Search Results (55)

Phytopathogenic Ascomycetes Blumeria graminis f. sp. tritici (Bgt) causes wheat powdery mildew disease and impacts global wheat production. Decoding the molecular wheat-Bgt interaction could facilitate the wheat disease resistance breeding. In this study, we elucidated that wheat histone deacetylase 19 (TaHDA19) regulates susceptibility to Bgt pathogen by suppressing biosynthesis of cuticular wax and salicylic acid (SA). Knockdown of wheat TaHDA19 gene expression led to in enhanced cuticular wax and SA accumulation, potentiated Bgt conidia germination and appressoria formation, attenuated formation of Bgt haustoria and microcolonies. Histone deacetylase TaHDA19 is enriched at the TaECR and TaSARD1 promoter regions to facilitate histone deacetylation, and thus suppressing TaECR and TaSARD1 transcription. In addition, we identified cuticular wax and SA regulated by TaHDA19 as chemical cues determining wheat pre- and postsusceptibility to Bgt pathogen. These findings collectively support that the wheat histone deacetylase TaHDA19 epigenetically suppresses cuticular wax and SA biosynthesis, thereby dampening chemical cues essential for the wheat powdery mildew susceptibility. Full article

The fungal pathogen Blumeria graminis forma specialis tritici (B.g. tritici) infects bread wheat (Triticum aestivum L.) to cause wheat powdery mildew disease. Elucidating the molecular mechanism underlying wheat susceptibility to the pathogenic fungus B.g. tritici could facilitate wheat genetic improvement. In this study, we identified the wheat TaSWI3B gene as a novel Susceptibility gene positively regulating wheat susceptibility to B.g. tritici. The TaSWI3B gene encodes the SWI3B subunit of the SWI/SNF chromatin remodeling complex. The overexpression of the TaSWI3B gene enhances wheat powdery mildew susceptibility, whereas TaSWI3B silencing results in attenuated wheat powdery mildew susceptibility. Importantly, we found that TaSWI3B could be enriched at the promoter regions of the salicylic acid (SA) biosynthesis activator gene TaSARD1, facilitating nucleosome occupancy and thereby suppressing TaSARD1 transcription and inhibiting SA biosynthesis. Silencing of TaSARD1 and TaICS1 encoding a key enzyme in SA biosynthesis could attenuate the SA biosynthesis and powdery mildew resistance potentiated by knockdown of TaSWI3B expression. Collectively, these results suggest that the SWI3B subunit of the wheat SWI/SNF chromatin remodeling complex negatively regulates SA biosynthesis by suppressing TaSARD1 transcription at the epigenetic level and thus facilitates wheat powdery mildew susceptibility. Full article

