Marburg virus (MARV) disease is an uncommon yet serious viral hemorrhagic fever that impacts humans and non-human primates. In humans, infection by the MARV is marked by rapid onset, high transmissibility, and elevated mortality rates, presenting considerable obstacles to the development of vaccines and treatments. Bats, particularly Rousettus aegyptiacus, are suspected to be natural hosts of MARV. Previous research reported asymptomatic MARV infection in bats, in stark contrast to the severe responses observed in humans and other primates. Recent MARV outbreaks highlight significant public health concerns, underscoring the need for gene expression studies during MARV progression. To investigate this, we employed two models from the Gene Expression Omnibus, including kidney cells from Rousettus aegyptiacus and primary proximal tubular cells from Homo sapiens. These models were chosen to identify changes in gene expression profiles and to examine co-regulated genes and pathways involved in MARV disease progression. Our analysis of differentially expressed genes revealed that these genes are mainly associated with pathways related to the complement system, innate immune response via interferons, Wnt/β-catenin signaling, and Hedgehog signaling, which play crucial roles in MARV infection across both models. Furthermore, we identified several potential compounds that may be useful against MARV infection. These findings offer valuable insights into the mechanisms underlying MARV pathophysiology and suggest potential strategies for preventing transmission, managing post-infection effects, and developing future vaccines.

Objectives: This study evaluated the clinical outcomes, surgical accuracy, and patient satisfaction in treating excessive gingival display caused by altered passive eruption (APE) using a comprehensive digital workflow and double surgical guide. Materials and Methods: A prospective case series study was conducted enrolling 30 patients diagnosed with APE Type 1B. Cone-beam computed tomography (CBCT), intraoral scanning, and digital smile design were used to design and fabricate a 3D-printed double surgical guide for both gingivectomy and osteotomy. The primary outcome was surgical accuracy, assessed by the gingival margin relapse at 6 months. Secondary outcomes included gingival display (GD), clinical crown length (CCL), periodontal and papillary parameters, and patient satisfaction. Statistical analyses were performed with significance set at p < 0.05. Results: Thirty participants were treated successfully. The digital workflow demonstrated high accuracy with a median gingival margin relapse of 0.69 [0.58–0.87] mm at 6 months. Regarding clinical efficacy, a statistically significant reduction in GD was observed (from 3.13 [2.90–3.85] to 1.06 [0.56–1.99] mm; p < 0.001) alongside a statistically significant increase in CCL (from 7.64 [7.25–8.16] to 10.00 [9.56–10.46] mm; p < 0.001). Patient-reported outcomes indicated 100.0% satisfaction with the aesthetic result. Conclusions: Within the limitations of this case series, the described comprehensive digital workflow using a double surgical guide is a predictable and effective method for treating excessive gingival display. The technique achieves significant aesthetic improvements and results in a high level of patient satisfaction.

This study presents a machine learning framework for predicting pancreatic ductal adenocarcinoma (PDAC) using urinary biomarkers, with post hoc validation through single-cell transcriptomics. Available urinary biomarkers were incorporated into a demographic-informed preprocessing approach, followed by predictive model development using normalization and feature-learning techniques. The framework was further validated using single-cell RNA sequencing (scRNA-seq) data to assess gene-expression patterns of identified biomarkers within pancreatic tumor samples. The analysis demonstrated the significance of urinary biomarkers for PDAC prediction and highlighted their biological relevance through transcriptomic validation. Multiple classification models and parameter combinations were evaluated, with deep learning approaches outperforming traditional machine-learning methods. The predictive model achieved high accuracy, and the framework provided insights into demographic influences without compromising predictive performance. The study supports the potential application of urinary biomarkers as a non-invasive tool for early PDAC detection and emphasizes the value of integrating transcriptomic validation into biomarker-based predictive modeling.

