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Safety of íntravitreal panitumumab combined with intravitreal ranibizumab in rabbits
Purpose To examine the safety of intravitreally applied epidermal growth factor (EGF) receptor antibody panitumumab combined with intravitreally injected vascular endothelial growth factor (VEGF) antibody ranibizumab in rabbits. Methods The experimental study included 8 male rabbits (age: 2−3 months; weight: 2.5–2.6 kg). The right eyes received three intravitreal injections of panitumumab (1 mg in 0.10 mL) combined with intravitreal injections of ranibizumab (0.5 mg in 0.05 mL) in intervals of 4 weeks, while the left eyes received three double intravitreal injections of Ringer´s solution (0.10 mL and 0.05mL). At baseline, at the time points of the re-injections, and at 2 weeks and at 6 weeks after the last injection, the animals were examined by fundus photography and optical coherence tomography (OCT). At study end at 2 weeks after the last injection for 4 animals (total study duration: 10 weeks) or at 6 weeks after the last injection for the remaining 4 rabbits (total study duration: 14 weeks), the animals were sacrificed and the eyes were histomorphometrically examined. Results The right eyes (study eyes) and left eyes (control eyes) did not differ significantly in cell count of the retinal ganglion cell layer (8.5 ± 8.3 cells per 150µm versus 4.5 ± 3.3 cells; P = 0.04), inner nuclear layer (33.1 ± 14.0 cells versus 49.0 ± 22.3 cells; P = 0.04) and outer nuclear layer (133.7 ± 50.0 cells versus 171.3 ± 75.3 cells; P = 0.07) nor in mean thickness of the ganglion cell layer (31.8 ± 34.4µm versus 24.3 ± 15.2µm; P = 0.15), inner plexiform layer (32.4 ± 48.2µm versus 25.6 ± 11.2µm; P = 0.22), inner nuclear layer (26.6 ± 14.0µm versus 26.7 ± 10.2µm; P = 0.43), outer plexiform layer (6.6 ± 3.7µm versus 6.8 ± 2.0µm; P = 0.07), outer nuclear layer (32.6 ± 16.1µm versus 30.6 ± 11.8 µm; P = 0.82) and of total retina (157.7 ± 99.4µm versus 152.0 ± 60.7µm; P = 0.34). Apoptotic cells were not detected in either group. Mean IOP did not differ significantly between the right eyes (study eyes) and the left eyes (control eyes). Intravital signs of intraocular toxicity were not detected. Conclusions Repeatedly intraocularly applied panitumumab combined with ranibizumab was intraocularly well tolerated and did not differ in the ocular reaction from intravitreal injections of Ringer´s solution.
Manganese (III) meso-tetrakis(4-nitrophenyl) porphyrin sensitizes TiO₂ nanoparticles into visible region via a pyridyl linker for degradation of organic dyes
Optimizing the preparation of labeled N-glycans for rapid, simplified, and high-precision analysis
Glycan structures hold promise as biomarkers for the early detection of diseases, owing to their sensitive reflection of cellular states. However, glycan analysis remains complex and time-consuming, and the use of hazardous chemicals in traditional hydrazinolysis methods presents a significant barrier to broader application and cross-disciplinary research. To enable efficient glycan biomarker discovery, we aimed to develop a simple and accurate N -glycan analysis method capable of high-throughput sample processing. A key feature of this study is the use of pyridylamination, a fluorescent labeling technique that enables high isomer separation efficiency in reversed-phase LC/MS. After comparing various methods for N -glycan release and purification, we identified Rapid PNGase F (New England Biolabs) and BlotGlyco (Sumitomo Bakelite) as optimal for this application. To improve accuracy by reducing artifact formation, the BlotGlyco protocol was modified from the manufacturer’s original instructions. Using this optimized workflow, we successfully analyzed human serum, human urine, and CHO-K1 membrane fractions, demonstrating that distinct glycan structures in each sample type could be effectively separated and quantified. This work supports the broader adoption of glycan analysis across diverse research fields.
