Browse Articles

Finite sample size errors in the context of multiple error sources in quantitative medical imaging: An evaluation for breast magnetic resonance diffusion-weighted imaging

Background Selecting appropriate sample sizes in magnetic resonance imaging studies is a complex process that requires to balance statistical rigor with the practical challenges of measuring a large patient population. In this Institutional Review Board approved study, we evaluate the dominant error types (“finite N” errors versus precision errors) for apparent diffusion coefficient (ADC)-based lesion characterization in diffusion-weighted magnetic resonance imaging (DWI) of the female breast in a local dataset and compare our results with current literature. Methods First, in a literature review including 24 published breast DWI studies, the standard error of the area under the receiver operating characteristic curve as a measure of sample size-related errors (finite N errors) was estimated for the reported ADC values and compared to the values, derived from expert readings of a university hospital’s cohort of 171 patients with suspicious breast lesions. Second, precision errors were assessed based on published analyses of the coefficient of variation of ADC values, measured in breast DWI exams. Results Finite N errors were dominant in the in-house study and most of the 24 reviewed studies. The median sample size at which finite N errors and precision errors were equal was determined to be n = 932. Discussion This analysis of dominant error types shows that the required sample sizes for the considered use case are not unreasonably large and that reducing sample sizes may not be justified based on the merits of the conducted analysis. Nonetheless, incorporating dominant error type assessments into future studies may provide valuable insights for optimizing study design and improving methodological rigor.

Comparative effects of natural and functional lipid sources on physicochemical, textural, sensory, and nutritional lipid indices of spreadable processed cheese analogue

Abstract This study evaluated the effects of natural and functional lipid sources, including butter, palm kernel oil, cocoa butter substitute, flaxseed oil, and sunflower oil, on the quality of spreadable processed cheese analogues during 60 days of refrigerated storage. Formulations were standardized to comparable moisture, fat, and protein contents to isolate the effect of lipid type on physicochemical, techno-functional, nutritional, and sensory properties. Lipid source significantly influenced meltability, oil separation, fatty acid composition, nutritional lipid indices, and sensory acceptability. Flaxseed oil markedly improved the lipid profile by reducing saturated fatty acids from 65.06% in the control to 14.98% and increasing unsaturated fatty acids to 85.02%, which reduced the atherogenic and thrombogenic indices from 2.14 to 2.87 to 0.13, respectively. However, this improvement was accompanied by greater oil separation and lower sensory scores, indicating reduced emulsion and sensory stability. Butter and sunflower oil formulations showed the highest sensory acceptability, with scores ranging from 8.1 to 8.9. Overall, the findings demonstrate that lipid selection strongly influences the balance between nutritional improvement, techno-functional stability, and consumer acceptability in spreadable processed cheese analogues.

Protective effects of Fraxinus xanthoxyloides bark in alloxan-induced diabetic rats: A phytochemical and pharmacological approach

Fraxinus xanthoxyloides Wall. ex DC (Family-Oleaceae) is a tiny tree found in arid highlands, often referred to as “Afghan ash”. This study aimed to explore F. xanthoxyloides bark extract as a potential anti-diabetic agent by conducting GC-MS analysis along with in vitro and in vivo studies. F. xanthoxyloides bark methanol extract (FXBM) was fractionated with n-hexane (FXBH), followed by chloroform (FXBC), ethyl acetate (FXBE), and residual aqueous fraction (FXBA). GC-MS and HPLC-MS analysis of the total extract were performed. The inhibitory activities against α-amylase, α-glucosidase, and DPP4 were assessed for the extract and its fractions. The in vivo  study included five groups: control group, diabetic control, groups pretreated with alloxan (150 mg/kg) + glibenclamide (5 mg/kg), group pretreated with alloxan (150 mg/kg) + FXBH (200 mg/kg), and group pretreated with alloxan (150 mg/kg) + FXBH (400 mg/kg). Further, a histopathological investigation was conducted. GC-MS analysis of FXBM revealed the presence of 17 compounds predominated by esters (17.9%), polyols (16.35%), and O -glycosides (12.24%). Among all extract/fractions, FXBH showed maximum α-amylase, α-glucosidase, and DPP4 inhibition when compared to acarbose and berberine, respectively. It also achieved the highest glucose uptake among all extract/fractions when compared with metformin. HPLC-DAD analysis showed the presence of gallic acid (3.29 µg/mg), catechin (4.23 µg/mg), caffeic acid (6.05 µg/mg), ferulic acid (2.99 µg/mg), and quercetin (6.4 µg/mg). FXBH-treated rats showed a significant increase in body weight and reduced blood glucose levels ( p  < 0.05) from days 1–30. The biochemical parameters like triglyceride, low-density lipoprotein, cholesterol, lipase, amylase, C-reactive protein, alanine aminotransferase, aspartate aminotransferase, creatinine, HbA1c, and urea were decreased, while high-density lipoprotein was elevated, compared to diabetic control. Histopathological studies demonstrated restoration of pancreatic β-cells. In conclusion, F. xanthoxyloides bark extract exhibited potential antidiabetic effects; meanwhile, further studies are recommended to characterize the pharmacodynamics, pharmacokinetics, and synergistic effects with standard drugs.

