Journal of Current Science and Technology

Protecting Forests Through Intelligent Edge Computing: CBAM-UNet for Real-Time Deforestation Detection

Shobha P — Tue, 15 Sep 2026 00:00:00 +0700

The accelerating loss and degradation of forest ecosystems necessitate accurate and efficient monitoring approaches. This study presents a lightweight, attention-enhanced semantic segmentation framework for binary forest canopy segmentation using satellite imagery. The proposed model integrates a U-Net architecture with a MobileNetV2 encoder and a Convolutional Block Attention Module (CBAM) to improve feature representation while maintaining computational efficiency. The model is evaluated on the Bragagnolo Amazon Rainforest dataset for forest-versus-non-forest segmentation. The CBAM-enhanced model achieved a mean Intersection over Union (mIoU) of 0.6339 compared with 0.6282 for the baseline U-Net–MobileNetV2, while maintaining a comparable Dice score (0.6141 vs. 0.6187), indicating more consistent class-wise segmentation. The exported ONNX model sustained approximately 5.9 frames per second on an NVIDIA Jetson Nano while consuming under 80 MB of memory, confirming its feasibility for resource-constrained edge deployment. This work focuses strictly on binary canopy segmentation and provides insights into the trade-offs between accuracy and efficiency in lightweight deep-learning models for remote-sensing applications.

Proactive Maintenance Strategy for Boiler Feed Pumps in Power Plant Industries Using Long Short-Term Memory Autoencoder-Based Anomaly Detection

Habib Muhajir, Toni Prahasto, Achmad Widodo — Tue, 15 Sep 2026 00:00:00 +0700

The boiler feed pump (BFP) plays a crucial role in power plants. As part of a prognostic and health management strategy, deep learning frameworks are currently being developed for anomaly detection to improve reliability. This study proposes a data-driven proactive maintenance framework based on anomaly detection using data from the supervisory control and data acquisition (SCADA) system. This research applied an anomaly detection framework built on a long short-term memory autoencoder (LSTM-AE) to monitor several critical operating parameters, including vibration, bearing temperature, lube oil temperature, and motor winding temperature, in a coal-fired steam power plant in Indonesia. Data collected in 2023 and 2024 were used to train and validate the models. The applied LSTM-AE demonstrated strong reconstruction performance for both training and validation datasets, indicating its ability to learn and reproduce the dominant temporal patterns of normal SCADA behavior. The model was able to highlight deviations from learned normal behavior, which were interpreted as early-stage anomalies. These anomaly indications were subsequently verified through field inspection, which revealed mechanical wear in several critical components, including slight pump shaft bending, excessive clearance in the impeller hub bush, impeller wear ring, balance disc, and balance seat. Although a quantitative comparison with conventional fixed-threshold or statistical baseline methods was not conducted in this study, the results demonstrate the practical feasibility of applying LSTM-AE–based anomaly detection for industrial condition monitoring using SCADA data. The proposed framework shows potential to support proactive maintenance activities, such as inspection prioritization and maintenance scheduling.

Utilization of Waste Silicone Sealant and Aluminium Scraps as Additives in Fly Ash–Based Geopolymer for Lightweight Construction Blocks

Tue, 15 Sep 2026 00:00:00 +0700

This study presents a pathway for using waste silicone sealant (Si-s) and aluminium scraps (Al-s) to produce lightweight geopolymer materials. Fly ash, sodium hydroxide, and sodium silicate were used as the starting materials for geopolymerization. Ground Si-s and Al-s were added to the mixtures, which were then cured for 28 days under ambient conditions (25°C). The structural composition and morphology were analyzed using Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy equipped with energy-dispersive X-ray spectroscopy (SEM–EDS). The results showed that Si-s acted as a dispersed additive in the geopolymer matrix and affected the reaction, possibly because its acidity neutralized the alkaline solution. It also increased the crystallite size to 51.68 nm, compared with 20.25 nm for the control geopolymer. The addition of Al-s produced a porous structure and reduced the crystallite size to 14.94 nm because it reacted with the alkaline solution, generating an exothermic reaction and hydrogen gas. The physical and mechanical properties, including density, apparent porosity, water absorption, compressive strength, and ultrasonic pulse velocity, were evaluated. The proportions of Al-s and Si-s were expressed as parts per hundred mixtures (phm), with the mixture comprising fly ash, NaOH, and Na₂SiO₃ used in the geopolymerization process. The addition of 0.4–0.6 phm Al-s and 40 phm Si-s resulted in geopolymers with densities of 1,292–1,438 kg/m³, apparent porosities of 18.18%–25.87%, and water absorption values of 6.97%–10.15%. The compressive strength ranged from 13.25 to 41.91 ksc, depending on the Si-s content. These geopolymers exhibited physical properties and compressive strengths that complied with the requirements for Type C12 lightweight concrete blocks specified in Thai Industrial Standard TIS 2601-2556. Therefore, waste Si-s and Al-s can be effectively recycled to produce lightweight geopolymer materials with properties suitable for construction applications.

