilms and E. coli biofilms could be a novel analytical system to give early warnings of pollution. Full article

The use of microwave energy to recycle high-quality coarse aggregates from waste concrete or assist hard rock breakage in underground building engineering is promising. Controlling or promoting the damage of coarse aggregates, i.e., hard rocks, under microwave irradiation is a crucial issue faced by these techniques. Understanding the damage mechanisms of hard rocks exposed to microwaves is thus urgent. Fracture toughness is a significant mechanical parameter of rocks that reflects their ability to resist crack propagation and damage evolution. In this study, the fracture toughness degradation of microwave-heated granite was investigated by combining experimental investigations and numerical simulations. A three-point-bending (TPB) experiment was conducted on granite specimens after microwave irradiation. A coupled electromagnetic–thermal–mechanical model considering the actual mineral texture of the granite specimen was established. The evolution of the temperature gradient and stress field near the initial notch tip were investigated. The results suggest that the microwave-induced maximum temperature gradient and stress in granite are at the plagioclase–quartz (Pl–Qtz) interfaces or inside the Pl near the boundary. The region of cracking initiation was defined as the damage zone, which could be obtained by comparing the microwave-induced thermal stress with the critical value. The fracture toughness degradation, which corresponds to the evolution of the damage zones, can be divided into two stages. A relatively rapid decrease in fracture toughness in the first stage is primarily caused by the spread of the scattered damage zones along the Pl–Qtz interfaces; subsequently, a gentler fracture toughness degradation results mainly from the extension of the previous damage zones. Full article

In biomedicine, the critical task is to decode Drug–Drug Interactions (DDIs) from complex biomedical texts. The scientific community employs Knowledge Graph Embedding (KGE) methods, enhanced with advanced neural network technologies, including capsule networks. However, existing methodologies primarily focus on the structural details of individual entities or relations within Biomedical Knowledge Graphs (BioKGs), overlooking the overall structural context of BioKGs, molecular structures, positional features of drug pairs, and their critical Relational Mapping Properties. To tackle the challenges identified, this study presents HSTrHouse an innovative hierarchical self-attention BioKGs embedding framework. This architecture integrates self-attention mechanisms with advanced neural network technologies, including Convolutional Neural Network (CNN) and Graph Neural Network (GNN), for enhanced computational modeling in biomedical contexts. The model bifurcates the BioKGs into entity and relation layers for structural analysis. It employs self-attention across these layers, utilizing PubMedBERT and CNN for position feature extraction, and a GNN for drug pair molecular structure analysis. Then, we connect the position and molecular structure features to integrate them into the self-attention calculation of entity and relation. After that, the output of the self-attention layer is combined with the connected vectors of the position feature and molecular structure feature to obtain the final representation vector, and finally, to model the Relational Mapping Properties (RMPs), the representation vector is embedded into the complex vector space using Householder projections to obtain the BioKGs model. The paper validates HSTrHouse’s efficacy by comparing it with advanced models on three standard BioKGs for DDIs research. Full article

In this article, I critically analyze and respond to empirical data in the form of racialized discourse—specifically, racist messages sent directly to me as a result of my previously published article entitled, “A Love Letter to Educational Leaders of Color: CREWing UP with Critical Whiteness Studies”. Being informed by a robust racial analysis of acts that reinforce white supremacy, this article will likely be perceived as not nice by those who benefit from and work to protect white supremacy. Likely, I will be the one accused of being hateful, divisive, and even racist. In order to interrogate the weaponization of this conception of “niceness”, my analysis will be driven by Critical Race Hermeneutics with white emotionality and whitelashing used as interpretive lenses. As this article’s engagement with these critical race frameworks poses a threat to those who benefit from racism, this is a dangerous, not-so-nice critical race love letter. Full article