Photo-activated charge transport and exciton dynamics in Cs₂NaInCl₆ double perovskite

Abstract On account of their environmentally-benign composition and structural stability, lead-free halide double perovskites have drawn increasing attention. Even though the charge-transport behavior of Cs₂NaInCl₆, one of these perovskites, remains poorly understood under illumination, it shows strong self-trapped exciton (STE) emission. Through a combined optical and electrical approach, this work investigates the interplay between electrical transport and exciton dynamics. With a wide bandgap and intrinsic STE-mediated blue emission, a highly crystalline cubic phase is confirmed by the optical and structural analyses. Multi-timescale photoinduced relaxation dynamics associated with recombination processes, lattice relaxation and exciton localization are inferred primarily from TRPL measurements and qualitatively supported by complementary transient absorption observations. Current–voltage measurements, dielectric analysis and complementary impedance spectroscopy evidence that illumination significantly reduces bulk resistance, enhances dielectric polarization and induces persistent photoconductivity. While the optical response is governed by STEs, the results indicate that photo-generated carriers dominate charge transport with an indirect influence of exciton dynamics through trap-state modulation. New insight into the optoelectronic functionality of lead-free double perovskites is provided through a physically-consistent framework proposed to correlate macroscopic transport properties with microscopic excitonic behavior.

Reconstruction of a segmental bone defect using vascularized tissue-engineered bone substitutes: An animal study

Background Repairing large segmental bone defects remains a major challenge in orthopedics, with conventional autografting and allografting limited by donor shortages and high complication rates. Tissue-engineered bone substitutes have emerged as a potential solution. This study aimed to assess the vascular regeneration of dual-vascularized tissue-engineered bone substitutes in the reconstruction of large segmental bone defects in rabbits. Method Demineralized bone matrix (DBM) was used as a scaffold, with endothelial progenitor cells (EPCs) seeded onto it. A vascular channel was created within the DBM-EPCs composite scaffold, and the radial artery was implanted into this channel. New Zealand white rabbits were used to create a 15-mm critical-sized rabbit radial bone defect model, with animals divided into four groups: DBM, DBM+EPCs, DBM+Vascular Bundle,and DBM+EPCs+Vascular Bundle (n = 9 per group).X-ray examinations,gross morphological observations,and CD31 immunofluorescence staining were conducted at 4, 8,and 12 weeks post-surgery. Micro-CT was used to reconstruct the three-dimensional structures of the defects after 12 weeks. Results The DBM+EPCs+Vascular Bundle group demonstrated the most significant bone regeneration and vascularization across all time points.X-ray,gross morphology, Micro-CT analysis,HE staining,and CD31 immunofluorescence staining all revealed superior bone regeneration and vascular density in this group compared to the others. Conclusions In conclusion, the dual vascularization strategy significantly enhanced bone regeneration and angiogenesis in the reconstruction of large bone defects. This approach has potential clinical applications for repairing critical-sized bone defects, particularly in anatomical regions with multiple arterial supplies such as the upper limbs and lower legs.

