Macromolecular-based gene delivery systems have emerged as viable alternatives to non-viral vectors for gene therapy due to their versatility, biocompatibility, and capacity to efficiently deliver therapeutic cargo. These systems, primarily based on synthetic and natural polymers, offer significant advantages in terms of safety, controlled gene release, and targeted delivery. This review explores the design and synthesis of macromolecular carriers, focusing on their chemical and physical architectures, which play a key role in improving gene delivery. Catanionic polymers and their derivatives (comb, brush, and star polymers) have been extensively researched for their capacity to condense and protect genetic material. Furthermore, natural polymers like chitosan and hyaluronic acid have been modified to enhance gene delivery capabilities. These macromolecular carriers are engineered to boost circulation time, increase cellular uptake, and facilitate the controlled release of genetic material at the target site. Strategies such as incorporating targeting ligands, stimuli-responsive elements, and reducing cytotoxicity are being pursued to improve the overall efficiency and specificity of these systems. This review highlights the current state of macromolecular gene delivery systems, their applications, and the ongoing research aimed at overcoming existing challenges, paving the way for more effective non-viral gene therapies.

Infection control is essential for the success of prosthodontic and oral implant procedures, as microbial contamination can lead to serious complications such as denture stomatitis and peri-implantitis. While synthetic disinfectants like chlorhexidine are commonly used, they may cause side effects including irritation, toxicity, and the development of microbial resistance over time. Natural products derived from plants, animals, and minerals are currently being explored as safer alternatives. Compounds such as epigallocatechin gallate from green tea; eugenol from clove oil; quercetin, thymol, cinnamaldehyde, and flavonoids from propolis; and terpinen-4-ol from tea tree oil have shown strong antimicrobial and anti-biofilm properties. These natural agents are not only effective against harmful oral bacteria but also promote healing, are more biocompatible, environmentally friendly, and are often preferred by patients. However, challenges remain regarding their routine clinical use. The strength and composition of natural agents can vary, and there is a lack of consistent product standards, clinical trials, and comprehensive safety data. Currently, these products are not approved by the U.S. Food and Drug Administration for dental use and are only available as over-the-counter remedies. Production costs and scalability must also be evaluated in comparison with synthetic alternatives. Emerging technologies, such as nanocarriers and targeted delivery systems, are being developed to enhance the effectiveness of natural agents in dental applications. Further clinical research and the establishment of clear regulatory guidelines are necessary to support their integration into clinical practice. Natural disinfectants hold significant potential to become valuable, safe, and sustainable tools for maintaining hygiene in prosthodontics and oral implantology.

Liver failure syndromes are characterised by a dysregulated immune response leading to immune paralysis. Adrenomedullin (ADM) is a potent vasodilator and immunoregulator. This study aimed to explore the role of ADM in liver failure, hypothesising that there is a detrimental imbalance between ADM and adrenomedullin binding protein (AMBP)1 that promotes a switch of monocytes/macrophages towards a pro-restorative phenotype and function.

Consecutive patients with acute liver failure (ALF), acute-on-chronic liver failure (ACLF), and decompensated cirrhosis, as well as healthy controls (HC) were included between April 2020 and June 2024. Peripheral blood mononuclear cells/monocytes were isolated and used for RNA sequencing and cell culture. ADM and AMBP1 were measured by enzyme-linked immunosorbent assay.

Fifty-four patients with ALF, 25 with ACLF, 9 with decompensated cirrhosis, and 16 with HC were included. ADM expression in isolated monocytes was increased in ALF (log fold change = 5.88, p = 0.000216413) and ACLF (log fold change = 4.62, p = 0.00057122) compared to HC. Plasma ADM concentration was higher in ALF (1,684 ± 1,156 pg/mL) vs. ACLF (836.1 ± 765.2 pg/mL) and HC (164.8 ± 62.73 pg/mL). AMBP1 was significantly reduced in ALF (59.27 ± 44 µg/mL) vs. ACLF (126.3 ± 72.23 µg/mL) and HC (252.8 ± 159.7 µg/mL) (p < 0.0001, ALF vs. HC). Treatment with LPS increased ADM concentration in peripheral blood mononuclear cell supernatant (ALF n = 6; 561.4 ± 1,038 pg/mL vs. 259.2 ± 213.7 pg/mL, ACLF n = 4; 3,202 ± 491.2 vs. 1,757 ± 1,689 pg/mL). The percentage of CD14+ cells expressing Mer tyrosine kinase was reduced after culture with LPS (2.077 ± 0.87%); however, co-culture with ADM 100 nM restored the phenotype (3.852 ± 1.063%).