Multidrug Resistant Staphylococci from Environments of Sub-District Health Promoting-Hospitals in Chiang Rai, Thailand

Korakot Chansareewittaya, Sirikarnnapa Krajangcharoensakul — Tue, 15 Sep 2026 00:00:00 +0700

The presence of multidrug resistant (MDR) bacteria in hospital environments poses a major challenge for infection control, given their role as environmental reservoirs. Staphylococcus spp. were the predominant bacteria, accounting for 36.95% of all isolates (126/341), of which 16.67% (21/126) exhibited MDR phenotypes. Accordingly, the present study comprehensively evaluated these 21 MDR isolates to determine their extended antibiotic susceptibility profiles and associated resistance genes. Antibiotic susceptibility was assessed using the disk diffusion method against 12 antibiotics classified into Groups A, B, and C. Polymerase chain reaction was used to detect eight resistance genes: blaZ, mecA1, mecA2, mecC, ermA, ermB, ermC, and aacA-aphD. In group A, all isolates showed resistance to cefoxitin, and high resistance to trimethoprim-sulfamethoxazole, clindamycin (both at 76.19%), and erythromycin (71.43%). The majority (95.24%) of bacteria were methicillin-resistant coagulase-negative staphylococci (MRCoNS), primarily methicillin-resistant Staphylococcus epidermidis (75%) and a small proportion of methicillin-resistant Staphylococcus aureus (4.76%). Most isolates remained sensitive to group B and C antibiotics, such as linezolid, doxycycline, and vancomycin, with limited resistance to rifampin (9.52%), gentamicin (33.33%), ciprofloxacin and moxifloxacin (9.52% each), and chloramphenicol (4.76%). MDR staphylococci isolates showed a high prevalence of diverse resistance genes. Notably, the blaZ and mecA1 genes were common (each found in 90.48% of isolates), whereas ermA and mecC genes were not detected. The ermC gene was present in all isolates while ermB was rare (4.76%). The mecA2 and aacA-aphD genes were detected only in MRCoNS, each occurring in 61.90% of isolates. These findings reveal distinctive local resistance profiles in resource-limited sub-district health promoting-hospitals and underscore the need for continuous surveillance, targeted antimicrobial stewardship, and rigorous environmental cleaning protocols to control MDR staphylococci in these healthcare settings.

Comparative Evaluation of Single and Hybrid Metal Oxide Nanoparticles for Multifunctional Hemp Textiles with Enhanced UV Protection and Self-Cleaning Performance

Tue, 15 Sep 2026 00:00:00 +0700

This study systematically investigated and compared the efficacy of single and hybrid metal oxide nanoparticles (NPs), including TiO₂, ZnO, and SiO₂, and their combinations, in imparting multifunctional properties to hemp fabrics. Despite increasing interest in multifunctional textile finishing, systematic comparative studies on single and hybrid metal oxide NP systems applied to hemp fabrics remain limited. For scalability and industrial applicability, commercial NPs were employed and applied to hemp textiles using a conventional pad-dry-cure method to evaluate wettability, UV protection, and photocatalytic self-cleaning performance. A commercial styrene–acrylic copolymer (SAC) emulsion was employed as a binder to facilitate the incorporation and adhesion of NPs onto the hemp fabric. XRD analysis confirmed the anatase phase of TiO₂, wurtzite structure of ZnO, and the amorphous nature of SiO₂, with crystallite sizes of 19.9, 36.2, and 22.4 nm, respectively. SEM–EDS examinations verified successful NP deposition and improved dispersion in hybrid and ternary systems. Contact angle measurements revealed a progressive increase in surface hydrophobicity from single to hybrid systems, with the ternary TiO₂-ZnO-SiO₂ nanocomposites exhibiting the highest water repellency due to hierarchical micro-nano surface structuring. UV protection was significantly enhanced after NP incorporation. The pristine hemp fabric exhibited moderate protection (UPF≈14), while the ternary nanocomposites achieved excellent protection (UPF 50++) with approximately 98-99% UV blocking, attributed to synergistic UV absorption and scattering effects. Assessment of photocatalytic self-cleaning based on methylene blue (MB) degradation showed superior performance for hemp finished with semiconductor NPs. The ternary nanocomposites exhibited the highest degradation efficiency (≈91%), followed by TiO₂-ZnO (≈89%), attributable to enhanced charge separation, reduced electron-hole recombination, and increased reactive oxygen species (ROS) generation. Overall, hybrid and ternary nanocomposite systems surpassed single oxides, highlighting the essential role of SiO₂ as a dispersion-supporting component. This work presents a practical and scalable approach for developing high-performance, multifunctional hemp textiles suitable for protective, healthcare, and sustainable apparel applications.