A new water-soluble polyamidoamine (PAMAM) dendrimer modified with 4-sulfo-1,8-naphthalimide (DSNI) and its monomeric structural analogue (MSDI) were synthesized. Their photophysical properties were investigated in organic solvents of different polarities and aqueous solutions. The effect of pH on fluorescence intensity was determined. It was found that the dendrimer emits blue fluorescence in an acidic medium, which is quenched in an alkaline environment. This phenomenon is due to the possibility of suppression of nonradiative photoinduced electron transfer in acidic media. The influence of different metal ions (Cu²⁺, Pb²⁺, Sn²⁺, Sr²⁺, Mg²⁺, Ba²⁺, Co²⁺, Hg²⁺, Zn²⁺, Ni²⁺, Fe³⁺, Al³⁺) and anions (CN⁻, S²⁻, S₂O₅²⁻, HPO₄²⁻, H₂PO⁴⁻, F⁻, CH₃COO⁻, NO₂⁻, CO₃²⁻, SO₄²⁻) on the intensity of the emitted fluorescence was studied. Quenching was only found in the presence of Cu²⁺. This makes the dendrimer suitable for determining copper ions in water solutions in the presence of other metal ions and anions. Additionally, DSNI was used as a ligand to obtain a stable copper complex, the structure of which was investigated by electron paramagnetic resonance (EPR), infrared spectrum, and elemental analysis. Two copper ions were found to form a complex with one dendrimer. The in vitro microbiological activity of the new compounds against bacteria Pseudomonas aeruginosa and two viruses HRSV-2 and HAdV-5 was investigated. With a view to obtaining antibacterial and anti-viral textiles, cotton fabrics were treated with the three compounds, and then their activity against the same microbial strains was investigated. It was found that the microbiological activity was preserved after the application of the new compounds to the cotton fabrics. Full article

The Common Agricultural Policy (CAP) is crucial in ensuring food safety and security in Europe. Providing a stable and diverse food supply also supports rural economies and promotes social, environmental and economic sustainability. However, as CAP consumes approximately 30% of the EU budget, debates regarding its pertinence have arisen. This paper aimed to understand European citizens’ perceptions of CAP, its associated benefits and their level of agreement regarding the allocation of the EU budget. Ultimately, the goal was to gain insights into EU citizens’ attitudes and perceptions towards the CAP. Information and data come from the European Survey Eurobarometer. The methods include statistical inferential techniques adjusted to the nature of the variables and goals. The findings confirm that European citizens generally perceive the CAP positively and have positive attitudes about the CAP. While some differences among various social groups may exist, the results did not identify any specific group strongly opposing the CAP. Overall, European citizens hold a favorable attitude towards the CAP, its associated benefits and budget allocation. This paper brings new insights into new European CAP measures and programs to promote food security and the sustainability of agriculture among European countries and citizens. These insights may be useful for public decision-makers to define better policies and measures adjusted to European citizens and to promote food security and sustainability. Full article

Various organisms, such as dogs and moths, can locate their prey and mates by sensing their smells. Following this manner, if an engineering device with the capability to detect a smell or gas source is realized, it can have a wide range of potential applications, such as searching for landmines, locating gas leaks, and rapid detection of fire. A previous study on the estimation of smell and gas-flow direction successfully detected the smell/gas-source direction in low-wind-velocity environments using a semiconductor gas sensor array. However, some problems are generally associated with the use of semiconductor gas sensors due to the use of heaters. This study aimed to detect the location of a smell/gas source using an integrated CMOS smell sensor array, which operates at room temperature without a heater. The experiment showed that under ideal conditions, the order of gas responses and concentration gradient of the gas enabled the estimation of the direction of the smell/gas-source location on one side of the sensor. Full article

In this work, we present the modification of a medical-grade silicone catheter with the N-vinylimidazole monomer using the grafting-from method at room temperature and induced by gamma rays. The catheters were modified by varying the monomer concentration (20–100 vol%) and the irradiation dose (20–100 kGy). Unlike the pristine material, the grafted poly(N-vinylimidazole) chains provided the catheter with hydrophilicity and pH response. This change allowed for the functionalization of the catheters to endow it with antimicrobial features. Thus, the quaternization of amines with iodomethane and bromoethane was performed, as well as the immobilization of silver and ampicillin. The inhibitory capacity of these materials, functionalized with antimicrobial agents, was challenged against Escherichia coli and Staphylococcus aureus strains, showing variable results, where loaded ampicillin was amply better at eliminating bacteria. Full article