A smile that reveals more than 3–4 mm of gum tissue is called a gummy smile (GS), which can negatively affect self-confidence and aesthetic appearance. Treatment planning for GS should consider underlying causes such as altered passive eruption, vertical maxillary excess, or hyperactive lip muscles. This case report describes a multidisciplinary approach for treating severe GS using digital planning and a surgical guide. The treatment combined orthodontic therapy with gingivoplasty supported by three-dimensional simulation and a digitally fabricated surgical guide. The digital workflow enabled precise diagnosis, improved surgical accuracy, and more predictable treatment outcomes. The results demonstrated significant aesthetic improvement and patient satisfaction, highlighting that digitally guided gingivoplasty can be an effective and minimally invasive alternative to more extensive surgical procedures for correcting severe gum exposure.

Triple-negative breast cancer (TNBC) remains one of the most aggressive and therapeutically challenging breast cancer subtypes due to its lack of targetable receptors and intrinsic chemoresistance. This study applies integrated multi-omics approaches combining single-cell RNA sequencing (scRNA-seq) with bulk transcriptomic and clinical data to investigate cellular heterogeneity and underlying mechanisms of drug resistance in TNBC. Analysis of the scRNA-seq dataset (GSE176078) reveals tumor microenvironment diversity and identifies distinct cell populations contributing to tumor progression and treatment resistance. Unsupervised clustering of TCGA-BRCA data delineates three molecular subtypes with unique biological and metabolic profiles. Differential gene expression analysis identifies key genes associated with prognosis and drug response. A prognostic gene signature composed of selected differentially expressed genes is developed and validated across independent cohorts, demonstrating robust predictive performance. The findings provide critical insights into TNBC heterogeneity and offer a foundation for personalized therapeutic strategies.

This case report presents an accelerated orthodontic treatment combining a 2D lingual appliance with an in-house aligner to address anterior cross-bite and temporomandibular disorder (TMD). A 23-year-old female patient with dental crowding and malocclusion underwent 3D simulation and treatment planning. Initial alignment was achieved using a lingual appliance, followed by refinement with an in-house aligner to improve aesthetics and occlusion. The treatment successfully corrected the cross-bite, reduced TMD symptoms, and achieved stable occlusion within one year. The study highlights the effectiveness of hybrid orthodontic approaches in managing complex dental cases with improved patient outcomes.

This study evaluates the accuracy and reliability of dental arch measurements obtained from digital models created using the CEREC Primescan intraoral scanner compared with traditional plaster models. Measurements of tooth heights and widths were analyzed, showing statistically significant differences only in isolated cases, with minimal deviations overall. Intra-rater and inter-rater reliability were assessed and demonstrated high consistency across measurements. The results indicate that digital intraoral scanning provides comparable accuracy to plaster models with excellent reproducibility, supporting its application in clinical orthodontic practice.

This study evaluates the accuracy of estimated glomerular filtration rate (eGFR) equations in potential Vietnamese living kidney donors by comparing them with measured GFR using scintigraphy. Various equations, including MDRD, CKD-EPI creatinine, cystatin C, and combined equations, were assessed. The results show that CKD-EPI equations based on creatinine and cystatin C provide the best accuracy, with low bias and narrow limits of agreement. The findings suggest that CKD-EPI equations are reliable tools for assessing kidney function in living donor screening and can support clinical decision-making in transplantation practices in Vietnam.

This study evaluates the performance of the latest large language models (LLMs) in answering dental multiple-choice questions, including both text-based and image-based formats. A total of 1,490 questions from United States National Board Dental Examination review books were used to assess models such as ChatGPT-4, Gemini, Copilot, Claude, Mistral, and Llama. Statistical analyses revealed significant differences in accuracy across models. Copilot, Claude, and ChatGPT achieved the highest performance, especially on text-based questions, while performance varied more on image-based questions. The findings indicate that multimodal capabilities improve performance and highlight the growing potential of LLMs in dental education and assessment.

