Search Results (103)

Background: Guanine-rich DNA regions can fold into G-quadruplex (G4) structures, which are prevalent in telomeres and oncogene promoters, making them attractive targets for anticancer therapeutics. Small molecules capable of selectively stabilizing G4 DNA can disrupt telomerase activity and oncogene expression, offering a promising strategy for cancer intervention. Methods: A rationally designed series of DPPZ–anhydride-conjugated ligands (1 and 2) and their corresponding quaternized derivatives (1-q and 2-q) were synthesized to investigate the combined effects of π-extension, bromine substitution, and cationic modification on DNA recognition. The synthetic strategy relied on the incorporation of a highly planar DPPZ–anhydride scaffold to enhance π-surface area, followed by selective quaternization to introduce permanent positive charge and reinforce electrostatic interactions with the DNA backbone. All compounds were fully characterized by NMR and spectroscopic methods. The DNA-binding properties of the ligands were systematically evaluated toward duplex (ds-DNA) and G-quadruplex (G4-DNA) structures using UV–Vis absorption titration, fluorescence intercalator displacement (FID) assays, and competitive dialysis experiments. Quaternization markedly enhanced intrinsic binding constants and significantly reduced DC₅₀ values, particularly for G4-DNA. While bromine substitution increased overall binding affinity, it did not substantially improve topology selectivity. Among the series, compound 1-q exhibited the most favorable balance between affinity and G4 selectivity. Results: The interaction of the compounds with BSA was quantified using Stern–Volmer quenching constants, which demonstrated a clear trend of enhanced quenching efficiency upon modification. The binding strength followed a descending order of 1-q > 2-q > 1 > 2, highlighting the superior performance of the first series over the second. These findings indicate that the structural features of 1-q facilitate a more robust interaction within the hydrophobic pockets of the protein. Conclusions: Overall, the results demonstrate that strategic π-conjugation combined with electrostatic reinforcement provides an effective approach for the development of topology-selective DNA-binding ligands. Full article

The aim of this study was to investigate the regulatory roles of distinct signaling cascades within the death receptor pathway in host cell apoptosis induced by Eimeria tenella (E. tenella); to this end, primary chicken embryo cecal epithelial cell culture, gene silencing, enzyme-linked immunosorbent assay (ELISA), Hoechst–Annexin V/PI apoptosis staining, hematoxylin–eosin (HE) staining, and quantitative real-time polymerase chain reaction (qRT-PCR) were employed. At 4, 24, 72, and 120 h post-inoculation (hpi) with E. tenella sporozoites, the proportion of apoptosis in six treatment groups [Group C, Group T0 (E. tenella infection group), Group T1 (E. tenella + Fas SiRNA), Group T2 (E. tenella + TRAIL SiRNA), Group T3 (E. tenella + TNFR1 SiRNA), and Group T4 (E. tenella + NC SiRNA)] and the dynamic changes in Fas cell surface death receptor (Fas), tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), tumor necrosis factor receptor 1 (TNFR1), TNF receptor-associated death domain (TRADD), Fas-associated death domain (FADD), and death domain-associated protein (Daxx) expression and caspase-8 activity in the cells were determined. The results demonstrated that, from 4 to 120 hpi, the Fas and TNFR1 mRNA expression levels in Group T0’s host cells were significantly higher than those in Group C (p < 0.05 or p < 0.01). At 72 and 120 hpi, TRAIL mRNA expression in Group T0’s host cells was significantly or highly significantly elevated compared to that in Group C (p < 0.05 or p < 0.01). From 24 to 120 hpi, the expression levels of the FADD and Daxx genes, caspase-8 activity, and apoptotic rates in Group T1’s host cells were significantly lower than those in Group T4 (p < 0.05). At 72 and 120 hpi, the FADD expression, caspase-8 activity, and apoptotic rates in Group T2’s host cells were significantly reduced relative to Group T4 (p < 0.05). Additionally, at 4 hpi, TRADD gene expression in Group T3’s host cells was significantly lower than that in Group T4 (p < 0.05), while the apoptotic rate was significantly higher (p < 0.05). However, from 24 to 120 hpi, the TRADD expression, caspase-8 activity, and apoptotic rates in Group T3’s host cells were significantly lower than those in Group T4 (p < 0.05). The results indicated that, in the early stages of E. tenella development, TNFR1 overexpression promoted TRADD mRNA expression, thereby inhibiting the apoptosis of E. tenella host cells. In the middle and late developmental stages of E. tenella, the Fas-FADD, Fas-Daxx, TRAIL-FADD, and TNFR1-TRADD apoptotic pathways were all activated, collectively facilitating host cell apoptosis. The pro-apoptotic effects of these pathways were ranked in descending order, as follows: Fas signaling pathway > TNFR1 signaling pathway > TRAIL signaling pathway. Full article