Herein, a series of heterogeneous Fenton catalysts, Cu doped MnO₂ (CDM), with different Cu/Mn molar ratios were prepared via a hydrothermal reaction. Meanwhile, detailed characterizations were used to study the structures of CDM, and it is amazing that the morphology of CDM changed from nanowires to nanoflowers with an increasing amount of Cu doped. Apart from this, both the specific surface area and oxygen vacancy increased obviously with the increasing Cu/Mn molar ratio. Then, the degradation of different dyes was utilized to evaluate the catalytic activity of different CDM with H₂O₂ used as the oxidizing agent, and the 50%-CDM with the highest content of Cu doped displayed the best catalytic activity. Herein, the degradation efficiency (D%) of Congo red (CR) solution with low concentration (60 mg/L) reached 100% in 3 min, while the D% of CR solution with a high concentration (300 mg/L) reached 99.4% after 5 min with a higher dosage of H₂O₂. Additionally, the 50%-CDM also displayed excellent reusability, for which the D% values were still higher than 90% after the 14th cycles. Based on the structure characteristics and mechanism analysis, the excellent catalytic capacity of 50%-CDM was due to the combined influence of large specific surface area and abundant oxygen vacancy. Thus, a promising heterogeneous Fenton catalyst was developed in this study, which proved the treatment efficiency of actual dye wastewater. Full article

This paper examines the role of exchange rate changes on India’s trade. The drivers of exports and imports (income, exchange rate including sectoral differences, and exchange rate variability) are estimated for the short and long run including a structural break. Using annual data from 1994 to 2022, the results of dynamic fixed effects estimation show that both exports and imports are income-elastic in the short and long run, but income elasticity is far stronger for exports. Moreover, exports are responsive to the real effective exchange rate in the short run but not in the long run, and the reverse is true for imports. Furthermore, exchange rates have asymmetric effects for high-volume and primary sectors for exports and imports. The combined impacts show the ineffectiveness of using currency depreciation to address trade imbalances. Full article

The application results of profile control and water plugging technology are highly related to the gelation time and strength of phenolic resin hydrogel. In this work, a hydrogel solution was prepared by fully mixing the prepared polymer solution with a crosslinker. The static gelation process of PFR hydrogel in ampoule bottles and porous media was analyzed by changes in the viscosity and residual resistance coefficient. Then, the dynamic gelation of the PFR hydrogel in porous media was tested using a circulating flow device, and the changes in viscosity and injection pressure were analyzed during the dynamic gelation process. Finally, the effects of the polymer concentration and crosslinker concentration on dynamic gelation were analyzed. The initial gelation time and final gelation time in porous media were 1–1.5 times and 1.5–2 times those in ampoule bottles under static conditions, respectively. The initial dynamic gelation time in porous media was 2–2.5 times and 1.5–2 times the initial static gelation times in ampoule bottles and porous media, respectively. The final dynamic gelation time was four times and two times the initial static gelation times in ampoule bottles and porous media, respectively. The production after dynamic gelation in porous media comprised hydrogel aggregates and water fluid, leading to a high injection pressure and low viscosity of the produced liquid. As the concentration of polymer and crosslinker increased, the dynamic gelation time was shortened and the gel strength was increased. In the dynamic gelation process in porous media, the phenol resin hydrogel could migrate deeply, but it was limited by the concentrations of the polymer and crosslinker. The results of subsequent water flooding showed that the polymer hydrogel had a good plugging ability after dynamic gelation. The deep reservoir could only be blocked off in the subsequent water flooding process when the migration of hydrogel happened in the dynamic gelation process. Full article

High-speed railway suspension bridges (HSRSBs) have been constructed with the new advancements in technology. The deformation prediction for HSRSBs is essential to their safety and maintenance. The conventional prediction methods are developed for bridges without high-speed railway. Different factors, including temperature (TEMP), time delay compensation (TDC), train live load (TLL), are considered in these methods. However, the train side (TS) and train instantaneous position (TIP) have a significant impact on deformation for HSRSBs, and they are not used in the prediction. More importantly, the coupling issue among different factors is so significant that it cannot be neglected. In this study, we propose a deformation prediction model based on a backpropagation (BP) neural network. This model uses different factors as model input, including TEMP, TDC, TLL, TS, and TIP. The coupling issue is addressed by using the new model. The new model was evaluated using a dataset of 10-day field measurements. It achieves a mean absolute error (MAE) of 8.81 mm, a mean relative error (MRE) of 9.82%, and coefficient of determination (R²) of 0.94. The new model will provide high-precision prediction for deformation and will be used in the development of an early warning system. Full article