Carbon-Based Electrodes from Agricultural Waste: Comparison of Textural and Electrical Properties

Naphatsorn Udompala, Songwuit Chanthee, Malee Santikunaporn — Tue, 15 Sep 2026 00:00:00 +0700

Activated carbon-based electrodes were successfully derived from agri-food residues, namely palmyra palm fibers and apricot stone shells, via activation with potassium hydroxide at 750°C. Palmyra palm fiber activated carbon (PPA) and apricot stone shell activated carbon (ASA) were prepared, while commercial activated carbon (CAC) was used as received. All samples were characterized and electrically evaluated in a comparative study. Characterization results confirmed that ASA and PPA were successfully converted into carbonaceous materials. Scanning electron microscopy revealed a sponge-like porous structure in the PPA sample, whereas one-dimensional channel-like pores were observed in the ASA, and a smooth surface with randomly distributed cracks was observed in the CAC sample. Interestingly, the surface area of the activated carbon electrodes alone did not determine the specific capacitance. Although ASA possessed the highest surface area (1372.9 m² g⁻¹), it exhibited the lowest specific capacitance of 30.5 F g⁻¹at 0.5 A g⁻¹. In contrast, PPA demonstrated the lowest surface area (502.5 m² g⁻¹) but delivered the highest specific capacitance of 47.6 F g^-1 at the same current density. Textural-electrical performance correlation analysis revealed that mesopore content (2-50 nm) has a greater impact on electrical capacitance than the overall specific surface area. Moreover, all carbon electrodes displayed quasi-rectangular cyclic voltammograms, consistent with the characteristic behavior of EDLCs. The PPA-based electrode exhibited excellent rate capability, retaining approximately 88% of its initial capacitance as the current density increased from 0.5 to 5.0 A g⁻¹, indicating its strong potential for practical EDLC applications.

COSHAP: An Explainable AI Framework Integrating Conformal Prediction and SHAP for Uncertainty-Aware Consumer Segmentation

Marsani Asfi, Budi Warsito, Adi Wibowo — Tue, 15 Sep 2026 00:00:00 +0700

Data-driven decision-making in digital marketing is often constrained by the lack of transparency and uncertainty estimation in conventional machine learning models. This study proposes COSHAP (Conformal Segmentation with Hierarchical Attribution Paths), a unified framework that integrates Conformal Prediction (CP) and SHAP to model uncertainty while enhancing interpretability in customer segmentation. Using the Online Retail II dataset, segmentation was performed based on Recency, Frequency, Monetary (RFM), Tenure, and Average Basket Size features using K-Means, which was subsequently approximated using supervised models (Random Forest, XGBoost, Naïve Bayes, and SVM). CP was applied to generate prediction sets with guaranteed statistical coverage, while SHAP analysis was extended by conditioning feature attributions on prediction set membership through Hierarchical Attribution Paths. Experimental results demonstrated that the XGBoost model achieved the highest approximation accuracy of 97.36%. At a 95% confidence level, the framework achieved empirical coverage consistent with the statistical target for the ensemble models, with an average prediction set size close to 1.0, indicating high certainty in the majority of cases. However, a subset of customers at decision boundaries yielded multi-label predictions, accurately reflecting behavioral ambiguity. SHAP analysis identified Recency and Frequency as the primary drivers of segmentation, whereas COSHAP successfully uncovered the push-pull feature dynamics that trigger prediction uncertainty. The COSHAP framework effectively transforms point-based segmentation into a reliable, calibrated, and transparent decision-support system.

