MRI spine request form enhancement and auto protocoling using a secure institutional large language model.

Background Context: Secure institutional large language models (LLM) could reduce the burden of noninterpretative tasks for radiologists.

Purpose: Assess the utility of a secure institutional LLM for MRI spine request form enhancement and auto-protocoling.

Study Design/setting: Retrospective study conducted from December 2023 to February 2024, including patients with clinical entries accessible on the electronic medical record (EMR).

Applications of Artificial Intelligence and Machine Learning in Spine MRI.

Diagnostic imaging, particularly MRI, plays a key role in the evaluation of many spine pathologies. Recent progress in artificial intelligence and its subset, machine learning, has led to many applications within spine MRI, which we sought to examine in this review. A literature search of the major databases (PubMed, MEDLINE, Web of Science, ClinicalTrials.

Oncologic Applications of Artificial Intelligence and Deep Learning Methods in CT Spine Imaging-A Systematic Review.

In spinal oncology, integrating deep learning with computed tomography (CT) imaging has shown promise in enhancing diagnostic accuracy, treatment planning, and patient outcomes. This systematic review synthesizes evidence on artificial intelligence (AI) applications in CT imaging for spinal tumors. A PRISMA-guided search identified 33 studies: 12 (36.

Investigating the effects of percutaneous endovascular aneurysm repair for abdominal aortic aneurysm on the lumen size of the common femoral artery.

Background: Percutaneous endovascular aneurysm repair (PEVAR) is the definitive therapy of choice for abdominal aortic aneurysms worldwide. However, current literature regarding the anatomic changes in the common femoral artery (CFA) post-PEVAR is sparse and contradictory, and a significant proportion of these studies did not control for the potential confounding effects of ethnicity. Thus, this study aims to investigate the anatomical effects of PEVAR on the CFA using an Asian study cohort.

Application of Artificial Intelligence Methods on Osteoporosis Classification with Radiographs-A Systematic Review.

Osteoporosis is a complex endocrine disease characterized by a decline in bone mass and microstructural integrity. It constitutes a major global health problem. Recent progress in the field of artificial intelligence (AI) has opened new avenues for the effective diagnosis of osteoporosis via radiographs.

Artificial Intelligence Applications for Osteoporosis Classification Using Computed Tomography.

Osteoporosis, marked by low bone mineral density (BMD) and a high fracture risk, is a major health issue. Recent progress in medical imaging, especially CT scans, offers new ways of diagnosing and assessing osteoporosis. This review examines the use of AI analysis of CT scans to stratify BMD and diagnose osteoporosis.

Epithelioid Sarcoma of the Spine: A Review of Literature and Case Report.

Epithelioid sarcoma is a rare malignant mesenchymal tumor that represents less than 1% of soft-tissue sarcomas. Despite its slow growth, the overall prognosis is poor with a high rate of local recurrence, lymph-node spread, and hematogenous metastasis. Primary epithelioid sarcoma arising from the spine is extremely rare, with limited data in the literature.

STING antagonists, synthesized Povarov-Doebner type multicomponent reaction.

The cGAS-STING axis plays an important role in protecting higher organisms against invading pathogens or cancer by promoting the production of cytokines and interferons. However, persistent or uncontrolled activation of this pathway could lead to inflamed environments, which is detrimental to the host in the long run. Persistent activation of STING is known to be the cause of STING-associated vasculopathy with onset in infancy (SAVI) and activated STING is believed to play important roles in worsening various diseased states, such as traumatic brain injury, diabetic kidney disease and colitis.

Application of Machine Learning for Differentiating Bone Malignancy on Imaging: A Systematic Review.

An accurate diagnosis of bone tumours on imaging is crucial for appropriate and successful treatment. The advent of Artificial intelligence (AI) and machine learning methods to characterize and assess bone tumours on various imaging modalities may assist in the diagnostic workflow. The purpose of this review article is to summarise the most recent evidence for AI techniques using imaging for differentiating benign from malignant lesions, the characterization of various malignant bone lesions, and their potential clinical application.

Application of Artificial Intelligence Methods for Imaging of Spinal Metastasis.

Spinal metastasis is the most common malignant disease of the spine. Recently, major advances in machine learning and artificial intelligence technology have led to their increased use in oncological imaging. The purpose of this study is to review and summarise the present evidence for artificial intelligence applications in the detection, classification and management of spinal metastasis, along with their potential integration into clinical practice.

c-di-GMP Induces COX-2 Expression in Macrophages in a STING-Independent Manner.