The application of deep learning algorithms to predict the molecular profiles of various cancers from digital images of hematoxylin and eosin (H&E)-stained slides has been reported in recent years, mainly for gastric and colon cancers. In this study, we investigated the potential use of H&E-stained endometrial cancer slide images to predict the associated mismatch repair (MMR) status. H&E-stained slide images were collected from 127 cases of the primary lesion of endometrial cancer. After digitization using a Nanozoomer virtual slide scanner (Hamamatsu Photonics), we segmented the scanned images into 5397 tiles of 512 × 512 pixels. The MMR proteins (PMS2, MSH6) were immunohistochemically stained, classified into MMR proficient/deficient, and annotated for each case and tile. We trained several neural networks, including convolutional and attention-based networks, using tiles annotated with the MMR status. Among the tested networks, ResNet50 exhibited the highest area under the receiver operating characteristic curve (AUROC) of 0.91 for predicting the MMR status. The constructed prediction algorithm may be applicable to other molecular profiles and useful for pre-screening before implementing other, more costly genetic profiling tests. Full article

Titanium alloys are commonly used for implants, but the naturally forming oxides are bioinert and not ideal for bacterial resistance or osseointegration. Anodization processes are a modification technique that can crystallize the oxides, alter oxide surface topography, and introduce beneficial chemistries. Crystalline titanium oxides are known to exhibit photocatalytic activity (PCA) under UVA light. Anodization was used to create mixed-phase oxides on six titanium alloys including commercially pure titanium (CPTi), Ti-6Al-4V (TAV), Ti-6Al-7Nb (TAN), two forms of Ti-15Mo (TiMo-β and TiMo-αβ), and Ti-35Nb-7Zr-5Ta (TNZT). Combined EDS and XPS analyses showed uptake of the electrolyte and substrate alloying elements into the oxides. The relative oxide PCA was measured using methylene blue degradation assays. CPTi and TAN oxides exhibited increased PCA compared to other alloys. Combined XRD and EBSD oxide phase analyses revealed an unfavorable arrangement of anatase and rutile phases near the outermost surfaces, which may have reduced PCA for other oxides. The relative Staphylococcus aureus attachment to each oxide was also assessed. The CPTi and TiMo-αβ oxides showed significantly reduced S. aureus attachment after 1 h of UVA compared to un-anodized CPTi. Cell culture results verified that the UVA irradiation did not negatively influence the MC3T3-E1 attachment or proliferation on the mixed-phase oxides. Full article

In this study, digital light processing (DLP) was utilized to generate 3D-printed blends composed of photosensitive acrylate-modified polylactic acid (PLA) resin mixed with varying weight ratios of lignin extracted from softwood, typically ranging from 5 wt% to 30 wt%. The microstructure of these 3D-printed blends was examined through X-ray microtomography. Additionally, the tensile mechanical properties of all blends were assessed in relation to the weight ratio and post-curing treatment. The results suggest that post-curing significantly influences the tensile properties of the 3D-printed composites, especially in modulating the brittleness of the prints. Furthermore, an optimal weight ratio was identified to be around 5 wt%, beyond which UV light photopolymerization experiences compromises. These findings regarding acrylate-modified PLA/lignin blends offer a cost-effective alternative for producing 3D-printed bio-sourced components, maintaining technical performance in reasonable-cost, low-temperature 3D printing, and with a low environmental footprint. Full article