Background/Objective: In recent years, artificial intelligence (AI) has gained increasing prominence in the fields of diagnostic decision-making in medicine. The aim of this study was to compare multidisciplinary team (MDT: rheumatology, pulmonology, thoracic radiology) decisions with single-session plans generated by ChatGPT-4o. Methods: In this cross-sectional concordance study, adults (≥18 years) with confirmed systemic autoimmune rheumatic disease (SARD) and having MDT decisions within the last 6 months were included. The study documented diagnostic, treatment, and monitoring decisions in cases of SARDs by recording answers to six essential questions: (1) What is the most likely clinical diagnosis? (2) What is the most likely radiological diagnosis? (3) Is there a need for anti-inflammatory treatment? (4) Is there a need for antifibrotic treatment? (5) Is drug-free follow-up appropriate? and (6) Are additional investigations required? Consequently, all evaluations were performed with ChatGPT-4o in a single-session format using a standardized single-prompt template, with the system blinded to MDT decisions. All data analyses in this study were conducted using the R programming language (version 4.3.2). An agreement between AI-generated and MDT decisions was assessed using Cohen’s Kappa (κ) statistic where κ (kappa) values represent the level of agreement: <0.20 = slight, 0.21–0.40 = fair, 0.41–0.60 = moderate, 0.61–0.80 = substantial, >0.80 = almost perfect agreement. These analyses were performed using the irr and psych packages in R. Statistical significance of the models was evaluated through p-values, while overall model fit was assessed using the Likelihood Ratio Test. Results: A total of 47 patients were involved in this study, with a predominance of female patients (61.70%, n = 29). The mean age was 61.74 ± 10.40 years. The most frequently observed diagnosis was rheumatoid arthritis (RA), accounting for 31.91% of cases (n = 15). This was followed by cases of anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis, interstitial pneumonia with autoimmune features (IPAF), and sarcoidosis. The analyses indicate a statistically significant level of agreement across all decision types. For clinical diagnosis decisions, agreement was moderate (κ = 0.52), suggesting that the AI system can reach partially consistent conclusions in diagnostic processes. The need for an immunosuppressive treatment and follow-up without medication decisions demonstrated a higher level of concordance, reaching the moderate-to-high range (κ = 0.64 and κ = 0.67, respectively). For antifibrotic treatment decisions, agreement was moderate (κ = 0.49), while radiological diagnosis decisions also fell within the moderate range (κ = 0.55). The lowest agreement—though still moderate—was observed in further investigation required decisions (κ = 0.45). Conclusions: In patients with SARDs with pulmonary involvement, particularly in complex cases, concordance was observed between MDT decisions and AI-generated recommendations regarding prioritization of clinical and radiologic diagnoses, treatment selection, suitability for drug-free follow-up, and the need for further diagnostic investigations. Full article

Powdery mildew disease caused by the obligate biotrophic fungus Blumeria graminis forma specialis tritici (B.g. tritici) severely affects grain yields and end-use quality of bread wheat (Triticum aestivum L.). Uncovering the mechanism underlying the wheat susceptibility to B.g. tritici pathogen could contribute to the wheat breeding against powdery mildew disease. Herein, we revealed that the wheat DNA methyltransferase TaMET1 negatively regulates biosynthesis of defense hormone salicylic acid (SA) to promote powdery mildew susceptibility. Overexpression of TaMET1 compromised wheat resistance against B.g. tritici pathogen, while silencing of TaMET1 led to the SA overaccumulation and enhanced powdery mildew resistance. TaMET1 directly targets the SA biosynthesis activator gene TaSARD1. Decreased DNA methylation, increased histone acetylation, and reduced nucleosome occupancy at TaSARD1 promoter regions were observed in the TaMET1-silenced wheat plants, which is associated with activated TaSARD1 gene transcription. Silencing of the TaSARD1 and TaICS1 genes resulted in attenuated SA biosynthesis and dampened powdery mildew resistance in the TaMET1-silenced wheat plants. These results implied that DNA methyltransferase TaMET1 epigenetically suppresses the SA biosynthesis activator gene TaSARD1 by modulating DNA methylation, histone acetylation and nucleosome occupancy, thereby negatively regulating SA biosynthesis and facilitating the powdery mildew susceptibility. Full article

Aeration is one of the most energy-intensive operations in wastewater treatment plants, with its efficiency strongly affected by the presence of surfactants. This study investigates the impact of Sodium Dodecyl Sulphate (SDS) on oxygen mass transfer using a commercial fine-bubble diffuser. Oxygen transfer experiments were performed under varying air flow rates and SDS concentrations. Key parameters, including the volumetric mass transfer coefficient ($k_{L}a$), gas holdup, bubble size, and interfacial area, were experimentally measured and analysed. SDS reduces the average bubble diameter by up to 50%; above 4 mg/L, further increases in concentration do not change the bubble size. Gas holdup increases by approximately 2% per mg L⁻¹ of SDS, and a new empirical correlation was proposed to predict gas holdup as a function of air flow rate and surfactant concentration, achieving an R² of 0.97 with deviations below 10%. Despite the increase in interfacial area, SDS strongly suppresses interfacial turbulence, reducing the liquid-side mass transfer coefficient ($k_L$) by up to 70%, which ultimately leads to a significant loss of overall oxygen transfer efficiency. The Sardeing model, originally developed for single bubbles, successfully predicted $k_L$ within ±15% of the experimental values, demonstrating its potential as a practical tool for estimating oxygen transfer in aeration systems. These findings highlight the substantial impact of surfactants on fine-bubble aeration performance and underscore the need to account for their effects in the design and operation of industrial aeration systems. Full article