Deep learning-based intelligent diagnosis and adaptive training system for university english oral proficiency

Abstract The development of oral English proficiency among university students remains constrained by limitations in traditional assessment approaches and the scarcity of personalized training resources. This study proposes an intelligent diagnosis and adaptive training system integrating deep learning technologies with multidimensional oral proficiency assessment theory. The diagnostic component employs a multi-task learning framework combining CNN-LSTM architectures with attention-based multimodal fusion to simultaneously evaluate pronunciation accuracy, fluency, vocabulary-grammar complexity, and content coherence from continuous speech samples. The adaptive training component utilizes reinforcement learning to optimize personalized practice recommendation sequences based on dynamically tracked learner competence states. Experimental validation on a corpus of 4,374 recordings from 486 university students, using a strict speaker-independent data partitioning protocol, demonstrates that the diagnostic model achieves correlation coefficients of 0.887, 0.862, 0.824, and 0.793 with human expert ratings across the four assessment dimensions respectively. Controlled training experiments over eight weeks reveal that learners receiving reinforcement learning-optimized content sequencing attain normalized learning gains approximately 2.2 times higher than those following fixed curricula (Cohen’s d = 1.34, 95% CI [0.87, 1.81]), while maintaining stronger engagement throughout the training period. These findings provide preliminary evidence supporting the potential of the proposed framework for scalable, individualized oral English instruction in higher education contexts, though further validation across broader populations and longer time periods is warranted.

Correction: Mammographic Assessment of a Geographically Defined Population at a Mastology Referral Hospital in São Paulo Brazil

A smaller and more efficient one-hot encoding for QUBO

Preschool and primary school teachers’ attitudes toward students with type 1 diabetes: A cross-sectional study

Introduction Type 1 diabetes mellitus (T1DM) is the most common chronic endocrine disorder in childhood, making teachers key agents in ensuring a safe school environment. The main objective of this study was to evaluate the attitudes and prejudices of teachers at Public Early Childhood and Primary Education Centres (ECPECs) in the municipality of San Bartolomé de Tirajana (SBTGC), on the island of Gran Canaria (Canary Islands, Spain), regarding the care of students with T1DM. Materials and methods A descriptive cross-sectional study was conducted. The target population consisted of 264 teachers from seven ECPECs schools in the municipality of SBTGC, Gran Canaria. Data collection was carried out using the validated instrument Teacher Negative Attitudes Index toward the Care of Students with Type 1 Diabetes Mellitus (INAPAD-18) , which allowed for the evaluation of teachers’ attitudes and provided an answer to the study’s main objective. The research was approved by the Research and Drug Ethics Committee (CEIm) of Las Palmas. Results The final sample consisted of 126 participants, representing a participation rate of 47.72%, which did not reach the size required for statistical representativeness. A total of 15.87% of teachers reported currently having students diagnosed with T1DM. The mean number of years of experience working with students with this condition was 3.77 years [0–35years]. A marked gender disparity was observed, with a predominance of women (84.12%). The mean score obtained on the INAPAD-18 questionnaire was 47.02 (range: 18–90). In this instrument, lower scores indicate more favourable attitudes toward the care of students with T1DM. Although male participants showed more favourable attitudes compared to their women, this difference was not statistically significant (p > 0.05). Discussion/Conclusion The results indicate generally favourable attitudes, with moderately low INAPAD-18 scores. However, slight deficiencies were observed in teachers’ training and perception, consistent with findings from previous similar studies. The ECPEC schools Juan Grande and Las Dunas stood out for demonstrating the most positive attitudes. It is necessary for educational institutions to implement specific measures aimed at teacher training in order to improve attitudes and ensure appropriate attention to the needs of students with T1DM.