Lingual treatment is becoming more and more common, but it is a field in which not all orthodontists excel. Moreover, patients wearing lingual appliances experience more pain, speech difficulties, and problems maintaining adequate oral hygiene, which may cause them to lose their patience with the technique. As a result, iatrogenic treatment outcomes are sometimes observed. In this case report, the patient's chief complaint was spacing. She had been wearing lingual brackets for 1.5 years with minimal improvement. The previous doctor had informed her that the total treatment time would be about 1–1.5 years. However, the patient lost her patience with the treatment and came to us seeking an alternative solution that maintains a similar focus on aesthetics. After discussing potential alternative treatments with the patient, we decided to proceed with in-house aligners. Initially, the patient opted to distribute the spaces for veneers on the anterior teeth to save time. However, after the first series of aligners, she changed her mind and decided to close all the spaces because she found the aligners effective. After 7 months with three series of aligners, the achieved outcomes included closing all spaces, improving the midlines, achieving a Class I canine relationship, and better intercuspation. The treatment outcomes remained stable at the 1-year follow-up. Using in-house aligners is an effective alternative to lingual brackets in certain cases.

This study evaluates the application of artificial intelligence in designing 3D-printed lingual indirect bonding trays and its impact on bracket transfer accuracy. Digital dental models were created using intraoral scanning and virtual setups, followed by automated tray generation using AI-powered tools. The accuracy of bracket placement was assessed by comparing planned and actual positions, including linear and angular deviations. Results show that most transfer errors were within clinically acceptable limits, with grouped trays demonstrating higher precision than individual trays. The findings highlight the effectiveness of AI-assisted digital workflows in improving consistency and accuracy in orthodontic appliance fabrication.

Tumor stemness is increasingly recognized as a key contributor to tumor heterogeneity, immune regulation, and therapeutic resistance in colorectal cancer (CRC). In this study, we developed a stemness-based risk model using bulk transcriptomic data from The Cancer Genome Atlas and evaluated its prognostic and therapeutic relevance through integrative analyses. The proposed risk score robustly stratified patients into distinct prognostic groups and remained an independent predictor of overall survival after adjustment for clinicopathological variables. Stemness-high tumors exhibited altered immune infiltration patterns and coordinated upregulation of immune checkpoint-related genes. Although the association between stemness score and immune evasion potential was modest, its clinical relevance was supported by validation in independent immunotherapy-treated cohorts, where low-risk patients demonstrated improved survival and higher response rates. Single-cell RNA sequencing (scRNA-seq) analysis further revealed that enhanced stemness and dedifferentiation were predominantly localized within malignant epithelial cells. Together, these findings establish tumor stemness as a central determinant of prognosis, immune regulation, and therapeutic vulnerability in CRC.

This analytical cross-sectional study investigated the prevalence and determinants of anemia among 805 adolescent girls across 11 high schools in a northern mountainous province of Vietnam. The findings reveal a high prevalence of anemia at 47.1%, with mild and moderate cases accounting for 29.5% and 17.1% of the participants, respectively. Statistical analysis identified significant risk factors, including living in poor households, using unsanitary toilets, and infrequent consumption of milk products. Conversely, girls of Kinh ethnicity and those with better knowledge of iron-rich foods demonstrated a significantly reduced risk of developing the condition. The study also noted that factors like age and anthropometric measurements were recorded, with a mean participant age of approximately 16 years. These results underscore the urgent need for targeted public health interventions focusing on nutritional education, improved sanitation, and dietary support for high-risk ethnic minority groups in mountainous regions.

Background: Salmonella spp. is a prominent causative agent of pediatric diarrhea, with recent research emphasizing the rising concern regarding antimicrobial resistance (AMR), particularly involving colistin, a last-resort antibiotic. This study involved the collection of 500 stool samples from children with diarrhea from two tertiary pediatric hospitals in Ho Chi Minh City. Conventional methods were used to isolate Salmonella spp., and antibiotic resistance profiling against seven antibiotics was conducted using the disk diffusion method. Colistin resistance was determined by the microdilution method. Colistin resistance (mcr) genes were detected by PCR assay. A conjugation experiment with a multidrug-resistant Salmonella strain and E. coli J53 was performed, and the plasmids from this Salmonella strain were analyzed using bioinformatics. Results: The Salmonella spp. infection rate was found to be 24/500 (14.8%). The predominant antibiotic resistance phenotype was ampicillin with 53/74 (71.6%), followed by trimethoprim-sulfamethoxazole with 23/74 (31.1%). Resistance rates to ceftazidime, cefotaxime and gentamicin were 14/74 (18.9%), 13/74 (17.6%) and 6/74 (8.1%), respectively. Resistance to imipenem was not observed. Colistin resistance was exhibited in 3/74 (4.1%) of isolates, all harboring the mcr-1 gene. The plasmid carrying the mcr-1 gene could transfer to E. coli, which belongs to the IncX4 type and contains IS26. Conclusion: This study provides valuable insights into the antibiotic resistance profiles of Salmonella spp. isolated from pediatric patients, with particular emphasis on colistin resistance.

