Smart biomaterials in dentistry: A review on the role of cellulose and other biological macromolecules in infection control.

Dental infections continue to present significant challenges in clinical dentistry, often resulting in severe oral and systemic complications. Conventional treatments, including antibiotics and mechanical debridement, face increasing limitations due to microbial resistance and persistent biofilms. This review delves into the evolving field of biomaterials designed for dental infections, especially biological macromolecule-based biomaterials, including cellulose and chitosan, emphasizing their role in infection prevention, treatment, and tissue regeneration.

Efficacy and safety of chemoradiotherapy versus chemotherapy for resectable gastric cancer: a systematic review and meta-analysis.

Background: Gastric cancer is a leading cause of cancer-related deaths. Surgery combined with adjuvant treatments improves survival. This meta-analysis compares the efficacy of chemoradiotherapy (CRT) vs.

Management of High-Riding Nipple-Areola Complex: A Systematic Review of Its Prevention and Management.

Background: The optimal positioning of the nipple-areola complex (NAC) remains a challenging part of breast surgery, with high-riding NAC (HRNAC) frequently occurring postoperatively. An evidence-based summary of all effective prevention and management strategies is needed for a variety of surgical contexts.

Objectives: This systematic review aims to explore and summarise the prevention and corrective strategies for HRNAC across aesthetic and reconstructive breast surgeries.

A Multilamellar, Thermoreversible, Phase-Selective Galactose-Triazole Organogelator: Role of Noncovalent Interactions and Porous Nanostructure in Environmental Remediation.

This article describes the design and synthesis of an efficient galactose-triazole-based reversed N-nucleoside as a thermoreversible, low molecular weight organogelator 8a. The gelator 8a shows a phase-selective behavior toward ethyl acetate with respect to water. Powder X-ray diffraction, scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FTIR), and UV results show that the xerogel has a multilamellar structure due to supramolecular forces identified as H-bonding, van der Waals interactions, and π-π stacking.

Genome-wide identification of the cytochrome P450 superfamily in Trichoplusia ni and in-silico expression of resistance against HDAC inhibitors.

The cabbage looper, Trichoplusia ni, is a serious pest of cruciferous crops such as cabbage, cauliflower, collard/spring greens, and horseradish, with a major financial impact. Despite its significant financial importance, there has been little study on the characterization of Cytochrome P450 (CYP450) genes, which are critical components in the control of metabolic activities. This study discovers and investigates 19 CYP450 genes in T.

A Novel Deep Learning Model for Predicting Colorectal Anastomotic Leakage: A Pioneer Multicenter Transatlantic Study.

: Colorectal anastomotic leak (CAL) is one of the most severe postoperative complications in colorectal surgery, impacting patient morbidity and mortality. Current risk assessment methods rely on clinical and intraoperative factors, but no real-time predictive tool exists. This study aimed to develop an artificial intelligence model based on intraoperative laparoscopic recording of the anastomosis for CAL prediction.

Reframing robotics in Mohs surgery for rare cutaneous sarcomas: conceptual promise and clinical realities in precision oncology.

Dermatofibrosarcoma protuberans (DFSP) is a rare, locally aggressive cutaneous sarcoma in which achieving histologically negative margins is paramount to minimizing recurrence. Mohs micrographic surgery (MMS) has transformed margin control in DFSP by enabling sequential, layer-by-layer excision with immediate histologic assessment, yet it remains technically challenging in anatomically complex sites and in cases with ambiguous deep or subclinical peripheral spread. Recent advances in robotic microsurgical platforms-characterized by tremor elimination, high-resolution imaging, and ergonomic interfaces-offer a conceptual framework for enhancing the precision and consistency of MMS.

VaxPulse: Active Global Vaccine Infodemic Risk Assessment.