Automatic crack detection in civil infrastructure based on a hybrid fine tuned MnasNet and adaptive patching
Assessment of the impact of the new blister packaging of Biktarvy® (B/F/TAF) on treatment satisfaction of people living with HIV
Background Antiretroviral therapy (ART) is highly effective in people living with HIV (PLHIV), but its success depends on treatment satisfaction and adherence. A determinant of satisfaction regards how the medication is delivered to the patient, namely how it is contained (e.g., bottles, blisters, etc). A new packaging of Biktarvy ® has been introduced as a monthly blister, aiming to improve satisfaction, facilitate traceability of daily medication, portability, and discretion (reducing stigma associated with ART), and, ultimately, enhance adherence. Goals The study’s objective was to assess the impact of changing the packaging of Biktarvy® (B/F/TAF) from a standard pill bottle to a monthly blister with a weekly calendar on therapy satisfaction. Additionally, the association between treatment satisfaction and selected patients’ characteristics (e.g., ART duration) was evaluated. A secondary goal was to characterize the association between the change of packaging on patient’s adherence. Methods This is an observational longitudinal (retrospective and prospective) study with patients following ART for at least six months (ambulatory clinical management) recruited according to a non-probabilistic sequential sampling. Satisfaction was measured at two different moments: at baseline, HIVTSQs were used to assess satisfaction within the previous six months’ use of medication containers (bottles). Six months later, patients filled in the HIVTSQc to assess their perception of satisfaction change with the new packaging (blister). Adherence was assessed by pharmacy medication dispensing at the hospital. Results The study enrolled 105 patients in two selected centers (102 patients completed the study). Patients were significantly more satisfied (HIVTSQc scores) with ART when using the new Biktarvy® blister pack package. Importantly, gains of ART satisfaction were higher among those less satisfied with the bottle packaging. No significant associations were found between HIVTSQc scores and sociodemographic or ART-related variables.
Single-cell analysis indicating CCR8 modulates CD8+ tissue-resident memory T cells to attenuates rejection in transplantation
Associations between serum pigment epithelium-derived factor and physical performance in older women: The Otassha study
Pigment epithelium-derived factor (PEDF) contributes to the beneficial effects of exercise by suppressing cellular senescence in multiple organs. Its expression declines in the skeletal muscle of aged animals, suggesting a role in age-related frailty. To investigate the association between circulating PEDF and physical performance, we analyzed its associations with skeletal muscle mass and mobility in a cohort of older women. A cross-sectional analysis was conducted in 143 community-dwelling females (mean age 77.01 ± 4.16 years). Serum PEDF and body composition were measured, and physical performance was assessed via gait speed, handgrip strength, leg extension strength, and the Five Times Sit-to-Stand test. Serum PEDF levels positively correlated with skeletal muscle mass index (SMI) and gait speed, while no significant correlation was observed between serum PEDF levels and other physical function parameters. These findings suggest that circulating PEDF is associated with skeletal muscle mass and mobility in older adults, warranting further investigation into its potential role as a myokine in humans.
Interannual variability of net primary productivity in the northwest African coastal upwelling system and their relation to Dakar Niños
Abstract The Canary Current upwelling system, located along the northwest African coast between approximately 10ºN and 35ºN, is among the most productive marine ecosystems globally, supporting a rich marine biodiversity. In the southern part (9ºN–18ºN), pronounced interannual variability in net primary production (NPP) is influenced by extreme warm and cold events, known as Dakar Niños and Niñas, respectively. In this study, we analyze the physical mechanisms driving the interannual variability of NPP from 2003 to 2023, using a combination of satellite observations, reanalysis data, and ocean model outputs. Our results indicate that the interannual NPP variability is closely linked to changes in sea surface temperature, with the most pronounced effects occurring during March-April-May, i.e., the main upwelling season. A total of six undocumented extreme coastal low NPP events are identified, nearly all of which are associated with Dakar Niños. These low NPP events are linked to both local and remote forcing. The local forcing is associated with fluctuations of alongshore winds and near-coastal wind stress curl. The remote forcing involves the propagations of coastal trapped waves emanating from the equator and the northern Gulf of Guinea. Part of the local and remote forcing can be associated with large-scale climate modes.
