Breast Mass Detection and Classification Using Machine Learning Approaches on Two-Dimensional Mammogram: A Review.

Breast cancer is a leading cause of mortality among women, both in India and globally. The prevalence of breast masses is notably common in women aged 20 to 60. These breast masses are classified, according to the breast imaging-reporting and data systems (BI-RADS) standard, into categories such as fibroadenoma, breast cysts, benign, and malignant masses. To aid in the diagnosis of breast disorders, imaging plays a vital role, with mammography being the most widely used modality for detecting breast abnormalities over the years. However, the process of identifying breast diseases through mammograms can be time-consuming, requiring experienced radiologists to review a significant volume of images. Early detection of breast masses is crucial for effective disease management, ultimately reducing mortality rates. To address this challenge, advancements in image processing techniques, specifically utilizing artificial intelligence (AI) and machine learning (ML), have tiled the way for the development of decision support systems. These systems assist radiologists in the accurate identification and classification of breast disorders. This paper presents a review of various studies where diverse machine learning approaches have been applied to digital mammograms. These approaches aim to identify breast masses and classify them into distinct subclasses such as normal, benign and malignant. Additionally, the paper highlights both the advantages and limitations of existing techniques, offering valuable insights for the benefit of future research endeavors in this critical area of medical imaging and breast health.

UV-killed Staphylococcus aureus enhances adhesion and differentiation of osteoblasts on bone-associated biomaterials.

Titanium alloys (Ti) are the preferred material for orthopedic applications. However, very often, these metallic implants loosen over a long period and mandate revision surgery. For implant success, osteoblasts must adhere to the implant surface and deposit a mineralized extracellular matrix (ECM). Here, we utilized UV-killed Staphylococcus aureus as a novel osteoconductive coating for Ti surfaces. S. aureus expresses surface adhesins capable of binding to bone and biomaterials directly. Furthermore, interaction of S. aureus with osteoblasts activates growth factor-related pathways that potentiate osteogenesis. Although UV-killed S. aureus cells retain their bone-adhesive ability, they do not stimulate significant immune modulator expression. All of the abovementioned properties were utilized for a novel implant coating so as to promote osteoblast recruitment and subsequent cell functions on the bone-implant interface. In this study, osteoblast adhesion, proliferation, and mineralized ECM synthesis were measured on Ti surfaces coated with fibronectin with and without UV-killed bacteria. Osteoblast adhesion was enhanced on Ti alloy surfaces coated with bacteria compared to uncoated surfaces, while cell proliferation was sustained comparably on both surfaces. Osteoblast markers such as collagen, osteocalcin, alkaline phosphatase activity, and mineralized nodule formation were increased on Ti alloy coated with bacteria compared to uncoated surfaces.

Staphylococcus aureus induces expression of receptor activator of NF-kappaB ligand and prostaglandin E2 in infected murine osteoblasts.

Osteomyelitis is an inflammatory disease of the bone that is characterized by the presence of necrotic bone tissue and increased osteoclast activity. Staphylococcus aureus is responsible for approximately 80% of all cases of human osteomyelitis. While the disease is especially difficult to treat, the pathogenesis of S. aureus-induced osteomyelitis is poorly understood. Elucidating the molecular mechanisms by which S. aureus induces osteomyelitis could lead to a better understanding of the disease and its progression and development of new treatments. Osteoblasts can produce several soluble factors that serve to modulate the activity or formation of osteoclasts. Receptor activator of NF-kappaB ligand (RANK-L) and prostaglandin E(2) (PGE(2)) are two such molecules which can promote osteoclastogenesis and stimulate bone resorption. In addition, previous studies in our laboratory have shown that osteoblasts produce inflammatory cytokines, such as interleukin 6, following infection with S. aureus, which could induce COX-2 and in turn PGE(2), further modulating osteoclast recruitment and differentiation. Therefore, we hypothesized that following infection with S. aureus, osteoblasts will express increased levels of RANK-L and PGE(2). The results presented in this study provide evidence for the first time that RANK-L mRNA and protein and PGE(2) expression are upregulated in S. aureus-infected primary osteoblasts. In addition, through the use of the specific COX-2 inhibitor NS 398, we show that when PGE(2) production is inhibited, RANK-L production is decreased. These data suggest a mechanism whereby osteoblasts regulate the production of RANK-L during infection.

Nafcillin-loaded PLGA nanoparticles for treatment of osteomyelitis.

The goal of this investigation is to develop poly(DL-lactide-co-glycolide) (PLGA) nanoparticles for the delivery of antibiotics such as nafcillin to osteoblasts. This is important in order to treat Staphylococcus aureus-mediated osteomyelitis. The latter is often chronic and highly resistant to antibiotics. Nafcillin (a penicillinase-resistant penicillin)-loaded nanoparticles were prepared by a single emulsion/solvent evaporation method. In vitro drug release studies were conducted in an incubator shaker at 37 degrees C in phosphate buffer saline. Drug loading and release were determined by UV-Vis spectroscopy. A viability study was conducted in S. aureus-infected mouse osteoblasts. In vitro release study showed an initial burst release and a second phase of slow release. Following 24 and 48 h of incubation, all formulations of nanoparticles loaded with nafcillin either killed or significantly reduced all of the intracellular bacteria. Our data demonstrate that effective killing of intracellular S. aureus is possible by treating the infected osteoblasts with nanoparticles loaded with nafcillin.