Modern software development fundamentally relies on agile methodologies and DevOps practices to facilitate accelerated software delivery. Continuous integration and continuous deployment CI/CD are among the most critical DevOps practices that require considerable attention to execute successfully. Therefore, this study proposes a multi-class XGBoost-based model to improve the performance of CI/CD failure prediction. The proposed model was trained and tested using the comprehensive TravisTorrent dataset, which contains extensive build information from several projects developed in various programming languages. The experimental results demonstrate that the proposed model achieves a statistically significant performance improvement of nearly 18% over SVM and the Random Forest models. Beyond the performance improvement, SHAP (SHapley Additive exPlanations) analysis was employed to explain the model’s decision-making process, revealing that the most influential features, ranked in descending order of importance, are build log status, build duration, build start time, the number of commits in the repository, and repository age. This interpretability enhances both the reliability and transparency of the proposed model. Full article

Spinal Cord Injury (SCI) rehabilitation is undergoing a transformative shift with the emergence of new treatment strategies. Historically, treatment options were limited, and few offered meaningful recovery. Recent work in human models has shown that neuromodulation specifically with spinal cord epidural stimulation (SCES) paired with task-specific training (TsT) can partially restore motor function such as the ability to stand, step, and perform volitional movements. Despite these advances, the recovery has been shown to plateau even with the combination of therapies. The recovery process typically leads to partial rather than complete restoration of function. This limitation arises because current approaches primarily reactivate existing circuits rather than repair the disrupted pathways. Scar tissue and loss of descending and ascending connections remain major barriers to full recovery, restricting the transmission of neural signals. We argue that the next phase of research should be a synergistic strategy building upon the successes of neuromodulation and TsT while incorporating a regenerative therapy such as stem-cell-based interventions. Whereas neuromodulation and task-specific training increases excitability and reorganizes existing networks, stem cells have the potential to repair structural damage and re-establish communication across injured regions or facilitating the establishment of dormant pathways. The future of SCI recovery relies on multi-modal synergistic interventions that are likely to maximize long-term functional outcomes. In the current perspective, we summarized the basic findings on applications of SCES on restoration of sensory-motor functions. We then projected on current interventions on utilizing stem cell therapy intervention. We highlighted the outcomes of randomized clinical trials, and the major barriers for considering the synergistic approach between SCES and stem cell intervention. We are hopeful that this perspective may lead to roundtable scientific discussion to bridge the gap on how to conduct numerous clinical trials in the field. Full article

Automated quality assurance is essential for low-dose computed tomography (LDCT) lung screening, yet manual checks strain clinical workflows. We present a fully automated artificial intelligence tool that quantifies scan coverage and image noise in LDCT without user input. Lungs and the aorta are segmented to measure cranial/caudal over- and underscanning, and noise is computed as the standard deviation of Hounsfield units (HUs) within descending aortic blood, normalized to a 1 ${\mathrm{mm}}^3$ voxel. Performance was verified in a reader study of 98 LDCT scans from the National Lung Screening Trial (NLST), and then applied to 38,834 NLST scans reconstructed with a standard kernel. In the reader study, lung masks were rated ≥“Nearly Perfect” in 90.8% and aorta-blood masks in 96.9% of cases. Across 38,834 scans, mean overscanning distances were 31.21 mm caudally and 14.54 mm cranially; underscanning occurred in 4.36% (caudal) and 0.89% (cranial). The tool enables objective, large-scale monitoring of LDCT quality—reducing routine manual workload through exception-based human oversight, flagging protocol deviations, and supporting cross-center benchmarking—and may facilitate dose optimization by reducing systematic over- and underscanning. Full article