Surgical removal of impacted mandibular third molars (M3M) is a common procedure, yet preoperative difficulty assessment remains heterogeneous and operator-dependent. While artificial intelligence (AI) has been increasingly investigated to automate radiographic interpretation and risk prediction, the literature lacks a comprehensive synthesis specifically focusing on how AI operationalizes surgical difficulty. Following PRISMA-ScR guidelines, this scoping review identified 12 original studies from PubMed, ScienceDirect, and Google Scholar up to December 31, 2025. Results show that most models utilize panoramic radiographs as primary input, with architectures evolving from traditional CNNs to advanced Transformers and YOLO-based detectors. Surgical difficulty is operationalized through non-equivalent endpoints, ranging from subjective radiographic indices to objective intraoperative time. Critical appraisal via PROBAST and CLAIM reveals that while models are highly applicable, 100% carry a high risk of bias due to insufficient external validation and reporting deficits. We propose the M3M-AI Framework to harmonize input fidelity, core outcome sets, and model explainability, providing a roadmap for reliable clinical translation and robust cross-study comparison.

Background: The use of agar-based disk diffusion (ABDD) for susceptibility testing of fungal pathogens is well-established. However, the incubation time may affect the result. Therefore, this study aims to determine the optimal incubation period for assessing the inhibition zone against Trichophyton spp., one of the most common pathogens among patients with dermatophytosis. Methods: This in-vitro study involved 129 cryopreserved strains of Trichophyton spp., including T. rubrum complex (67 strains) and T. mentagrophytes complex (62 strains). The strains were recovered in Sabouraud’s dextrose agar, and conidia were harvested after 5 to 7 days of culture. The ABDD method was performed in Müller-Hinton agar with five antifungals: itraconazole (ITC), griseofulvin (GRI), clotrimazole (CLO), miconazole (MCI), and voriconazole (VOR). The inhibition diameter zone (IZD) was measured consecutively on days 3, 5, and 7 by the caliper. Data analysis was performed by SPSS 25. Results: The mean IZD of all antifungals on T. rubrum was highest on day 5. The results were similar in T. mentagrophytes except VOR presented the highest IZD on day 3. We noticed significant differences in the IZD of ITC, CLO, MCI, and VOR for T. rubrum. In T. mentagrophytes, only VOR showed a marked difference between periods. Conclusion: The study’s findings recommend the optimal incubation time in dermatophyte susceptibility testing. Specifically, the incubation time should be 5 days for ITC, GRI, CLO, and MCI for both T. rubrum and T. mentagrophytes. Regarding VOR, it should be 5 days for T. rubrum and 3 days for T. mentagrophytes.