Transient Embryotoxicity and Disrupted Forebrain Architecture Following in Ovo Cannabidiol Exposure in Chick Embryo

Tue, 15 Sep 2026 00:00:00 +0700

The increasing prevalence of cannabidiol (CBD) use during pregnancy raises concerns regarding its impact on fetal neurodevelopment. This study examined how the administration of CBD in ovo influences mortality rates, physical development, and the structural arrangement of the forebrain in avian embryos. Fertilized eggs were injected with 10 µM CBD or vehicle control into the yolk sac at Hamburger–Hamilton (HH) stages 7–8 (24 hours of incubation). Embryos were evaluated at Days 3, 6, and 13 using morphological, histological, and molecular analyses. Early exposure significantly reduced survival at Day 3 (79.3% vs. 93.8%, p = 0.041) and accelerated neural tube differentiation, coinciding with a 2.3-fold upregulation of Bone Morphogenetic Protein 4 (BMP-4) (p = 0.009). While survival rates showed a non-significant reduction by Day 6, transient growth retardation was observed. By Day 13, CBD-treated embryos exhibited distinct morphological alterations, including increased egg tooth length (p = 0.023) and brain weight (p = 0.007). Histological examination of the forebrain revealed narrowed ependymal zones, aberrant mesenchymal-like cell infiltration, and significantly reduced neurite extension. These findings suggest that early CBD exposure disrupts neurodevelopmental timing and forebrain architecture, potentially mediated through dysregulated BMP-4 signaling. Although embryos demonstrated somatic resilience, the persistent cellular and structural anomalies highlight the potential neuroteratogenic risks of CBD exposure during early embryogenesis.

Prevalence and Multidimensional Determinants of Mild Cognitive Impairment among Urban-Dwelling Older Adults in Pathum Thani, Thailand: A Cross-Sectional Study

Tue, 15 Sep 2026 00:00:00 +0700

Mild cognitive impairment (MCI) is a stage of cognitive decline beyond normal aging that has not progressed to dementia and is increasingly recognized as a major public health concern worldwide. However, population-based evidence on MCI in urban Thailand remains limited. This cross-sectional study assessed the prevalence of MCI and its multidimensional determinants among older adults in an urban community in Pathum Thani, Thailand. A total of 414 adults aged 60 years or older were recruited using multistage sampling between September and November 2025. Cognitive status was assessed using the Thai Mental State Examination (TMSE; cutoff ≤23, indicating MCI), while depressive symptoms and perceived stress were evaluated using the PHQ-9 and ST-5, respectively. Associations were examined using univariable and multivariable logistic regression analyses. The prevalence of MCI was 35.0%, affecting more than one-third of the participants. Multivariable analysis identified nine factors significantly associated with MCI: older age, lower educational attainment, unemployment, low income, physical inactivity, depression, elevated stress, limited social participation, and lack of engagement in brain-training activities (p < 0.05). Knowledge of MCI was not significantly associated with MCI after adjustment (p > 0.05). These findings highlight the multifactorial nature of MCI in urban settings and emphasize the need for targeted, community-based screening and integrated health-promotion strategies that address modifiable risk factors in Thailand’s rapidly aging population.

Enhancing Wear Resistance and Interfacial Properties of Hardfaced AISI 1050 Steel Utilizing an Austenitic Buffer Layer

Yodnapha Ketmuang, Apichart Chaichawalit — Tue, 15 Sep 2026 00:00:00 +0700

The performance of hardfaced carbon steels is strongly influenced by interfacial integrity and microstructural evolution during welding. This study investigated the effects of an austenitic E309L-16 buffer layer on the microstructure, hardness distribution, and abrasive wear resistance of SMAW-hardfaced AISI 1050 steel. A functionally graded hardfacing architecture incorporating the buffer layer was developed to improve metallurgical compatibility and interfacial stability. Two conditions were examined: direct hardfacing (S1) and buffer-assisted hardfacing (B1). Optical microscopy (OM), scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS), microhardness measurements, and ASTM G65 abrasion testing were conducted. The results showed that direct hardfacing promoted carbon redistribution toward the interface, resulting in a brittle interfacial region and an abrupt hardness transition. In contrast, the E309L-16 buffer layer moderated carbon redistribution, eliminated the interfacial white band, and promoted a more homogeneous microstructure with a gradual hardness profile. The B1 specimen predominantly exhibited lath martensite and demonstrated superior wear resistance despite its slightly lower peak hardness (586 HV compared with 647 HV for S1). The specific wear rate decreased from (10.08 ± 0.43) × 10⁻⁴ mm³/N·m for the base metal to (4.30 ± 0.10) × 10⁻⁴ mm³/N·m for S1 and further to (3.62 ± 0.11) × 10⁻⁴ mm³/N·m for B1. These findings demonstrate that interfacial engineering using an austenitic buffer layer can improve wear resistance and provide practical guidance for designing durable multilayer hardfacing systems.