The diagnosis of MS relies on a combination of imaging, clinical examinations, and biological analyses, including blood and cerebrospinal fluid (CSF) assessments. G-Oligoclonal bands (OCBs) are considered a “gold standard” for MS diagnosis due to their high sensitivity and specificity. Recent advancements have involved the introduced of kappa free light chain (k-FLC) assay into cerebrospinal fluid (CSF) and serum (S), along with the albumin quotient, leading to the development of a novel biomarker known as the “K-index” or “k-FLC index”. The use of the K-index has been recommended to decrease costs, increase laboratory efficiency, and to skip potential subjective operator-dependent risk that could happen during the identification of OCBs profiles. This review aims to provide a comprehensive overview and analysis of recent scientific articles, focusing on updated methods for MS diagnosis with an emphasis on the utility of the K-index. Numerous studies indicate that the K-index demonstrates high sensitivity and specificity, often comparable to or surpassing the diagnostic accuracy of OCBs evaluation. The integration of the measure of the K-index with OCBs assessment emerges as a more precise method for MS diagnosis. This combined approach not only enhances diagnostic accuracy, but also offers a more efficient and cost-effective alternative. Full article

In rotating detonation engines the turbine inlet conditions may be transonic with unprecedented unsteady fluctuations. To ensure an acceptable engine performance, the turbine passages must be suited to these conditions. This article focuses on designing and characterizing highly diffusive turbine vanes to operate at any inlet Mach number up to Mach 1. First, the effect of pressure loss on the starting limit is presented. Afterward, a multi-objective optimization with steady RANS simulations, including the endwall and 3D vane design is performed. Compared to previous research, significant reductions in pressure loss and stator-induced rotor forcing are obtained, with an extended operating range and preserving high flow turning. Finally, the influence of the inlet boundary layer thickness on the vane performance is evaluated, inducing remarkable increases in pressure loss and downstream pressure distortion. Employing an optimization with a thicker inlet boundary layer, specific endwall design recommendations are found, providing a notable improvement in both objective functions. Full article

Earthquake-triggered landslides (ETLs) feature large quantities, extensive distributions, and enormous losses to human lives and critical infrastructures. Near-real spatial prediction of ETLs can rapidly predict the locations of coseismic landslides just after a violent earthquake and is a vital technical support for emergency response. However, near-real prediction of ETLs has always been a great challenge with relatively low accuracy. This work proposes an ensemble prediction model of EnPr by integrating machine learning tree models and a deep learning convolutional neural network. EnPr exhibits relatively strong prediction and generalization performance and achieves relatively accurate prediction of ETLs. Six great seismic events occurring from 2008 to 2022 on the southeastern margin of the Tibetan Plateau are selected to conduct ETL prediction. In a chronological order, the 2008 M_s 8.0 Wenchuan, 2010 M_s 7.1 Yushu, 2013 M_s 7.0 Lushan, and 2014 M_s 6.5 Ludian earthquakes are employed for model training and learning. The 2017 M_s 7.0 Jiuzhaigou and 2022 M_s 6.1 Lushan earthquakes are adopted for ETL prediction. The prediction accuracy merits of ACC and AUC attain 91.28% and 0.85, respectively, for the Jiuzhaigou earthquake. The values of ACC and AUC achieve 93.78% and 0.88, respectively, for the Lushan earthquake. The proposed EnPr algorithm outperforms the algorithms of XGBoost, random forest (RF), extremely randomized trees (ET), convolutional neural network (CNN), and Transformer. Moreover, this work reveals that seismic intensity, high and steep relief, pre-seismic fault tectonics, and pre-earthquake road construction have played significant roles in coseismic landslide occurrence and distribution. The EnPr model uses globally accessible open datasets and can therefore be used worldwide for new large seismic events in the future. Full article

Efficiently determining crop water stress is vital for optimising irrigation practices and enhancing agricultural productivity. In this realm, the synergy of deep learning with remote sensing technologies offers a significant opportunity. This study introduces an innovative end-to-end deep learning pipeline for within-field crop water determination. This involves the following: (1) creating an annotated dataset for crop water stress using Landsat 8 imagery, (2) deploying a standalone vision transformer model ViT, and (3) the implementation of a proposed CNN-ViT model. This approach allows for a comparative analysis between the two architectures, ViT and CNN-ViT, in accurately determining crop water stress. The results of our study demonstrate the effectiveness of the CNN-ViT framework compared to the standalone vision transformer model. The CNN-ViT approach exhibits superior performance, highlighting its enhanced accuracy and generalisation capabilities. The findings underscore the significance of an integrated deep learning pipeline combined with remote sensing data in the determination of crop water stress, providing a reliable and scalable tool for real-time monitoring and resource management contributing to sustainable agricultural practices. Full article