Blood culture remains the gold standard for identifying bloodstream infections caused by bacteria and fungi. Isolation of the culprit microorganism onto agar plates also facilitates antimicrobial susceptibility testing. The purpose of this study was to determine the contamination rates, pathogen profile, and antimicrobial resistance in a secondary healthcare setting in a two-year timeframe. In this study, data regarding blood cultures of the years 2023 and 2024 were retrospectively analyzed to address the above questions. Blood cultures were incubated for seven days before being discarded as negative. The percentage of positive blood cultures for both years was 14.3%. Most positive cultures contained Gram-positive cocci, with a prevalence of coagulase-negative Staphylococci. In descending order, 72.72% were coagulase-negative Staphylococci, 15.15% were Staphylococcus aureus, and 12.12% were Streptococci. One strain of S. aureus was methicillin-resistant (MRSA), and one strain of Enterococcus faecium was vancomycin-resistant (VRE). Of the Gram-negative rods, 78.3% were Enterobacterales. Of these, Escherichia coli, Klebsiella pneumoniae, and Proteus mirabilis were the top pathogens. The remainder comprised eight strains of Pseudomonas aeruginosa, four strains of Acinetobacter baumannii (one pandrug-resistant), three strains of Stenotrophomonas maltophilia, one strain of Sphingomonas paucimobilis, and one strain of Campylobacter jejuni. The isolated fungi comprised Candida parapsilosis, Candida glabrata, and Candida tropicalis. Of the isolated Escherichia coli strains, 39.5% were resistant to ciprofloxacin regardless of origin (outpatient or hospitalized patients). Outpatient samples were taken in a Hemodialysis Unit that collaborates with our laboratory, obtained from patients with fever or other signs of infection. Distinguishing true bacteremia from contamination remains challenging. The contamination rate in our study was quite high at 5.3%. Since there is no dedicated phlebotomy team in our healthcare setting, in light of our results, educational courses have been conducted to demonstrate the best practices for sample collection. Full article

Rodents models of myocardial infarction (MI) continue to be frequently used in preclinical cardiovascular research, despite alternative approaches being on the rise. The commonly used coronary artery permanent ligation (PL) approach is often hampered by substantial perioperative mortality and variable success rates. We optimized the rat PL protocol by relying exclusively on isoflurane inhalation anesthesia by introducing a standardized intubation setup, maintaining strict control of body temperature throughout surgery, and surgical technique refinements. The latter included gentle mobilization of the Pectoralis major and thymus, a medial thoracotomy through the third intercostal space, and the use of a reference ligature to facilitate reliable identification and ligation of the left anterior descending coronary artery (LAD). Cardiac rhythm was continuously monitored, and extubation was carefully timed to reduce complications. With this protocol, perioperative mortality was reduced to zero and successful ligation was obtained in 94% of animals (n = 172). Echocardiography and histology confirmed consistent induction of infarcts. By lowering invasiveness and improving survival and reproducibility, the refined PL method enhances both the reliability of preclinical research and compliance with the 3Rs, representing a meaningful step forward for studies in cardiac regeneration. Full article

The angle of repose is a fundamental parameter for assessing the stability of coral reefs. However, predictive models for this angle are currently lacking. In this study, a series of laboratory experiments were undertaken to investigate the angle of repose by varying moisture content, particle shape, and particle size. Based on our experimental data, variation in the angle of repose with moisture content is classified into five distinct zones. It is demonstrated that the range of moisture content for each zone varies with particle size. Coral sands of dendrite, flake, rod, and block particles have a descending order of angle of repose, as demonstrated for a sieve size of 4.5 mm. The angle of repose for dry, submerged, and steady coral sands exhibits a correlation with the nominal diameter of particle size. Finally, extended models are proposed for predicting the angle of repose of coral sands (R² = 0.8, D_n50 = 0.317−5.470). To facilitate use of these models, a linear relationship between sieve particle size diameter, nominal particle size diameter, and Corey shape factor, allowing for conversion among these parameters, is established. This study thereby helps to enhance our understanding of how moisture content affects angle of repose and improve our ability to predict the angle for coral grains with intricate geometries. Full article