Work Fatigue and Associated Factors among Wood-Cutting Workers: An Ergonomic Assessment Using the Fatigue Assessment Scale

Agung Kristanto, Farid Ma’ruf, Choirul Bariyah — Tue, 15 Sep 2026 00:00:00 +0700

Work fatigue is a common occupational health problem in labor-intensive industries, particularly among wood-cutting workers exposed to repetitive physical demands and prolonged standing. However, studies integrating subjective fatigue assessment and physiological monitoring in woodworking settings remain limited. Therefore, this study aimed to examine the relationship between individual characteristics and work fatigue among wood-cutting workers in Indonesia. A total of 60 participants, comprising 41 males and 19 females aged 19.17–58.67 years, were included in this cross-sectional study. Data were collected using the Standardized Nordic Questionnaire (SNQ) to screen for musculoskeletal complaints; the Fatigue Assessment Scale (FAS) was applied to measure fatigue levels; and a wearable heart rate monitor recorded physiological responses before, during, and after work. Spearman correlation analysis examined associations between individual characteristics (age, working hours, daily recovery duration, overtime, coffee consumption, exercise frequency, commuting distance, and heart rate) and fatigue scores. The results showed that 40.00%, 48.33%, and 11.67% of workers experienced severe, moderate, and no fatigue, respectively. Significant correlations were found between fatigue levels and age (ρ = 0.267, p = 0.039), daily recovery duration (ρ = –0.265, p = 0.041), and heart rate (ρ = 0.305, p = 0.018). Heart rate showed the strongest association with fatigue, suggesting that cardiovascular strain may be associated with perceived fatigue during wood-cutting activities. Other variables, including working hours, overtime duration, coffee consumption, exercise frequency, and commuting distance, were not significantly associated with fatigue. These findings indicated that physiological workload, worker age, and insufficient recovery periods were important factors associated with work fatigue among wood-cutting workers. The study supported the use of combined subjective and physiological approaches for ergonomic fatigue assessment and workplace fatigue management.

Computational Design Optimization of Internal Ramp Geometry in Side-Port Embryo Transfer Catheters to Minimize Fluid Recirculation and Shear Stress

Abhinat Vairungroj, Punn Pongsawasdi — Tue, 15 Sep 2026 00:00:00 +0700

The success of in vitro fertilization (IVF) relies heavily on non-traumatic embryo delivery. While end-opening catheters provide direct flow, they pose a risk of endometrial injury and embryo displacement due to high-velocity jetting, whereas conventional side-port designs minimize trauma but inherently suffer from fluid stagnation and elevated shear stress. This study aims to resolve this critical hydrodynamic trade-off by proposing a novel 'Flow-Guiding Internal Ramp Architecture' (FGIRA) integrated with an oval lateral aperture to eliminate dead zones while maintaining safe, low-velocity expulsion. Three-dimensional computational fluid dynamics (CFD) simulations were conducted using SolidWorks Flow Simulation based on the finite volume method to solve the Navier–Stokes equations. The study modeled the fluid as a Newtonian standard culture medium at 310.15 K, utilizing a mesh refinement strategy optimized for grid independence to comparatively analyze the hydrodynamic performance of four catheter configurations, focusing on velocity distribution, vorticity, and Wall Shear Stress (WSS). The results demonstrated that the Oval-FGIRA design successfully eliminated fluid recirculation and achieved a maximum WSS of 1.21 Pa within the 0.04 m/s injection speed regime. This value falls well within the physiological safety threshold (< 2 Pa), supported by a stable laminar flow regime (Maximum Local Reynolds Number = 49.95). In conclusion, unlike traditional side-port designs that merely redirect flow at the cost of high shear stress, the Oval-FGIRA establishes a breakthrough. By simultaneously eliminating fluid stagnation and dampening mechanical forces, the synergy between the internal ramp and oval aperture creates a superior hydrodynamic environment that minimizes mechanotransduction-induced cellular damage, offering a paradigm shift in catheter geometry to improve clinical pregnancy rates. However, at the injection velocity of 0.08 m/s, maximum wall shear stress exceeded the safety threshold at 2.10 Pa. Consequently, clinical implementation of the Oval-FGIRA is recommended for slow-to-immediate injection protocols.