Diagnostic performance of four AI tools in pharmacology MCQs: Accuracy, sensitivity, and specificity
Background The rapid rise of AI in medical and pharmaceutical education has engendered much interest; however, a knowledge gap still exists in the evaluation of performances of these tools in critical academic contexts. Objectives The aim of this study was to assess and compare the performances of four openly accessible AI language tools, Microsoft Copilot, ChatGPT-3.5, Google Gemini, and DeepSeek AI, in responding to pharmacology-related MCQs with regard to diagnostic accuracy, sensitivity, specificity, and reproducibility. Methods A total of 80 MCQs were generated and validated, representing four therapeutic systems: cardiovascular, respiratory, gastrointestinal, and endocrine, including four pharmacological domains: mechanism of action, side effects, pharmacokinetics, and drug-drug interactions. Answers were classified into true/false positives and negatives in order to calculate accuracy, sensitivity, and specificity. After two weeks, a second round of testing was performed with the questions to assess answer reproducibility. Results The top overall performer was Microsoft Copilot: 87.5% accuracy, a sensitivity of 94.6%, and a specificity of 70.8%. It continued to perform strongly across all therapeutic systems, especially in the cardiovascular and respiratory domains, with the highest accuracy in identifying drug mechanisms and side effects. ChatGPT-3.5 performed similarly to Google Gemini (76.3% and 75.0% accuracy, respectively) but with higher sensitivity for ChatGPT-3.5 and higher specificity for Gemini. DeepSeek AI had the lowest accuracy overall (68.8%) and the lowest specificity (29.2%), but the highest consistency of reproducibility (97.5%). The performance of all tools decreased significantly with increasing level of question difficulty (p < 0.05). Conclusion All tools have some value in pharmacology education, but Microsoft Copilot was the most consistently accurate. Limitations in complexity and reproducibility suggest that caution should be exercised in academic and clinical use, particularly given the variability seen with ChatGPT-3.5.
From prediction to sustainability: AI for smart energy management in wastewater treatment plants
Effect of obesity and exercise training on circulating lipids in American Indian adolescents
Childhood dyslipidemia is predictive of future cardiometabolic disease. We determined the impact of obesity (Ob) and an exercise program on lipids in American Indian adolescents. This is a secondary analysis from a previously reported trial designed to determine the impact of financial incentives on exercise behavior in American Indian adolescents who were tested in Southeast Oklahoma between June 2013 and January 2017. We performed a cross-sectional comparison of fasting lipids in participants with Ob (n = 74) and a group with normal weight (NW, N = 39) at baseline prior to the exercise intervention. Measurements were repeated for the Ob group after they completed a 16-week exercise program (n = 53). Compared to the NW group, the Ob group at baseline had higher triglycerides (median [interquartile range]: 1.02 [0.67, 1.73] vs. 0.55 [0.40, 0.74] mmol/L), oxidized high density lipoprotein (HDL) (393 [311, 511] vs. 316 [281, 360] ng/mL), oxidized low density lipoprotein (LDL) (49.3 [38.0, 58.6] vs. 38.8 [29.8, 43.4] U/L), and 4 out of 11 targeted fatty acids measured, while HDL-C (mean ± SD: 0.61 ± 0.18 vs. 0.89 ± 0.20 mmol/L) was lower, all p < 0.001. Fatty acid ratios suggested that hepatic lipid metabolism was altered in the Ob group, with higher stearoyl desaturase, and lower elongase and delta-6 desaturase activities. Aerobic fitness increased 10% in the Ob group but among the lipids measured, only elaidic and myristic acid declined in response to exercise. This study is among the first to report that several plasma lipids were altered in American Indian adolescents with Ob and only minor changes occurred following an exercise program. These findings should be interpreted as exploratory and hypothesis-generating, given the study’s observational and secondary analysis design, but highlight the elevated cardiometabolic disease risk in this understudied population and the need for effective prevention and intervention strategies.