Vaccine infodemics, driven by misinformation, disinformation, and inauthentic online behaviours, pose significant threats to global public health. This paper presents our response to this challenge, demonstrating how we developed VaxPulse Vaccine Infodemic Risk Assessment Lifecycle (VIRAL), an AI-powered social listening platform designed to monitor and assess vaccine-related infodemic risks. Leveraging interdisciplinary expertise and international collaborations, VaxPulse VIRAL integrates machine learning methods, including deep learning, active learning, and data augmentation, to provide real-time insights into public sentiments, misinformation trends, and social bot activity.

Enhancing Vaccine Safety Surveillance: Extracting Vaccine Mentions from Emergency Department Triage Notes Using Fine-Tuned Large Language Models.

This study evaluates fine-tuned Llama 3.2 models for extracting vaccine-related information from emergency department triage notes to support near real-time vaccine safety surveillance. Prompt engineering was used to initially create a labeled dataset, which was then confirmed by human annotators.

VaxPulse: Monitoring of Online Public Concerns to Enhance Post-Licensure Vaccine Surveillance.

The recent vaccine-related infodemic has amplified public concerns, highlighting the need for proactive misinformation management. We describe how we enhanced the reporting surveillance system of Victoria's vaccine safety service, SAEFVIC, through the incorporation of new information sources for public sentiment analysis, topics of discussion, and hesitancies about vaccinations online. Using VaxPulse, a multi-step framework, we integrate adverse events following immunisation (AEFI) with sentiment analysis, demonstrating the importance of contextualising public concerns.

Diagnostic accuracy of discovery NM 530c CZT SPECT for myocardial perfusion imaging in coronary artery disease: a systematic review and meta-analysis.

Coronary artery disease (CAD) is the leading cause of cardiovascular mortality (CVD), accounting for 1 in 5 CVD-related deaths. The advent of non-invasive imaging modalities has driven the use of myocardial perfusion imaging (MPI) to enhance diagnostic accuracy and improve clinical outcomes in CAD. Building on the role of myocardial perfusion imaging (MPI), this meta-analysis assesses the diagnostic accuracy of the Discovery NM 530c CZT SPECT for CAD compared with invasive coronary angiography (ICA ± FFR) and noninvasive modalities, including PET, MRI, and coronary CT angiography.

Interface-Engineered 2H-MoS/MXene Heterostructures for High-Performance Ammonium-Ion Hybrid Supercapacitors.

Aqueous ammonium-ion hybrid supercapacitors (AAHSCs) have received significant interest due to their environmental friendliness and excellent electrochemical performance. 2D transition metal carbides and nitrides (MXenes) are promising cathode candidates for AAHSCs owing to their high conductivity and redox activity. However, their tendency to restack severely limits ion accessibility and rate performance.

Novel cardiac biomarkers and multiple-marker approach in the early detection, prognosis, and risk stratification of cardiac diseases.

Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide, necessitating innovative diagnostic and prognostic strategies. Traditional biomarkers like C-reactive protein, uric acid, troponin, and natriuretic peptides play crucial roles in CVD management, yet they are often limited by sensitivity and specificity constraints. This narrative review critically examines the emerging landscape of cardiac biomarkers and advocates for a multiple-marker approach to enhance early detection, prognosis, and risk stratification of CVD.

Dual-track collaboration: Joint processing of heterogeneous positive and negative graph convolutional network for whole-slide image analysis.

Background And Objective: Graph-based methods are widely applied in whole-slide histopathology images (WSI) analysis since they can effectively capture spatial relationship between nodes. However, existing methods focus on promoting positive nodes to have similar representations while ignoring the expression of negative samples of each node, failing to fully utilize various diagnostic information for comprehensive analysis.

Methods: In this paper, we propose a Dual Collaboration Heterogeneous Graph Convolutional Network (DCH-GCN) framework that considers both positive and negative samples implicit in whole-slide images (WSIs).

Validating community concerns of menstrual changes associated with COVID-19 vaccination using a self-controlled case series analysis of real-world data.