Polyclonal selection of immune checkpoint mutations in thyroid autoimmunity

Abstract Our immune system contains multiple checkpoints to prevent the activation of self-reactive lymphocytes. How some lymphocytes escape these constraints to cause autoimmune disease remains poorly understood. A long-standing hypothesis posits that somatic mutations in immune regulatory genes may enable self-reactive lymphocytes to bypass tolerance checkpoints 1–3 , but testing this has been challenging owing to technical limitations. Here we used whole-exome and targeted NanoSeq 4,5 , an accurate single-molecule DNA sequencing protocol, to comprehensively search for driver mutations in autoimmune thyroid disease. This showed many B cell clones convergently acquiring loss-of-function mutations in the key immune checkpoint genes TNFRSF14 (also known as  HVEM ) and CD274 (which encodes PD-L1), as well as less frequent mutations in other immune genes. In highly inflamed biopsies, we detected tens to hundreds of independent immune checkpoint mutant clones. Laser microdissection, methylation sequencing, spatial transcriptomics, immunostaining, single-nucleus DNA sequencing and antibody synthesis localized these mutations to B cells, confirmed some to be self-reactive and identified clones carrying multiple hits. We found widespread TNFRSF14 biallelic loss, and clones with as many as 4–6 driver mutations. While each clone accounts for a small fraction of cells (typically less than 1%), the myriad mutant clones in each donor amounted to a substantial fraction of B cells harbouring driver mutations. Our results support the hypothesis that somatic mutations in autoimmune lymphocytes may allow them to escape tolerance constraints through a polyclonal cascade of somatic evolution, providing insights into the molecular basis of autoimmune disease.

Toward energy-efficient sour gas treatment: exergy-based modeling and response surface methodology optimization of a diethanolamine absorption process

Deep learning-based arterial waveform analysis for predicting postoperative cerebrovascular events in pediatric patients with Moyamoya disease

Background Postoperative cerebrovascular events, including transient ischemic attacks, infarctions, and hemorrhages, remain a significant concern in pediatric patients with Moyamoya disease (MMD)undergoing surgical revascularization. This study aimed to develop an explainable deep learning-based classification model using intraoperative arterial blood pressure (ABP) waveform analysis for postoperative cerebrovascular events in pediatric patients undergoing surgery for MMD, with exploratory analysis of associated waveform-derived physiologic features. Methods This retrospective study included 181 pediatric patients (≤18 years) who underwent revascularization surgery for MMD, with an independent temporal holdout cohort of 79 patients reserved for validation. ABP signals were preprocessed using detrending, pulse segmentation, and normalization, then converted into image representations for deep learning classification. Various convolutional neural network (CNN) models, including ResNet50, ResNet34, DenseNet121, VGG16, and VGG19, were evaluated against Vision Transformer (ViT) architectures. Multiple image transformation methods were tested, and Grad-CAM analysis and statistical comparisons of waveform-derived physiologic features were conducted between patients with and without postoperative cerebrovascular events. Results The optimal model configuration achieved the best performance using raw pulse waveforms with three consecutive pulses per image. CNN-based models outperformed ViT-based models, with the highest internal classification performance observed using raw pulse waveforms (AUROC = 0.772, SD = 0.070).In the independent temporal validation cohort, the model achieved an AUROC of 0.738 ± 0.011 at the patient level. Grad-CAM visualization highlighted the diastolic runoff phase as a region of interest for classification. Four waveform-derived features related to arterial compliance were significantly associated with postoperative cerebrovascular events (p < 0.05). Conclusions In this study, CNN-based deep learning models demonstrated the feasibility of predicting postoperative cerebrovascular events from intraoperative ABP waveforms, with diastolic runoff dynamics emerging as a potentially relevant physiologic pattern. These findings are exploratory and require prospective multi-center validation before clinical application.

Comparative study of granular computing and RKCCA-based feature fusion for early lithium-ion battery RUL estimation

Trends in the burden of sickle cell disorders in Sierra Leone, 1990–2023: An analysis of Global Burden of Disease Study 2023 estimates