Pathogenic fungus Blumeria graminisforma specialistritici (B.g. tritici) is the causal agent of the devastating wheat powdery mildew disease. Identifying the key regulators governing wheat susceptibility to the B.g. tritici pathogen is essential for developing wheat varieties with improved powdery mildew resistance. In this study, we demonstrated that the wheat chromatin remodeler TaSWI3D positively regulates wheat susceptibility to B.g. tritici. Overexpression of TaSWI3D gene attenuates wheat resistance against B.g. tritici, while silencing of TaSWI3D gene potentiates wheat powdery mildew resistance. TaSWI3D protein was found to be enriched at the promoter regions of the TaSARD1 gene encoding the salicylic acid (SA) biosynthesis activator, and silencing of TaSWI3D resulted in decreased nucleosome occupancy at the TaSARD1 promoter regions. Activated TaSARD1 transcription and increased SA accumulation were observed in the TaSWI3D-silenced wheat plants. Silencing of TaSARD1 and the SA biosynthesis gene TaICS1 resulted in attenuated SA biosynthesis and decreased powdery mildew resistance in the TaSWI3D-silenced wheat plants. These findings support that the chromatin remodeler TaSWI3D maintains epigenetic suppression of the SA biosynthesis activator gene TaSARD1 and negatively regulates SA biosynthesis, thereby positively contributing to wheat powdery mildew susceptibility. Full article

Objective: To evaluate the real-world safety and efficacy of macitentan (MACI) in patients with systemic autoimmune rheumatic diseases (SARDs) and refractory digital ulcers (DUs). Methods: We conducted a retrospective observational study of 42 patients treated with MACI (10 mg/day) on a compassionate-use basis across Spanish reference hospitals. Given the cohort’s heterogeneity, a two-step analysis was performed: a global assessment of all patients, followed by a subgroup analysis restricted to those with systemic sclerosis (SSc) or fulfilling very early SSc (VEDOSS) criteria to explore predictors of response. Efficacy was defined as complete healing, partial response, or a lack of response based on physician assessment. Safety was evaluated through analysis of adverse events. Results: In the global cohort, MACI demonstrated a high rate of complete ulcer healing (82.9%) at the 3-month follow-up, with a significant reduction in median ulcer count (p < 0.001). Subgroup analysis within the SSc/VEDOSS cohort (n = 36) revealed that the presence of gastrointestinal involvement (GI) and a higher baseline DUs were significant predictors of a poorer therapeutic response (p = 0.022 and p = 0.028). The drug was well-tolerated; adverse events were infrequent and rarely led to treatment discontinuation. Conclusions: In this real-world refractory population, MACI was associated with rapid DU healing and a favorable safety profile. GI and higher ulcer burden predicted diminished treatment response in SSc patients. These results support the use of MACI as a valuable therapeutic option for severe digital vasculopathy in SARDs, although further prospective studies are warranted to confirm these observations. Full article

Systemic lupus erythematosus (SLE) and other systemic autoimmune rheumatic diseases (SARDs) require long-term immunosuppressive therapy, placing patients at increased risk of infection. Salmonella species are particularly concerning due to their invasiveness and potential link to autoimmune activation, notably in SLE. This study aimed to compare the risk of culture-confirmed Salmonella infection between SLE and other SARDs, based on data from the Chang Gung Research Database between 2005 and 2020. After propensity score matching, 3537 patients per group were analyzed. Patients with SLE had a higher incidence of Salmonella infection compared with those with other SARDs (0.54 vs. 0.17 per 1000 person-years), with a significantly greater cumulative incidence (log-rank p < 0.01). The adjusted hazard ratio (HR) for Salmonella infection in SLE was 2.47 (95% confidence interval (CI): 0.95–6.38), and the competing risk model confirmed a significant association (sub-distribution HR 2.58, 95% CI: 1.06–6.29, p = 0.04). Among SLE patients, lymphopenia was the only independent predictor of Salmonella infection (adjusted HR 3.98, 95% CI: 1.83–8.68, p < 0.001). Bloodstream infections were most common (70%), and serogroup D was the predominant strain (80%). These results suggest patients with SLE face higher Salmonella risk than other SARDs, especially those with lymphopenia, underscoring the need for targeted surveillance and preventive strategies. Full article