Many pathogen-associated molecular patterns (PAMPs), such as lipopolysaccharide (LPS) and lipoteichoic acid, are potent immunostimulatory molecules and promote the expression of cyclooxygenase 2 (COX-2). While the production of COX-2, and ultimately prostaglandin E, could be protective, persistent induction of COX-2 leads to inflamed environments that can result in septic shock and death. Bacterial derived cyclic dinucleotides (CDNs), c-di-GMP and c-di-AMP, are also PAMPs and have been shown to produce inflamed environments via the production of pro-inflammatory cytokines such as type I interferons.

A STING-based fluorescent polarization assay for monitoring activities of cyclic dinucleotide metabolizing enzymes.

Cyclic dinucleoties, such as cGAMP, c-di-GMP and c-di-AMP, are fascinating second messengers with diverse roles in both prokaryotes and eukaryotes. Consequently there is a need for simple and inexpensive methods for profiling these compounds in biological media, monitoring their synthesis or degradation by enzymes and for identifying inhibitors of proteins that metabolize or bind to these dinucleotides. Since 2011, when we reported the first simple method to detect c-di-GMP (S.

Bacterial Cyclic Dinucleotides and the cGAS-cGAMP-STING Pathway: A Role in Periodontitis?

Host cells can recognize cytosolic double-stranded DNAs and endogenous second messengers as cyclic dinucleotides-including c-di-GMP, c-di-AMP, and cGAMP-of invading microbes via the critical and essential innate immune signaling adaptor molecule known as STING. This recognition activates the innate immune system and leads to the production of Type I interferons and proinflammatory cytokines. In this review, we (1) focus on the possible role of bacterial cyclic dinucleotides and the STING/TBK1/IRF3 pathway in the pathogenesis of periodontal disease and the regulation of periodontal immune response, and (2) review and discuss activators and inhibitors of the STING pathway as immune response regulators and their potential utility in the treatment of periodontitis.

Beyond diabetes mellitus: role of metformin in non-muscle-invasive bladder cancer.

Introduction: Usage of metformin is associated with improved survival in lung, breast and prostate cancer, and metformin has been shown to inhibit cancer cell growth and proliferation in in vitro studies. Given the lack of clinical data on metformin use in patients with bladder cancer, we aimed to evaluate the role of metformin in their oncological outcomes.

Methods: Medication use data from a prospectively maintained database of 122 patients with non-muscle-invasive bladder cancer treated with intravesical Bacille Calmette-Guerin (BCG), who were recruited under a randomised, double-blinded, controlled clinical trial, was collected and analysed.

Is preoperative withdrawal of aspirin necessary in patients undergoing elective inguinal hernia repair?

Background: Antiplatelets such as aspirin are widely used to reduce thrombotic events in patients with various cardiovascular comorbidities. Continuing aspirin through noncardiac surgery has been shown to reduce risk of major adverse cardiac events (MACE) but may lead to higher bleeding complications. Inguinal hernia repair is a commonly performed surgical procedure among such patients, but no guideline exists regarding perioperative use of aspirin.

Long-term results of a randomized controlled trial of T2 versus T2-T3 ablation in endoscopic thoracic sympathectomy for palmar hyperhidrosis.

Background: Despite good short-term results and patient satisfaction with endoscopic thoracic sympathectomy (ETS), there has been much debate on the level of sympathectomy for treatment of palmar hyperhidrosis (PH) in terms of long-term clinical outcomes.

Objective: The aim of the study was to analyze the long-term recurrence and compensatory hyperhidrosis (CH) rates of ETS, comparing single-level T2 against multi-level T2-T3 ablation in single patients.

Methods: Patients who had undergone treatment for PH with unilateral T2 and contralateral T2-T3 ablation in ETS were retrospectively reviewed.

Prognostic significance of lymph node density in squamous cell carcinoma of the tongue.

Background: The prognostic significance of lymph node density in oral squamous cell carcinoma (OSCC) has been well recognized. However, its use in a specific subsite of the tongue has not been evaluated. The purpose of this study was to determine the prognostic significance of lymph node density in tongue squamous cell carcinoma (SCC).