Objectives: Stories of menstrual changes occurring post COVID-19 vaccination have abounded, with many affected persons expressing frustration their concerns were not being heard. In an era where misinformation is rampant and can fuel vaccine hesitancy it is imperative to address and validate community concerns. We aimed to investigate evidence of increased menstrual disturbances associated with COVID-19 vaccination.

Identification and evaluation of pyrimidine based CDK6 inhibitors against glioblastoma using integrated computational approaches.

Cyclin-dependent kinases (CDKs) are crucial for controlling the cell cycle, and many malignancies are linked to CDK dysfunction. Therefore, CDKs are desirable targets for cancer treatment. Since abnormal expression of CDK4/6 is the etiology of glioblastoma, it is imperative to investigate the mechanism underlying CDK4/6 selectivity for inhibitors compared to CDK1/2, another member of the family.

Total Neoadjuvant Therapy for Locally Advanced Rectal Cancer.

Importance: This was a clinical study of total neoadjuvant therapy (TNT) for rectal cancer.

Objective: To assess the use and outcomes of TNT in routine practice.

Design, Setting, And Participants: This international, multicenter study was conducted at 61 centers across 21 countries and included consecutive patients treated off trial with TNT for stage II/III rectal adenocarcinoma from September 2012 to December 2023.

Comparative study of Vertucci's and Ahmed's classifications to evaluate the root canal configuration of mandibular incisors in Saudi Arabian subpopulation.

Background &objective: The precise anatomical knowledge of root canals can have positive impact on endodontic treatment outcomes. Recently, a new root canal classification system has been proposed by Ahmed. This study aims to compare Vertucci's and Ahmed's classification systems to analyze canal configuration of mandibular incisors on CBCT scans.

Influence of virtual reality simulation (excluding augmented reality) on endodontic learning experiences of undergraduate dental students: a systematic review.

Background: Virtual Reality (VR) technology has demonstrated a promising prospect for enhancing endodontic learning in undergraduate dental students by boosting their procedural skills, accuracy, and confidence.

Aim: To systematically evaluate the effectiveness of virtual reality (VR) simulation in endodontic education among undergraduate dental students, with a specific focus on four key outcomes: procedural accuracy, enhancement of student confidence, reduction in procedural errors, and overall learner satisfaction.

Methods: An exhaustive literature search was carried out in December 2024 in PubMed, Cochrane Library, Embase, Scopus, and ClinicalTrials.

CBCT based investigation of furcation groove's prevalence, depth, length and associated dentin thickness in Maxillary First Permanent Premolars in Saudi Sub-population.

Background: The study aimed to investigate the furcation groove's (FG) prevalence, depth, length and associated dentin thickness (DT) in Maxillary First Permanent Premolars (MFPM's) in Saudi Sub-population.

Methods: The study was a cross-sectional study, conducted at Qassim University, KSA, on 156 CBCT images. The presence of FG, its length, depth, and associated DT at the deepest point were recorded.

MOF-Based Composite Materials for Supercapacitors: Design, Performance, and Challenges.

Composite materials based on metal-organic frameworks (MOFs) are appealing materials for supercapacitor electrodes because of their high specific surface area, large pore volume, and range of adjustable topologies. This review paper thoroughly examines the synthesis techniques, morphological traits, and problems associated with pristine MOFs. Then, this article focuses on the synthesis techniques of MOF-based composites that include MOF/carbon, MOF/metal oxide, MOF/conducting polymer, MOF-derived carbons, and multimetallic MOF composites.

Rituximab-based regimens for primary cardiac lymphoma: A systematic review of outcomes, challenges and future directions.

Background: Primary cardiac lymphoma (PCL) is a rare subset of cardiac tumors, often diagnosed late due to nonspecific symptoms. It predominantly affects immunocompromised individuals, primarily in the pericardium and right heart. Late diagnosis mimics common cardiac ailments, leading to poor prognosis.