Compressive strength and maturity of UHPC cubes and cylinders: new conversion factors and recommendations for early-age quality control
PERMA-guided multi-topology graph neural networks for cross-cultural student well-being prediction
Student well-being prediction is of great significance for promoting personalized education and preventing mental health problems, but existing methods suffer from limitations including lack of psychological theory guidance, neglect of student relationship modeling, and insufficient cross-cultural adaptability. This study proposes the PERMA-GNN-Transformer model, which innovatively integrates Seligman’s PERMA positive psychology theory with graph neural networks and Transformer architecture. The model achieves the transformation from raw educational data to psychologically meaningful representations through a theory-driven feature embedding mechanism, designs four types of student relationship graphs based on cosine similarity, Euclidean distance, learning styles, and PERMA weighting, and employs a five-head attention mechanism corresponding to the five PERMA dimensions. Experiments on the Western cultural background Lifestyle and Wellbeing Data (n = 12,757) and the East Asian cultural background International Student Mental Health Dataset (n = 268) demonstrate that compared to the optimal baseline methods, our proposed model achieves an 18.9% performance improvement on large-scale datasets and a 27.8% improvement on small-scale datasets, with the PERMA comprehensive evaluation metric reaching 0.792 and passing statistical significance tests at p < 0.01. This research provides a theory-driven, relationship-aware, and culturally adaptive technical solution for student well-being prediction in cross-cultural educational environments.
Evaluation of Lens culinaris germplasm against ascochyta blight by applying phenotyping and defense genes attributes
Prevalence and factors associated with hyperglycemia among children living with HIV on dolutegravir in Kabale district, southwestern Uganda
Background Undiagnosed and poorly managed high blood sugar levels can result in short- and long-term complications in children. Following worldwide introduction of dolutegravir based antiretroviral treatment in 2018, several studies in adult people living with HIV have reported high prevalence of hyperglycemia. Little is known about hyperglycemia in children living with HIV on dolutegravir treatment combinations in Uganda. Objectives To determine the prevalence and factors associated with hyperglycemia in children living with HIV on dolutegravir in Kabale district, southwestern Uganda. Methods In a cross-sectional study, 271 HIV infected children on dolutegravir (DTG) were recruited using proportional to size and simple random sampling methods from 18 health facilities that provide Anti-retroviral therapy (ART) services in Kabale district. HIV infected children aged below 18 years were considered eligible to participate in the study. Data was collected using structured questionnaires. Blood samples were taken for random blood sugar and HbA1C. Data was analyzed using STATA 17.0 for both descriptive and inferential statistics. Logistic regression analysis was done, crude and adjusted odds ratios obtained. Results The prevalence of hyperglycemia was 20.3% (95% CI; 15.9–25.5): Of the children with hyperglycemia, 76% (42/55) had prediabetes and 24% (13/55) had diabetes mellitus. Red meat consumption (AOR:3.52; 95% CI: 1.4–9.0, p = 0.009) and being above 13 years of age (AOR:2.61; 95% CI 1.4–4.87, p = 0.003) were independently associated with hyperglycemia. Conclusion One in every five children with HIV on DTG had hyperglycemia. Among those with hyperglycemia, 24% had diabetes mellitus. Hyperglycemia was more likely to be present in adolescents and those who consumed red meat. Regular monitoring of blood sugar in children living with HIV on DTG is recommended.
Integration of fast charging EV infrastructure with high gain Z-source converters and hybrid optimized MPPT algorithm
Correction: From fishing village to atomic town and present: A grounded theory study
Hybrid local-global representation learning with stochastic Gaussian classification for underwater acoustic target recognition
Vehicle driving area detection and sensor data preprocessing based on deep learning
With the rapid development of intelligent vehicles, it has become particularly important to effectively detect the environment of the vehicle’s driving area. A vehicle driving road recognition algorithm on the basis of an improved bilateral segmentation network is built to address the poor real-time performance and low accuracy in current intelligent vehicle driving area detection methods. Combined with the algorithm, a vehicle driving area detection model based on bilateral segmentation network and data dimensionality reduction is designed. The performance comparison analysis between the recognition algorithm and other algorithms showed that the average frame processed per second and the average recognition time were 68.78FPS and 4.45ms, outperforming the comparison algorithms. The average precision and accuracy were 98.97% and 97.66%, both higher than the comparison models. Finally, the application effect analysis showed that it had good detection performance. The proposed recognition algorithm and detection model have effectiveness and practical value, which can help improve the real-time and accuracy of intelligent vehicle driving area detection, and provide theoretical basis for related research.