This paper examines the translation theories and practices of Xu Zongze 徐宗澤 (1886–1947), a key figure in the Jesuit community of the Zi-ka-wei compound 徐家匯. Descending from the prominent Catholic Xu family and serving as chief editor of the Revue Catholique 聖教雜誌, Xu was uniquely positioned to engage in religious and cultural dialogues. By situating Xu within modern China’s translation history, this paper highlights his significant contributions to translation scholarship, especially in merging Western religious thought with Chinese traditions. Xu utilized the “Discussion” column of the Revue for his “Treatise on Translation” 譯書論, celebrating Jesuit translation accomplishments and examining historical policies. His works advocate for using the Jesuit legacy in contemporary translation debates to enhance cultural understanding. Xu’s efforts, including the Synopsis of Jesuit Translations during the Ming and Qing Dynasties 明清間耶穌會士譯著提要 and the “New Terms” series, resist linguistic dominance while facilitating intercultural understanding. Through his translation experience and Jesuit cultural initiatives, Xu Zongze advocated for the establishment of a Catholic translation institute aimed at developing talent and enhancing communication with Catholic publishers. By centering on Xu, this study reexamines the role of Zi-ka-wei within the context of modern Chinese translation history, evaluating how its engagement with Western knowledge effectively addressed the intellectual demands of the era, which called for contemporary interpretations. Full article

Colombo, a rapidly urbanizing city, increasingly faces the Urban Heat Island (UHI) effect due to urban expansion and climate change. Urban parks mitigate UHI by creating cool microclimates, quantified as Park Cool Island Intensity (PCII), the temperature difference between parks and surrounding areas. Colombo exhibits an average cooling effect of 0.98 °C $\pm 0.21\%$. The results found that the park area has the most significant positive relationship with the PCII, where the model explained 87.7% of the variance (R² = 0.877), indicating a strong fit, following the park perimeter (R² = 0.811). Park vegetation characteristics exert a significant influence to enhance the cooling effect, with canopy density emerging as a primary factor with a variance of 87.1% (R² = 0.871). Notably, canopy density of more than 80% demonstrates a marked PCII exceeding 1.0 °C. Additionally, other vegetation attributes, tree basal area (R² = 0.868), tree height (R² = 0.784), DBH (R² = 0.757), and stem density (R² = 0.717), exhibit a significant positive correlation with PCII, following canopy density in descending order. Furthermore, park composition analysis reveals that higher water and green cover contribute to maximizing PCII, underscoring the importance of reducing impervious cover in urban park design. These findings provide valuable insights for urban planners in facilitating the development of more effective urban park designs aimed at maximizing cooling effects, promoting sustainable urban development, and contributing to the achievement of SDG 11 and SDG 13. Full article