The interplay between two paradigms, artificial intelligence (AI) and optical metasurfaces, nowadays appears obvious and unavoidable. AI is permeating literally all facets of human activity, from science and arts to everyday life. On the other hand, optical metasurfaces offer diverse and sophisticated multifunctionalities, many of which appeared impossible only a short time ago. The use of AI for optimization is a general approach that has become ubiquitous. However, here we are witnessing a two-way process—AI is improving metasurfaces but some metasurfaces are also improving AI. AI helps design, analyze and utilize metasurfaces, while metasurfaces ensure the creation of all-optical AI chips. This ensures positive feedback where each of the two enhances the other one: this may well be a revolution in the making. A vast number of publications already cover either the first or the second direction; only a modest number includes both. This is an attempt to make a reader-friendly critical overview of this emerging synergy. It first succinctly reviews the research trends, stressing the most recent findings. Then, it considers possible future developments and challenges. The author hopes that this broad interdisciplinary overview will be useful both to dedicated experts and a general scholarly audience. Full article

Subjective well-being presents a societal challenge for vulnerable older adults. This study aims to investigate the mediating role of place attachment in the relationship between attitudes toward aging and subjective well-being among community-dwelling older adults in Taiwan. Two waves of investigations were conducted to examine the interplay between attitudes toward aging, subjective well-being, and place attachment among older adults. In Wave I, 1190 participants were enrolled, revealing predominantly younger cohorts with substantial educational levels. The subsequent Wave II involved 483 participants, maintaining continuity in characteristics. Subjective well-being remained moderate across waves, with prevalent positive attitudes toward aging. Place attachment scores indicated moderate to high associations. After controlling for demographics, structural equation modeling (SEM) in both waves revealed significant positive associations: attitudes toward aging influenced well-being, attitudes toward aging were positively associated with place attachment, and place attachment was positively related to well-being. Mediation testing confirmed the mediating role of place attachment in the relationship between attitudes toward aging and well-being. These findings underscore the important role of place attachment. It is evident that improving attitudes toward aging is an effective intervention which can lead to a better sense of well-being by enhancing place attachment to empower civil society. Full article

Patients with rheumatoid arthritis (RA) are prone to develop infections. Methods: Accordingly, 195 untreated early (e)RA patients and 398 healthy controls were selected from women in Tatarstan’s cohort to study infectious history in the anamnesis (four criteria) and in the previous year (16 criteria). Information about annual infections was collected face-to-face from year to year by a qualified rheumatologist/ general practitioner and included the active use of information from medical records. Results: In the anamnesis, tuberculosis, and pneumonia, and in the previous year, respiratory tract infections, skin infections, and herpes simplex virus reactivation incidence were reported to be increased in eRA patients, as well as the event number and duration of acute and chronic tonsillitis. Moreover, more bacterial-suspected upper respiratory infections and urinary tract infections were retrieved in sporadic eRA patients as compared to familial eRA patients. An elevated immunization against CCP prevented respiratory tract infection in those with HSV exacerbation. Finally, associations were retrieved between infection (event number/delay) and RA indices: (i) chronic tonsillitis exacerbations with disease activity and health assessment (HAQ) in familial eRA; (ii) bacterial-suspected upper respiratory infections with the number of swollen and tender joints in sporadic eRA; and (iii) HSV exacerbation with inflammation in eRA patients with negative/low response against CCP. Here, we demonstrate the complex nature of the interplay of RA with specific infections. Conclusions: For the first time, differences in the patterns of annual trivial infections and their links with RA indices were found in cohorts of familial and sporadic cases of the disease. Additionally, for the first time, we identified a remarkable relationship between early RA and exacerbations of chronic tonsillitis, as well as tuberculosis in the patient’s history. Altogether, this study supports the existence of a complex interplay between infections and RA at onset driven by familial status and the presence of anti-CCP Ab at elevated levels. Full article