Background Sickle cell disease is a major cause of childhood mortality in sub-Saharan Africa, yet country-specific burden estimates for high-prevalence settings in West Africa remain limited. Objective To describe Global Burden of Disease (GBD) 2023 modeled estimates of sickle cell disorders burden in Sierra Leone from 1990 through 2023, including temporal trends, age and sex patterns, and demographic contributors to mortality change. Methods We analyzed GBD 2023 modeled estimates for sickle cell disorders in Sierra Leone, including prevalence, deaths, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) as absolute counts and age-standardized rates. Temporal trends in age-standardized rates were assessed using log-linear regression. The Kitagawa-Das Gupta decomposition partitioned the change in estimated deaths into population growth, age-structure change, and age-specific mortality-rate changes. Results Estimated prevalent cases increased from 48,689 (95% UI, 42,588−56,140) in 1990–90,498 (78,126−105,815) in 2023. Estimated deaths increased from 408 (288−579) to 635 (438−862), while the estimated age-standardized mortality rate declined from 10.2 to 7.9 per 100,000 (APC, −0.46%; 95% CI, −0.64 to −0.29). Decomposition attributed 159.6% of the net increase in deaths to population growth, −7.8% to age-structure change, and −51.8% to lower modeled age-specific rates. In 2023, an estimated 49.5% of deaths occurred before age 20. Point estimates suggested possible higher male mortality, but uncertainty intervals were wide and compatible with no clear sex difference. Conclusions GBD estimates suggest that Sierra Leone’s absolute burden of sickle cell disorders increased substantially between 1990 and 2023, while modeled rates declined. These modeled estimates highlight a growing absolute burden and persistent early-life mortality, supporting the need for improved surveillance, newborn screening, infection prophylaxis, hydroxyurea access, and longitudinal care systems.

Optimisation of seaweed-based biostimulant application to improve bell pepper yield and quality using Topsis-Shannon entropy

Eosinophil count trajectories are associated with the prognosis of acute myocardial infarction patients: Insights from ICU data analysis

Objective Previous clinical studies have demonstrated conflicting evidence regarding the relationship between eosinophil (EOS) count and adverse outcomes in acute myocardial infarction (AMI). This study aimed to evaluate the impact of EOS count trajectories during ICU admission on mortality and the incidence of acute kidney injury (AKI) in AMI patients. Methods A total of 1,493 critically ill AMI patients from the MIMIC-IV database were enrolled. Primary outcomes included 28-day and 1-year mortality, and secondary outcomes encompassed severe AKI incidence and ICU mortality. Group-based trajectory modeling (GBTM) was applied to identify distinct EOS count trajectories. Survival differences were assessed by Kaplan-Meier curves and log-rank tests. Associations between the EOS trajectory and mortality were evaluated using multivariable logistic/Cox regression. Furthermore, mediation analysis was conducted to investigate the potential mediating effect of AKI on mortality. Results Three EOS trajectories were identified: Trajectory1 (stable-low), Trajectory2 (low-level steady rise), and Trajectory3 (medium-level rapid rise). Compared to Trajectory1, both the Trajectory2 (HR = 0.68, 95% CI: 0.47–0.99) and Trajectory3 (HR = 0.63, 95% CI: 0.50–0.79) showed significant reductions in 28-day mortality risk. The Trajectory3 also exhibited a 34% lower 1-year mortality risk compared to Trajectory1 (HR = 0.72, 95% CI: 0.60–0.86). Mediation analysis revealed that AKI partially mediated the association between EOS trajectories and 28-day mortality. Conclusion EOS count trajectory independently predicts both short- and long-term mortality in critically ill AMI patients, establishing its role as a reliable marker for risk stratification and prognostic evaluation.

Sustainable synchronized spectrofluorimetric determination of remdesivir and baricitinib: a first-derivative synchronous approach with multi-color and GLANCE assessment

Abstract This study presents a novel, rapid, and sensitive spectrofluorometric method for the simultaneous quantification of remdesivir and baricitinib, for the treatment of hospitalized patients with Covid-19 pneumonia. The method utilizes a first-order derivative synchronous spectrofluorimetry technique, with measurements taken at 388 nm for remdesivir and 383 nm for baricitinib, using a wavelength interval (Δλ) of 140 nm. A linear correlation (r = 0.9999) was established between derivative signal amplitudes and concentration across the ranges of 25.0–2000.0 ng /mL for both analytes. The method was validated per ICH guidelines including accuracy and precision. The developed method also successfully quantified the target drugs individually, in laboratory prepared mixtures and laboratory-prepared dosage form, without interference from each other or from excipients. The method enabled the simultaneous analysis of these drugs in spiked human plasma at concentrations relevant to higher therapeutic levels and combination therapy studies, yielding results with acceptable precision (standard deviation ≤ 1.48). The method’s environmental sustainability and practical applicability were evaluated to confirm its overall utility for the analysis of these pharmaceuticals.