Launching a new institution of higher education requires navigating complex stakeholder relationships while justifying significant public investment. The rarity of successfully launching new postsecondary institutions makes each case a valuable source of insights for higher education leaders seeking to advance institutional innovation. This case study examines how the City University of New York (CUNY) successfully founded Guttman Community College (GCC) in 2012. Using Strategic Academic Research and Development (SARD) as a conceptual framework, we analyze two distinct phases: the founding process (2007–2012) and early operational years. During the founding phase, CUNY’s planning team excavated research-based best practices from leading experts and harnessed local expertise through consultative meetings with community college presidents, administrators, and faculty from across the university. In the operational phase, GCC institutionalized continuous improvement through an advisory board, dedicated Assessment Days, the Academic Assessment & Learning Committee governance structure, and the SAGE (Systematic Approach for Guttman Effectiveness) framework. Despite recent declines following the onset of the COVID-19 pandemic, the college’s initial three-year graduation rate of 49.1% dramatically aaexceeded CUNY’s community college average of 15.9% from the same time period. This case demonstrates how systematic application of SARD principles can guide successful institutional innovation in higher education. Full article

To address the limitation of existing static defect detection methods in capturing code semantics and structural relationships—which leads to incomplete feature representation—we propose a multimodal feature fusion approach for source code defect detection. First, semantic features are extracted from code character sequences while structural features are derived from Abstract Syntax Trees (ASTs). Second, a structural attention mechanism dynamically models interdependencies between these two modalities and fuses them into comprehensive representation vectors. Finally, defect detection is performed based on the integrated representations. Experimental results on the Sard dataset demonstrate: Compared to baseline methods using single representations (semantic or structural), our approach improves F1-score by 1.96% to 11.76%. Against other feature fusion methods, it achieves 1.36% to 1.66% higher F1-score. The method demonstrates good stability when dealing with imbalanced defect category data. By effectively fusing multimodal code information, this approach significantly enhances the accuracy and adaptability of code defect detection in open-source environments. Full article

Background: Women with systemic autoimmune rheumatic disease (SARD) are at higher risk of developing infection-related complications, anxiety, and depression. Using the example of the COVID-19 pandemic, we aimed to explore the impact of this external stressor on symptoms of depression, anxiety, and stress in a sample of women with SARD in a cross-sectional study design. Methods: Females aged 18–50 with SARD were enrolled from 04/2021 to 04/2022 at the Medical University of Vienna or through an online self-help group, while snowball sampling was used to recruit an age-matched healthy control group. Participants completed questionnaires including: (1) demographic information, medical history, and access to healthcare; (2) the Depression, Anxiety, and Stress Scale (DASS-21); and (3) the Coronavirus Anxiety Scale (CAS). Parameters were compared between groups using Chi-squared, Fisher’s exact, and Mann–Whitney U tests. Linear regression analysis was used to investigate which individual factors predicted the DASS-21 in women with SARD. Results: The study sample consisted of 226 women (n = 99 with SARD and n = 127 healthy controls). Women with SARD reported lower DASS-21 stress (p = 0.008) and CAS scores (p = 0.057) than the control group. There were no significant differences in DASS-21 anxiety or depression scores. Among women with SARD, a linear regression model identified the most important predictors of DASS-21 as access to rheumatological care (p = 0.002) and recent disease activity (p = 0.028). Conclusions: Despite the pandemic, women with SARD reported mental health outcomes equal to or better than those of the healthy control group. Continued access to rheumatological care may serve as an important protective factor for their mental health during large-scale crises like pandemics. Full article