Diagnostic Accuracy of Cybersight AI for Glaucoma Detection: Sensitivity, Specificity, and ROC Analysis

Tue, 15 Sep 2026 00:00:00 +0700

Glaucoma is a chronic, progressive optic neuropathy and a leading cause of irreversible blindness worldwide. Early detection is crucial but is often limited by nonspecific clinical signs and the need for specialist expertise. Artificial intelligence (AI), particularly deep learning, has shown promise for glaucoma detection from ophthalmic images. This study independently validated an existing third-party AI tool, Cybersight AI, powered by the Visulytix Pegasus engine, for detecting primary glaucoma. No new algorithm was developed or proposed. A cross-sectional diagnostic accuracy study was conducted on 229 eyes from 121 patients, including 133 eyes with primary glaucoma and 96 controls, at Hue Central Hospital between December 2024 and September 2025. Fundus photographs were analyzed using the Cybersight AI platform, which estimated the vertical cup-to-disc ratio and generated a binary glaucoma referral recommendation. AI outputs were compared with diagnoses established by ophthalmologists using an expert multimodal clinical reference standard. Diagnostic performance was assessed using sensitivity, specificity, positive and negative predictive values, and the area under the receiver operating characteristic curve (AUC). At its default operating point, Cybersight AI achieved 51.9% sensitivity (95% CI 43.5–60.2) and 90.6% specificity (95% CI 83.1–95.0), with an AUC of 0.744 (95% CI 0.682–0.807). Positive and negative predictive values were 88.5% and 57.6%, respectively. The Youden-optimal cut-off was 10%, yielding 60.9% sensitivity and 85.4% specificity. Cybersight AI demonstrated moderate discrimination, high specificity, and modest sensitivity at its default binary setting in this Vietnamese tertiary-care cohort. It may serve as a screening or triage adjunct, although context-specific thresholding and further external validation are required before broad clinical deployment. Limitations include the single-center convenience sample, within-patient clustering, and comparison of a fundus-only index test against a multimodal reference standard. Future studies should prioritize multicenter validation in Vietnamese settings and comparison with expert fundus assessment alone.

Optimization of Extraction and Drying Methods of Low-Grade Mulberry Leaf Tea Extract for Encapsulation in Alginate-Pea Protein Hydrogels with pH-Responsive Release Behavior

Tue, 15 Sep 2026 00:00:00 +0700

This study investigated alginate–pea protein hydrogel beads as an encapsulation material for antioxidants derived from low-grade mulberry leaf tea residue (LGMLT). The quality of LGMLT extract powder was significantly influenced by both extraction and drying methods with freeze drying, particularly when combined with ultrasonication-assisted extraction, providing the highest antioxidant activities (ABTS: 37.12 mg of Trolox equivalents/g and FRAP: 43.90 mg of Trolox equivalents/g) and a total phenolic content (22.97 mg gallic acid equivalents/g) statistically comparable to decoction–freeze drying, while spray drying consistently resulted in higher powder yield across extraction methods. The physicochemical and antioxidant properties of hydrogel beads were strongly dependent on the alginate-to-LGMLT extract ratio; higher alginate content improved bead uniformity, encapsulation efficiency (95.90%), and water-holding capacity (55.94%), whereas increased extract loading enhanced total phenolic content and antioxidant activity. In vitro pH-responsive release studies demonstrated a rapid release of phenolic compounds under pH 1.2, followed by a more sustained release at pH 7.4, reflecting the pH-dependent behavior of the hydrogel matrix. Differences between ABTS and FRAP responses indicated assay-dependent antioxidant capacities influenced by hydrogel composition. Based on these findings, alginate–pea protein hydrogels represent a tunable, food-grade encapsulation system for antioxidants and offer an alternative approach for the valorization of tea-processing residues in functional food applications, contributing to sustainable food production and food security.

Association between Praziquantel Treatment and Cholangiocarcinoma in Khon Kaen, Thailand: A Retrospective Cohort Study