Introduction: Twelve-lead electrocardiography (ECG) remains an essential diagnostic tool for patients presenting with chest pain. Timely recognition of specific electrocardiographic patterns is critical for guiding reperfusion strategies and predicting adverse outcomes. Among these, Wellens’ pattern is a high-risk marker of critical left anterior descending (LAD) artery stenosis and an impending anterior myocardial infarction. Although typically described in clinically stable patients without heart failure, its occurrence in the setting of acute decompensation is rare. Case Report: We report the case of a 66-year-old male with hypertension, obesity, and active smoking who presented with exertional chest pain, dyspnea, and signs of acute heart failure. Initial ECG revealed biphasic T waves in V2–V4, consistent with type A Wellens’ pattern. Laboratory evaluation demonstrated elevated troponin I, while point-of-care ultrasound (POCUS) identified systolic and diastolic dysfunction, lateral wall hypokinesia, pericardial effusion, and cardiogenic pulmonary edema. The patient received acute management with antiplatelet therapy, statins, diuretics, and anticoagulation, followed by referral for coronary angiography. This revealed critical stenosis (>90%) of the proximal LAD, successfully treated with percutaneous coronary intervention and drug-eluting stent implantation. The in-hospital course was uneventful, and guideline-directed medical therapy was optimized at discharge, including dual antiplatelet therapy, beta-blocker, renin–angiotensin system inhibitor, and SGLT2 inhibitor. Conclusions: This case highlights the need for early recognition of Wellens’ pattern, even in atypical contexts such as acute heart failure. Integrating ECG interpretation with bedside POCUS facilitated diagnostic accuracy and guided an early invasive strategy, preventing extensive myocardial infarction. In resource-limited settings, strengthening frontline diagnostic capabilities and referral networks is crucial to improving patient outcomes. Full article

The supply–demand network facilitates regional sustainable development by optimizing resource flows and allocation within the Water–Energy–Food system. However, few studies have constructed such networks from a Water–Energy–Food Nexus (WEF Nexus) supply–demand perspective, and the key driving factors influencing network formation, along with their underlying mechanisms, remain poorly understood. To bridge this gap, we propose a new framework for constructing WEF Nexus supply–demand networks via explainable artificial intelligence (EAI). Taking the Bohai Rim urban agglomeration as an example, we identified the key factors affecting the long-term supply and demand of the WEF Nexus and their mechanisms using the XGBoost-SHAP model. By quantifying the magnitude and direction of these factors’ influences, we constructed supply–demand networks and further developed optimization strategies that consider complex factor interactions and distinct thresholds. Key findings include: (1) Identification of 114 stable supply sources and 128 chronic deficit sources, forming 472 high-efficiency and 296 standard supply–demand corridors, with 6 major supply potential zones delineated. (2) Precipitation, vegetation coverage, human activity intensity, cropland distribution, and temperature emerged as primary determinants in descending order of importance. (3) Synergistic analysis revealed significant negative interactions between human activity and precipitation/vegetation, but positive correlation with temperature, with distinct nonlinear thresholds across zones. Based on these findings, we proposed a differentiated optimization strategy. Our study constructs a supply–demand network from the perspective of the WEF Nexus and highlights the importance of threshold effects and interactions among key factors in the construction and optimization of the network. The research results are also applicable to other urban agglomerations facing similar challenges. Full article

This article examines the current statutory care and protection landscape in Aotearoa New Zealand (Aotearoa), focusing on the operations of Waikato-Tainui, a post-treaty settlement entity operating on behalf of the Waikato tribe (iwi), within this complex colonial context to safeguard and nurture mokopuna (descendants) and whaanau (families). Waikato-Tainui supports indigenous mokopuna within a fundamentally flawed settler-colonial care and protection system while concurrently reimagining an indigenous-led model rooted in ancestral wisdom and knowledge systems. Mokopuna Ora (Thriving descendants) is an indigenous whaanau-led and mokopuna-centred care and protection initiative that has been piloted, tested, researched, evaluated, and expanded over the past eleven years within the current settler colonial system. Drawing from deep empirical ancestral wisdom, the authors reimagine a new approach, building a roadmap for mokopuna and whaanau success. Ki Tua o Ngaku Mokopuna is presented as a cultural practice framework encapsulating Waikato ancestral wisdom and knowledge. While still in its early implementation stages, its development has been generations in the making, belonging to Waikato paa (communal meeting places) and hapuu (sub-tribes). Beyond a tool for frontline staff, this framework offers a vision, measures of success, and standards of excellence to inform theory and practice. This work addresses continuous indigenous resistance against negative colonial impacts, reflecting a shared indigenous experience and system of care and protection. In contemporary Aotearoa, the neo-colonial challenge is exacerbated by the current right-wing coalition Government and its ideological stance. The swift and extensive legislative reforms driven by harmful racist ideology are unprecedented, facilitating the exploitation of people, Papatuuaanuku (the earth mother), and te taiao (the natural world) for corporate gain and profit. Maaori tribes, organisations, sub-tribes, families, and individuals are actively countering these racist ideologies, legislations, strategies, policies, funding decisions, and operational practices. This ongoing colonial violence is met with the strength of ancestral knowledge and wisdom, envisioning a future where mokopuna thrive. The framework represents indigenous love, growth, prosperity, and abundance amidst enduring colonial harm and ideological warfare. Full article