ADM is increased in liver failure, whereas AMBP1 is reduced. ADM affects monocyte function, increasing Mer Tyrosine Kinase and promoting a pro-restorative, anti-inflammatory phenotype.

Soft tissue cytopathology plays a vital role in the diagnosis and management of soft tissue neoplasms, necessitating a standardized classification system to improve diagnostic accuracy and guide clinical decision-making. This article provides a concise review of the World Health Organization (WHO) Reporting System for Soft Tissue Cytopathology and presents a practical diagnostic approach to soft tissue cytopathology.

The WHO Reporting System is reviewed in conjunction with relevant literature. The reporting system employs a six-category framework: non-diagnostic, benign, atypical, soft tissue neoplasm of uncertain malignant potential, suspicious for malignancy, and malignant. Each category is associated with a corresponding risk of malignancy and recommended clinical management guidelines. This classification aligns with the WHO Classification of Soft Tissue and Bone Tumours (5th edition) and incorporates cytomorphologic features, ancillary studies, and clinical correlation to enhance diagnostic reproducibility and communication among pathologists and clinicians.

The system supports a probabilistic approach to risk stratification, enabling more consistent diagnostic and therapeutic strategies.

As molecular diagnostics and immunocytochemistry continue to advance, this framework provides a robust foundation for the interpretation of soft tissue fine-needle aspiration biopsies and optimized patient care.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of hepatic fibrosis, yet its prevalence in asymptomatic populations remains unclear. This study aimed to assess the prevalence of steatosis and significant fibrosis in asymptomatic individuals without known liver disease in the Greater Vancouver Area.

Interested individuals voluntarily registered online via the Canadian Liver Foundation website or by telephone. Inclusion criteria included age ≥ 19 years, no known liver disease, and low alcohol intake (<30 g/day for men, <20 g/day for women). Demographic and clinical data were collected, and all participants underwent transient elastography after a 3-h fast. The study aimed to collect 4,500 analyzable scans while reflecting the region’s ethnic diversity.

A total of 4,193 participants were analyzed. The median age was 62 years, the median body mass index was 25.4, and 45% were male. Asian individuals comprised 42% of the cohort. Steatosis was present in 59.6% of participants, and 45.7% met diagnostic criteria for MASLD. Significant fibrosis (F2–F4) was found in 8.6%. Age, male sex, ethnicity, cardiac disease, diabetes, hypertension, and obesity were significantly associated with fibrosis. Logistic regression analysis confirmed age, weight, diabetes, dyslipidemia, hypertension, and obesity as independent predictors.

A substantial proportion of asymptomatic individuals in Greater Vancouver have undetected MASLD and significant fibrosis. Early identification of high-risk groups may support broader implementation of transient elastography screening. This study provides one of the first North American population-based estimates of MASLD and fibrosis stratified by ethnicity, offering new insights into liver disease distribution among Caucasian, Chinese, and South Asian populations.