Systemic autoimmune rheumatic diseases (SARDs), such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and Sjögren’s syndrome (SS), are traditionally characterized by chronic inflammation and immune-mediated damage to joints and other tissues. However, many patients also experience symptoms such as widespread pain, persistent fatigue, cognitive dysfunction, and autonomic disturbances that cannot be attributed directly or entirely to peripheral inflammation or structural pathology. These conditions suggest the involvement of interactions between the nervous and immune systems, which probably include both peripheral and central components. This review summarizes the current knowledge of neurological and neuroimmune mechanisms that may contribute to these symptoms in SARDs. Glial cell activation and neuroinflammation within the central nervous system (CNS), small-fiber neuropathy (SFN) affecting peripheral nociceptive pathways, central pain sensitization, and autonomic nervous system dysfunction will be discussed. In addition, the role of molecular mediators, including cytokines, neuropeptides, and microRNAs, that could potentially modulate neuroimmune signaling will be highlighted. Integrating findings from pathology, immunology, and neuroscience, this review seeks to provide a useful framework for understanding neuroimmune dysregulation in SARDs. It also highlights the clinical relevance of these mechanisms and summarizes new directions for diagnosis and treatment. Full article

This study explores the impact of educational technology on student success within higher education institutions (HEIs). Faced with pressures to improve enrollment, retention, and graduation rates, HEIs have increasingly turned to technology solutions. This article examines a pilot initiative at a large midwestern university, which implemented a collaborative studying software platform across multiple campuses. The research employed a Strategic Academic Research and Development (SARD) framework, triangulating data sources, methods, and interpreters to assess the effectiveness of the technology in improving student outcomes. This study utilized both quantitative and qualitative methodologies. Quantitative data included pass rates, grade-point averages, instructor fidelity, and software usage metrics, analyzed using Chi-square tests, analysis of variance, and linear mixed-effects models. Qualitative data were gathered from instructor reflections and student surveys, providing insights into changes in student engagement and performance. Pass rates and average GPAs increased following the intervention, but gains were similar across usage levels. Instructor fidelity was significantly associated with student performance, and results varied by discipline and campus, emphasizing the importance of context. This study also revealed challenges related to student adoption and instructor engagement with the technology. Overall, the findings suggest that while educational technology can enhance student success, its effectiveness depends on thoughtful integration and continuous assessment. The SARD framework proved valuable in guiding the evaluation process, emphasizing the need for comprehensive and collaborative approaches to educational technology assessment. Full article

This study addresses the side effect of the rapid development of the Internet, positioning botnets within digital ecosystems as a very serious potential threat to the Internet users. Malicious web robot might facilitate Web/data scraping, DDoS attacks, and data theft yielding serious cybersecurity threats. Modern botnets are advanced and have unique browser fingerprints, making their detection a real challenge. Traditional feature extraction methods heavily depend on expert knowledge. They also struggle with dimensional inconsistency when processing sessions of varying lengths, failing to counter evolving camouflage attacks. To approach such challenges, we propose Session2vec, a session representation framework based on multi-instance learning (MIL), which pioneers the MIL approach for Web session modeling. In this approach, we treat each request as an instance and the entire session as an instance collection, and then we use the FastText model to convert each URL request into a vector representation. Then, we utilize two innovative multi-instance aggregation methods: SARD (Session-level Aggregated Residual Descriptors) and SFAR (Session-level Fisher Aggregated Representation) to aggregate variable-length sessions into fixed-dimensional vectors capturing spatiotemporal features and distributional information within sessions. Simulation results of the proposed SARD and SFAR methods on public datasets show accuracy improvement of 5.2% and 16.3% on average, respectively, compared to state-of-the-art baselines. They also enhance F1 scores by 8.5% and 19.7%, respectively. Full article