Tue, 15 Sep 2026 00:00:00 +0700

Cholangiocarcinoma (CCA) is highly prevalent in northeastern Thailand, where Opisthorchis viverrini (OV) infection is endemic. Recurrent infection may lead to repeated praziquantel (PZQ) treatment, chronic biliary inflammation, and long-term carcinogenic processes. However, population-based longitudinal evidence regarding the association between PZQ use and CCA remains limited. Therefore, this study aimed to estimate the association between PZQ use and CCA incidence in a population-based cohort. This retrospective cohort study used data from the Khon Kaen Cohort Study conducted between 1990 and 2001. A total of 17,941 participants aged 30–70 years were followed through linkage with the Khon Kaen Population-Based Cancer Registry until 2022. Participants were classified by baseline history of PZQ use, obtained from structured interviews. Missing values for PZQ use and OV infection were addressed using logistic regression-based imputation models. Generalized linear models were used to estimate relative risks (RRs) and 95% confidence intervals (CIs). As a secondary exploratory analysis, the CCA Risk Lifestyle Index (CRLI), constructed from four factors, namely PZQ use, OV infection, alcohol consumption, and smoking (range 0–4), was evaluated separately. Among participants, 3,769 (21.01%) reported PZQ use. CCA occurred in 156 PZQ users (4.14%) and 456 non-users (3.22%). PZQ use was associated with a modestly increased risk of CCA (adjusted RR = 1.22, 95% CI: 1.01–1.48). Higher CRLI scores were associated with increased CCA risk (RR = 1.23, 95% CI: 1.13–1.33). PZQ use was associated with higher CCA incidence in this cohort. However, the findings should be interpreted cautiously because residual confounding related to recurrent OV infection may remain. Further longitudinal studies are needed to clarify this relationship.

Clinical and Optical Coherence Tomography Characteristics of Large Primary Macular Holes

Duc Anh Nguyen, Huy Binh Nguyen, Tran Dat Dang, Xuan Hai Ho, Thu Trang Nguyen — Tue, 15 Sep 2026 00:00:00 +0700

Large primary full-thickness macular holes are associated with visual impairment and complex optical coherence tomography (OCT) abnormalities. This single-center cross-sectional study described pretreatment clinical and OCT characteristics of large primary macular holes and explored associations with symptom duration and visual acuity. Forty eyes from 40 surgical candidates with primary macular holes and a minimum linear diameter (MLD) > 400 µm were analyzed at Vietnam National Eye Hospital, Hanoi, Vietnam, from March to December 2025. Clinical variables included age, sex, symptom duration, and best-corrected visual acuity (BCVA). OCT variables included vitreomacular status, fluid cuff, intraretinal cyst severity, MLD, base diameter, hole height, external limiting membrane (ELM) and ellipsoid zone (EZ) defect lengths, macular thickness parameters, and macular hole indices. Mean age was 63.7 ± 8.4 years, and women accounted for 57.5% of patients. Mean BCVA was 1.47 ± 0.44 logMAR. Mean MLD, base diameter, and hole height were 594.3 ± 155.8 µm, 1234.9 ± 456.3 µm, and 480.3 ± 110.4 µm, respectively. Complete posterior vitreous detachment, fluid cuff, and intraretinal cysts of any severity were observed in 77.5%, 57.5%, and 85.0% of eyes, respectively. Longer symptom duration was associated with larger MLD and lower HFF and THI. Poorer BCVA was associated with larger MLD and lower MHI and THI. Outer retinal defect lengths correlated with hole size, and fluid cuff was associated with wider structural disruption. Comprehensive pretreatment OCT assessment helps characterize structural severity in large primary macular holes. These associations are exploratory and should be validated prospectively.

Morphology and Anisotomous Branching of rhizoids in Non-terminal Cells of a Spirogyra sp.

Tue, 15 Sep 2026 00:00:00 +0700

Spirogyra, a widespread filamentous green alga, typically anchors to substrates via rhizoids at the filament termini, an anchoring strategy that enhances their resilience to environmental disturbance. In this descriptive study, we examined rhizoid morphology in a Spirogyra unialgal culture using light and epifluorescence microscopy coupled with Calcofluor white and aniline blue staining. We observed rhizoid-like structures associated with non-terminal (intercalary) cells, suggesting that these cells may possess an inducible developmental potential beyond terminal cell identity. The observed rhizoids were consistently rod-shaped and dichotomously branched; however, rosette morphologies were not observed, possibly due to culture conditions or species-level variation. Notably, these single-celled rhizoids also exhibited anisotomous branching (unequal bifurcation). To our knowledge, this is a previously uncharacterized morphological feature in Spirogyra and a novel observation for unicellular rhizoids, raising important questions about developmental plasticity in streptophyte algae.