Background: Severe hypoglycemia (SH) is a critical complication in children and adolescents with type 1 diabetes (T1D), associated with cognitive impairment, coma, and significant psychosocial burden. Despite advances in glucose monitoring, predicting SH remains challenging, as most models focus on milder hypoglycemic events. Objective: To develop a machine learning model for early prediction of SH using continuous glucose monitoring (CGM) data in children and adolescent T1D patients. Methodology: This retrospective study analyzed CGM data from 67 patients (37 SH episodes, 1430 non-SH segments). Glycemic curves were segmented into 5-day windows, and 21 features were extracted, including glycemic mean, variability, time below range (TBR < 60 mg/dL), and PCA components of glucose trends. A support vector machine (SVM) model was trained using repeated cross-validation to predict SH 15 min before onset. Model performance was evaluated using sensitivity, specificity, balanced classification rate (BCR), and area under the ROC curve (AUC). Results: The model achieved robust performance, with a median AUC of 90% (IQR: 87–93%) and median BCR of 84% (IQR: 80–89%). Sensitivity and specificity exceeded 80%, demonstrating reliable detection of impending SH. However, the positive predictive value (PPV) was low (12%), with false alarms frequently triggered during descending glucose trends or near-hypoglycemic values (end glucose <54 mg/dL). SH episodes were stratified into two subgroups: group 1 (<45 mg/dL, n = 26) and group 2 (>52 mg/dL, n = 15). Notably, false alarms occurred at a median interval of 25 days, minimizing alarm fatigue. Conclusions: These findings confirm the feasibility of SH prediction in clinical practice, prioritizing high-risk events over milder hypoglycemia. By alerting patients and medical teams early on, this tool could facilitate individualized treatment adjustments, reduce the risk of serious hypoglycemic events, and thus contribute to more personalized management of pediatric diabetes, while improving patients’ quality of life. Full article

Continuous blood pressure (BP) monitoring provides valuable insight into the body’s dynamic cardiovascular regulation across various physiological states such as physical activity, emotional stress, postural changes, and sleep. Continuous BP monitoring captures different variations in systolic and diastolic pressures, reflecting autonomic nervous system activity, vascular compliance, and circadian rhythms. This enables early identification of abnormal BP trends and allows for timely diagnosis and interventions to reduce the risk of cardiovascular diseases (CVDs) such as hypertension, stroke, heart failure, and chronic kidney disease as well as chronic stress or anxiety disorders. To facilitate continuous BP monitoring, we propose an AI-powered estimation framework. The proposed framework first uses an expert-driven feature engineering approach that systematically extracts physiological features from photoplethysmogram (PPG)-based arterial pulse waveforms (APWs). Extracted features include pulse rate, ascending/descending times, pulse width, slopes, intensity variations, and waveform areas. These features are fused with demographic data (age, gender, height, weight, BMI) to enhance model robustness and accuracy across diverse populations. The framework utilizes a Tab-Transformer to learn rich feature embeddings, which are then processed through an ensemble machine learning framework consisting of CatBoost, XGBoost, and LightGBM. Evaluated on a dataset of 1000 subjects, the model achieves Mean Absolute Errors (MAE) of 3.87 mmHg (SBP) and 2.50 mmHg (DBP), meeting British Hypertension Society (BHS) Grade A and Association for the Advancement of Medical Instrumentation (AAMI) standards. The proposed architecture advances non-invasive, AI-driven solutions for dynamic cardiovascular health monitoring. Full article