A multicenter, randomized, parallel-group confirmatory study protocol to evaluate the efficacy of Soft Protector CPC, a novel oral mucosal protectant, in preventing oral mucositis and alleviating pain in patients with breast cancer

Oral mucositis is a frequent and debilitating adverse event observed in patients undergoing chemotherapy or radiotherapy. Current management strategies are limited in duration, require frequent application, and fail to address the mechanical irritation from teeth. A novel device, Soft Protector CPC, was developed to overcome these limitations. This multicenter, randomized, two-arm, open-label, confirmatory trial aims to evaluate the efficacy and safety of Soft Protector CPC in patients with breast cancer undergoing chemotherapy. A total of 154 participants will be randomly assigned in a 1:1 ratio to receive either oral care with Soft Protector CPC or oral care alone. The primary endpoint will be oral mucositis as assessed according to the Common Terminology Criteria for Adverse Events (CTCAE) v3.0 during the comparative treatment period. The secondary endpoints will include CTCAE v3.0 during the continuous treatment period, oral mucositis, pain (CTCAE v5.0), quality of life (Patient Reported Outcomes-CTCAE version 1.0 [PRO-CTCAE v1.0], the 15-item oral health questionnaire of the European Organization For Research And Treatment Of Cancer [EORTC QLQ-OH15], and the pain Numeric Rating Scale), onset and site of mucositis, completion of chemotherapy, use of rescue medications, technical feasibility, and patient preference. The safety endpoints will include adverse events, device malfunction, and laboratory tests. This trial is expected to establish the clinical utility of the Soft Protector CPC for the prevention and management of oral mucositis, with the potential to improve the patients’ quality of life and adherence to cancer therapy. This study was approved by the Clinical Research Review Board and registered with the Japan Registry of Clinical Trials, jRCTs062250005, on April 18, 2025.

Bacteriophage-mediated restoration of epithelial integrity, DNA damage response, and transcriptomic homeostasis in colon organoids exposed to ETBF and pks + E. coli

Epidemiological patterns and healthcare utilization among malaria patients in Sorong City, Papua, Indonesia: A cross-sectional analysis of national surveillance data

Objectives Malaria remains endemic in Indonesia, with high transmission rates observed in the Papua region. Routine surveillance data are essential to inform service delivery and optimize case management. This cross-sectional study examined malaria cases in Sorong City in 2024 reported through Indonesia’s national surveillance system to describe malaria burden across healthcare facilities, diagnostic and treatment practices, and predictors of hospital attendance and hospitalization. Methods All laboratory-confirmed malaria cases were analyzed, including demographics, malaria diagnosis, disease severity, treatment received, and hospitalization data. Descriptive statistics and logistic regression were used to identify determinants of hospital attendance and inpatient admission. Results Among 3,953 malaria cases, most patients were ≥15 years old (65.9%), males (59.4%), Papuan (54.2%), students (36.6%), and living in highly endemic areas (78%). Community health centers reported most cases (61.7%). Microscopy was the primary diagnostic tool (70.1%). Plasmodium vivax was the predominant species (65.5%), and nearly all infections were uncomplicated (99.9%). Notably, nearly 21% of patients received non-standard antimalarial regimens. Predictors of hospital attendance include older age (aOR: 1.02; 95% CI: 1.00–1.02; p = 0.001), non-Papuans ethnicity (aOR: 1.77; 95%CI: 1.51–2.07; p = 0.001), being housewife (aOR: 1.57; 95%CI: 1.02–2.42; p = 0.041) or student (aOR: 1.56; 95%CI: 1.05–2.31; p = 0.029), and living in moderate- (aOR: 2.01; 95%CI: 1.69–2.40; p = 0.001) or low- (aOR: 4.57; 95%CI: 2.01–10.39; p = 0.001) endemicity areas. Children <15 years were more likely to be hospitalized (aOR 1.9; 95% CI 1.18–3.06; p = 0.009). Conclusions Malaria remains a substantial public health burden, dominated by P. vivax , with community health centers serving as primary care providers. Older individuals were more likely to attend hospital, while younger children had a higher likelihood of hospitalization once diagnosed. Strengthening community-based services, promoting early treatment-seeking among children, and ensuring consistent adherence to national treatment guidelines are critical to reducing severe disease and hospital burden.