Population-based Incidence and Incidence Trends by Age Group of Female Breast Cancer in Khon Kaen Province, Thailand, 2002-2021

Tue, 15 Sep 2026 00:00:00 +0700

This study aimed to delineate the age-specific incidence and temporal trends of female breast cancer in Khon Kaen Province, Thailand, between 2002 and 2021. We conducted a descriptive study using longitudinal data from the Khon Kaen Population-Based Cancer Registry. Incidence was reported using Crude Incidence Rates (CIR) and Age-Standardized Rates (ASR). Temporal trends were evaluated using the Average Annual Percentage Change (AAPC) derived from Joinpoint regression. A total of 5,800 cases were analyzed. The overall incidence showed a consistent upward trend, peaking in 2020 (ASR = 31.38 cases per 100,000 women-years). The overall AAPC was 4.71% for CIR (95% CI 4.0, 5.4, p < 0.001) and 3.57% for ASR (95% CI 3.2, 4.0, p < 0.001). Age-stratified analysis revealed a rising incidence across all age groups. When measured by ASR, the < 40 years age group experienced the most rapid increase (AAPC = 5.12%). Conversely, when measured by CIR, the 55-69 years age group showed the greatest increase (AAPC = 3.80%), reflecting an increasing proportion of elderly individuals. The rising incidence, coupled with an aging population, necessitates a two-pronged approach to public health policy. These findings support further evaluation of age-appropriate screening, awareness programs, stage distribution, mortality, and cost-effectiveness.

Development of a Functional Goat Milk Yogurt Fortified with Canine-Derived Probiotics: Physicochemical Properties, Gastrointestinal Survival, and Palatability in Dogs

Tue, 15 Sep 2026 00:00:00 +0700

Dog yogurt products have gained increasing popularity among pet owners because of their nutritional value and their potential as vehicles for delivering probiotics to companion animals. This study aimed to develop a host-specific probiotic goat milk yogurt for dogs by combining canine-derived probiotic strains with selected yogurt starter cultures isolated from commercial yogurts. Six lactic acid bacteria (LAB) isolates were obtained from ten commercial yogurt products and identified as Lacticaseibacillus paracasei subsp. paracasei, Limosilactobacillus fermentum, and Streptococcus salivarius subsp. thermophilus using the API 50 CHL system. Among the isolates, Lacticaseibacillus (Lac.) paracasei LPC1 and Streptococcus (S.) thermophilus ST8 were selected as starter cultures based on their technological properties. Functional goat milk yogurts were produced by co-culturing the selected starter cultures with canine-derived probiotics, namely Agrilactobacillus fermenti Pom1, Limosilactobacillus fermentum Pom5, Pediococcus pentosaceus Chi8, or their cocktail. Compared with probiotic monocultures, the incorporation of Lac. paracasei LPC1 and S. thermophilus ST8 significantly improved yogurt structure by reducing syneresis and increasing the water-holding capacity. During 7 days of storage at 4°C, all formulations maintained stable physicochemical properties, with pH values ranging from 4.1 to 4.4 and titratable acidity from 0.77% to 1.13%. Viable LAB populations remained within 10⁷–10⁸ CFU/g throughout storage. Simulated gastrointestinal assays showed that substantial populations of viable LAB and S. thermophilus survived exposure to gastric and intestinal conditions, indicating a protective effect of the yogurt matrix. Palatability testing in 30 dogs demonstrated excellent acceptance of all formulations, with complete consumption rates of 96.7–100.0% and average consumption times of 28–38 s. Overall, co-culturing Lac. paracasei LPC1 and S. thermophilus ST8 with canine-derived probiotics successfully produced a functional goat milk yogurt with desirable physicochemical properties, high palatability, and sustained LAB viability during refrigerated storage, supporting its potential as a probiotic delivery vehicle for dogs.

Polyester That is Degradable by Sodium Bicarbonate After Oxidation of Sulfide to Sulfone: Polyester from Glyceraldehyde Ethylene-Thioacetal

Nobuhiro Kihara, Miho Honma — Tue, 15 Sep 2026 00:00:00 +0700

Polyesters bearing the 2-thioethyl ester moiety degrade through oxidation to sulfone followed by b-elimination promoted by a base. The basicity of sodium carbonate is essential for the b-elimination process, while degradation using sodium bicarbonate has proven unsuccessful. To achieve highly selective degradation, novel polyesters were developed in which sodium bicarbonate can promote the b-elimination process. A thioacetal of glyceraldehyde was synthesized as the monomer for the preparation of a model ester and of polyesters. The model diester was prepared by reaction with benzoyl chloride. Quantitative oxidation of the model diester to the bis-sulfone and subsequent b-elimination using sodium bicarbonate solution were monitored by ¹H-NMR spectroscopy. Polyesters were synthesized through reactions with terephthaloyl chloride and isophthaloyl chloride. The oxidative degradation of these polyesters was successfully carried out via oxidation followed by treatment with sodium bicarbonate solution.