Patients with end-stage renal disease (ESRD) who are on maintenance hemodialysis (HD) often experience chronic, low-level inflammation, which is closely linked to complications such as anemia, poor nutritional status, and cardiovascular issues. The purpose of this study was to assess the average level of the systemic immune-inflammation index (SII) among individuals receiving regular HD due to ESRD and to explore the clinical and laboratory variables associated with ongoing inflammatory conditions, as indicated by the SII. This descriptive cross-sectional study involved 116 patients diagnosed with ESRD who were receiving maintenance HD. Blood samples were collected and tested for complete blood count, serum albumin, lipid profile (including cholesterol, high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol, and triglycerides), and high-sensitivity C-reactive protein (hs-CRP). Several inflammatory markers were derived from the complete blood count results, including the neutrophil-to-lymphocyte ratio, SII, systemic inflammation response index, and pan-immune-inflammation value. Among the 116 HD patients included in the analysis, the median SII was 498.22 (363.85–749.52). Elevated hs-CRP levels (≥3 mg/L) were observed in 35.34% of patients and were associated with clinical and laboratory characteristics such as gender, body mass index, hemoglobin, triglycerides, albumin, HDL-C, and inflammatory indices such as SII, neutrophil-to-lymphocyte ratio, systemic inflammation response index, and pan-immune-inflammation value (P < .05). hs-CRP showed a moderate positive correlation with SII (r = 0.32, P < .001) and an association with anemia, hypoalbuminemia, and dyslipidemia. Receiver operating characteristic analysis demonstrated that SII had the highest area under the curve (0.673), and the combination of high SII and low albumin significantly increased the odds of elevated hs-CRP (OR = 6.50, 95% confidence interval: 1.73–24.39, P < .05). The median SII in HD patients was 498.22, and it showed a moderate correlation with hs-CRP. The high-inflammation group (hs-CRP ≥ 3 mg/L) showed a statistically significant association with hemoglobin, albumin, triglycerides, and HDL-C (P < .05). The combination of SII and albumin improved the identification of patients at high inflammatory risk. These findings suggest that SII and the SII–albumin combination may serve as practical surrogate markers of systemic inflammation in routine dialysis care.

Context: Although traditional, complementary, and alternative medicine (TCAM) is widely utilized in Vietnam, limited data are available regarding its usage and public attitudes in Can Tho. Aims: To identify factors associated with the practice and attitudes toward TCAM among the adult population in Can Tho, Vietnam. Methods: A cross-sectional study was conducted at seven public healthcare facilities in Can Tho City. Data were collected using a structured questionnaire distributed to 1400 patients, of which 1075 valid responses were analyzed. Binary logistic regression and principal component analysis were employed to identify predictors of TCAM use and to evaluate underlying dimensions of participants’ attitudes. Results: Among participants, 77.4% reported current use of practitioner-recommended TCAM, while 46.7% reported self-administered use. Urban residency and marital status were significantly associated with both types of TCAM use (p<0.001). Principal component analysis revealed two attitudinal dimensions: perceived benefits and concerns regarding TCAM. Older age, cohabitation with relatives, and practitioner-recommended use were significantly associated with higher benefit scores (p<0.05). Female gender and younger age were associated with greater concern scores (p<0.05). Conclusions: High levels of TCAM use and predominantly favorable attitudes were observed among adults in Can Tho. Findings may assist healthcare providers in identifying target groups for evidence-based education and safer integration of traditional medicine practices.

Introduction. In Vietnam, studies on medication use behaviours in patients with chronic obstructive pulmonary disease (COPD) mainly focus on measuring compliance and identifying related factors. However, there is still a lack of in-depth research around the barriers to COPD medication use. The objective of the study was to assess barriers to medication use and associated factors in patients with COPD. Materials and methods. A cross-sectional descriptive study was conducted in 216 COPD patients in a public hospital in Vietnam from February to April 2025. The Vietnamese questionnaire comprised 14 items grounded in the COM-B framework, developed from literature and expert consultation, and evaluated on a 5-point Likert scale. Differences in barriers to medication use according to demographic and health characteristics were analyzed.

This study evaluated the bond strength and failure modes of orthodontic auxiliaries bonded directly to different aligner materials using two adhesive strategies, with and without sandblasting treatment. Six aligner materials, including thermoplastic polymers and 3D-printed resins, were tested after thermocycling. The results showed that bond strength was significantly influenced by the aligner material and sandblasting treatment, with substrate-specific differences observed among bonding protocols. Sandblasting generally improved bond strength, although some exceptions occurred. Failure modes also varied depending on the material and were not always directly related to bond strength values. The findings highlight the importance of material-specific bonding protocols for modern thermoformed and 3D-printed orthodontic aligners.