Metabolic dysfunction-associated fatty liver disease, representing a spectrum of liver disorders from simple steatosis to metabolic dysfunction-associated steatohepatitis, fibrosis, and cirrhosis, has emerged as one of the most prevalent chronic liver conditions globally, affecting an estimated approximately 30% of the world's population. Its pathogenesis is highly complex, involving intricate interactions between genetic predisposition, metabolic dysregulation, inflammation, and cellular stress responses. Within this complex landscape, orphan nuclear receptors (ONRs) have gained significant attention. Defined by the lack of identified endogenous ligands, ONRs function as master transcriptional regulators controlling diverse biological processes. Crucially, they play pivotal roles in the development and progression of numerous diseases, including metabolic disorders.This review specifically focuses on elucidating the critical contributions of various ONRs to the pathogenesis of metabolic dysfunction-associated fatty liver disease. We examined how these receptors modulate key pathological drivers: lipid metabolism, inflammation,and autophagy.

Blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is essential for non-invasively investigating brain function. However, conventional fMRI methods are limited by low spatial and temporal resolution. This narrative review evaluates recent advancements in deep learning techniques for high-resolution BOLD-fMRI reconstruction, focusing on super-resolution, segmentation, and image registration. A comprehensive literature search was conducted across PubMed, IEEE, Scopus, and Web of Science databases for the period 2000–2023. Studies employing deep learning methods, including convolutional neural networks, transformer-based models, and generative adversarial networks for super-resolution, segmentation, and registration of BOLD-fMRI, were included. Deep learning approaches demonstrated significant improvements in spatial resolution, segmentation accuracy, and registration robustness. Convolutional neural network-based models, particularly generative adversarial networks, notably improved image reconstruction quality and detail preservation. Preliminary studies targeting specific brain regions such as the cerebellum and hippocampus showed promise; however, systematic evaluations across broader brain areas and large-scale clinical validations remain limited. While deep learning techniques have led to substantial advancements in high-resolution BOLD-fMRI reconstruction, future research should focus on standardized protocols, multi-center validation, and improving computational efficiency and model generalization to enhance clinical utility.

Emerging evidence implicates immune dysregulation and neuroinflammation in the pathogenesis of epilepsy, yet the causal mechanisms remain unclear. This study aimed to investigate the causal effects of immune cells and inflammatory proteins on epilepsy and evaluate the mediating role of inflammatory proteins.

This study utilized the largest available genome-wide association study data on immune cell phenotypes and inflammatory proteins as exposures, and epilepsy genome-wide association study data from the FinnGen dataset as outcomes. Five Mendelian randomization (MR) methods were applied within a two-sample MR framework to assess causal effects. Furthermore, a two-step MR analysis was conducted to quantify the proportion of epilepsy and its subtypes influenced by immune cells through inflammatory proteins.

The two-sample MR analysis identified 32 immune cell phenotypes associated with epilepsy risk (19 risk-increasing, e.g., CD19+ B cells; 13 protective, e.g., regulatory T cell subsets). Subtype analyses revealed 30 immune phenotypes associated with generalized epilepsy and 26 with focal epilepsy. Eight inflammatory proteins showed suggestive causal effects on epilepsy: C-C chemokine ligand 23, C-X-C motif chemokine ligand 6, C-X-C motif chemokine ligand 11, and vascular endothelial growth factor A increased epilepsy risk, while interleukin-13 (IL-13), leukemia inhibitory factor receptor, tumor necrosis factor, and osteoprotegerin conferred protection. Mediation analysis indicated that inflammatory proteins mediated 6.3–13.5% of the immune effects on epilepsy. Specifically, CD14+CD16+ monocytes increased epilepsy risk through elevated C-C chemokine ligand 23 levels (8.5% mediation), while effector memory double-negative (CD4−CD8−) T cells reduced epilepsy risk via upregulation of IL-13 (6.3%). Sensitivity analyses confirmed the robustness of these findings (P heterogeneity/pleiotropy > 0.05). Although no associations reached Bonferroni-corrected significance, the findings implicate B cells, monocytes, regulatory T cells, and cytokines (e.g., IL-13, leukemia inhibitory factor receptor) in the pathogenesis of epilepsy, with inflammatory proteins acting as partial mediators.

These results enhance our understanding of immune-inflammatory pathways in epilepsy and highlight potential therapeutic targets. Future studies should validate these findings across diverse populations and further elucidate the molecular mechanisms underlying the identified associations.