Sinonasal NUT carcinoma: A consecutive case series and systematic review.

BACKGROUND: Sinonasal NUT carcinoma is an extremely rare, lethal malignancy with limited literature. METHODS: A case series was conduction of all patients with sinonasal NUT carcinoma at a single institution between 2010 and 2022. Survival and associated were evaluated. A systematic review of the literature was performed. RESULTS: In 12 patients, followed for a median of 1.5 years, the median overall survival (OS) and disease-specific survival (DSS) were both 14.6 months. Patients with maxillary sinus tumors were 91% more likely to survive (hazard ratio [HR]: 0.094, 95% confidence interval [CI]: 0.011-0.78, p = 0.011). Patients with higher-stage disease stage had worse OS (stage IVb-c vs. III-IVa, p = 0.05). All three patients who were alive with no evidence of disease received induction chemotherapy. CONCLUSION: For patients with sinonasal NUT carcinoma, the median survival was 15 months but better with lower-stage and maxillary tumors. Induction chemotherapy may be beneficial.

Non-Melanoma Skin Cancer Detection in the Age of Advanced Technology: A Review.

Skin cancer is the most common cancer diagnosis in the United States, with approximately one in five Americans expected to be diagnosed within their lifetime. Non-melanoma skin cancer is the most prevalent type of skin cancer, and as cases rise globally, physicians need reliable tools for early detection. Artificial intelligence has gained substantial interest as a decision support tool in medicine, particularly in image analysis, where deep learning has proven to be an effective tool. Because specialties such as dermatology rely primarily on visual diagnoses, deep learning could have many diagnostic applications, including the diagnosis of skin cancer. Furthermore, with the advancement of mobile smartphones and their increasingly powerful cameras, deep learning technology could also be utilized in remote skin cancer screening applications. Ultimately, the available data for the detection and diagnosis of skin cancer using deep learning technology are promising, revealing sensitivity and specificity that are not inferior to those of trained dermatologists. Work is still needed to increase the clinical use of AI-based tools, but based on the current data and the attitudes of patients and physicians, deep learning technology could be used effectively as a clinical decision-making tool in collaboration with physicians to improve diagnostic efficiency and accuracy.

Review of the Tumor Microenvironment in Basal and Squamous Cell Carcinoma.

It is widely known that tumor cells of basal and squamous cell carcinoma interact with the cellular and acellular components of the tumor microenvironment to promote tumor growth and progression. While this environment differs for basal and squamous cell carcinoma, the cellular players within both create an immunosuppressed environment by downregulating effector CD4+ and CD8+ T cells and promoting the release of pro-oncogenic Th2 cytokines. Understanding the crosstalk that occurs within the tumor microenvironment has led to the development of immunotherapeutic agents, including vismodegib and cemiplimab to treat BCC and SCC, respectively. However, further investigation of the TME will provide the opportunity to discover novel treatment options.

Trends in antibiotic resistance among major bacterial pathogens isolated from blood cultures tested at a large private laboratory network in India, 2008-2014.

OBJECTIVE: There have been no long-term studies on trends in antibiotic resistance (ABR) on a national scale in India. Using a private laboratory network, the ABR patterns of organisms most commonly associated with bacteremia, obtained from patients across India between 2008 and 2014, were examined. METHODS: A retrospective study of patient blood cultures collected over a 7-year period (January 1, 2008-December 31, 2014) was conducted. Data on the microorganism(s) identified and their antimicrobial susceptibility were obtained from SRL Diagnostics (Mumbai, India). RESULTS: Of 135268 blood cultures, 18695 (14%) had at least one identified pathogen. In addition to continual high rates of methicillin-resistant Staphylococcus aureus (MRSA; approximately 44.2%), high resistance to nalidixic acid among Salmonella Typhi (98%) was observed, and carbapenem resistance increased in both Escherichia coli (7.8% to 11.5%; p=0.332) and Klebsiella pneumoniae (41.5% to 56.6%; p<0.001). Carbapenem resistance was also stable and high for both Acinetobacter species (approximately 69.6%) and Pseudomonas aeruginosa (approximately 49%). Resistance was also detected to colistin in the Gram-negatives and to vancomycin and linezolid in S. aureus. CONCLUSION: Increasing resistance to antibiotics of last-resort, particularly among Gram-negatives, suggests an urgent need for new antibiotics and improved antimicrobial stewardship programs in India.