Extraction-Free Testing for SARS-CoV-2 in Nasal Swab and Saliva Samples on a Single High-Throughput Platform.

The COVID-19 pandemic introduced an urgent need for rapid and high-throughput testing for SARS-CoV-2. RNA extraction is a major bottleneck for RT-qPCR. We describe a semi-automated, extraction-free RT-qPCR assay for detection of SARS-CoV-2 in nasal swab and saliva samples on a single platform. With a limit of detection of 4 copies/mL, this laboratory developed test performed equivalently to established methods requiring nucleic acid extraction. Five technologists staffing two shifts per day (80 person-hours) processed more than 400,000 samples over 10 months. Patients opted to provide nasal swab samples (83.6%) more frequently than saliva (16.4%), creating the added challenge of producing swab collection kits. Real-world testing data indicated a higher frequency of SARS-CoV-2 detection in saliva (10.1%) compared to nasal swab (7.7%). This cost-effective and quickly scalable approach is suitable for pandemic preparedness planning related to surveillance and diagnostic testing.

The Role of Local Therapy for Oligo-Progressive Disease in Oncogene-Addicted Non-Small-Cell Lung Cancer.

Purpose: We first described the role of local radiation therapy (LT) for oligoprogressive disease (OPD) on targeted therapy in 2012. Here, we present an updated and larger data set and extend the analysis beyond EGFR and ALK. Methods: A retrospective review of patients with metastatic NSCLC harboring EGFR/BRAF V600E mutations, or ALK/ROS1/RET rearrangements, who had OPD on respective tyrosine-kinase inhibitor (TKI) and treated with LT was performed. OPD was defined as disease progression on therapy in ≤5 sites. PFS1 (progression-free survival 1) was defined as time from initiation of TKI-containing regimen to the first course of LT for OPD. Subsequent PFS times (eg, PFS2, PFS3) were defined as time from prior LT to subsequent LT, switch of systemic therapy, death, or loss to follow-up, whichever occurred first. Extended-PFS was defined as time from the first day of the first LT course to the day of change in systemic therapy, death, or loss to follow-up, whichever came first. Results: Eighty-nine patients were identified. In 75.4% of the LT courses, a single lesion was treated. Median PFS1 was 10.2 months (95% CI, 8.7-13.1) and median Extended-PFS was 6.7 months (95% CI, 4.9-8.3). Extended-PFS was similar across different oncogenic drivers; 51.4% of patients who underwent LT to a single site had only 1 site on next disease progression. Conclusions: LT is effective in prolonging treatment duration on TKI in oncogene-addicted NSCLC across multiple oncogenes.

Upscaling net ecosystem CO2 exchanges in croplands: The application of integrating object-based image analysis and machine learning approaches.

Accurately estimating the net ecosystem exchange of CO2 (NEE) in cropland ecosystems is essential for understanding the impacts of agricultural practices and climate conditions. However, significant uncertainties persist in the estimation of regional cropland NEE due to landscape heterogeneity and variations in the efficacy of upscaling models. Here, we applied an integrated approach that combined object-based image analysis (OBIA) techniques with advanced machine learning (ML) approaches to upscale regional cropland NEE. We conducted a thorough evaluation of the upscaling approach across four distinct cropland areas characterized by diverse climate conditions. Our study confirmed that OBIA techniques can efficiently segment cropland objects, thereby enhancing the representation and accuracy of characteristics relevant to cropland features. The sequential least squares programming algorithm, among the three methods used for ML model integration, demonstrated exceptional performance in predicting NEE, with an R2 value exceeding 0.80 across all study areas and peaking at 0.90 in the most successful area. On average, there was an 18 % improvement compared to the poorest-performing ML model and a 6 % enhancement compared to the best-performing ML model. The upscaled regional products exhibited superior performance in characterizing cropland NEE patterns compared to pixel-based products. Additionally, we utilized the SHapley Additive exPlanations (SHAP) to assess driver importance, revealing that phenology and radiation had the greatest influence on prediction accuracy, followed by temperature and soil moisture. This study highlights the potential of integrating OBIA techniques with machine learning approaches for upscaling regional cropland NEE, while concurrently reducing estimation uncertainties.

Respiratory viral infection promotes the awakening and outgrowth of dormant metastatic breast cancer cells in lungs.

Breast cancer is the second most common cancer globally. Most deaths from breast cancer are due to metastatic disease which often follows long periods of clinical dormancy1. Understanding the mechanisms that disrupt the quiescence of dormant disseminated cancer cells (DCC) is crucial for addressing metastatic progression. Infection with respiratory viruses (e.g. influenza or SARS-CoV-2) is common and triggers an inflammatory response locally and systemically2,3. Here we show that influenza virus infection leads to loss of the pro-dormancy mesenchymal phenotype in breast DCC in the lung, causing DCC proliferation within days of infection, and a greater than 100-fold expansion of carcinoma cells into metastatic lesions within two weeks. Such DCC phenotypic change and expansion is interleukin-6 (IL-6)-dependent. We further show that CD4 T cells are required for the maintenance of pulmonary metastatic burden post-influenza virus infection, in part through attenuation of CD8 cell responses in the lungs. Single-cell RNA-seq analyses reveal DCC-dependent impairment of T-cell activation in the lungs of infected mice. SARS-CoV-2 infected mice also showed increased breast DCC expansion in lungs post-infection. Expanding our findings to human observational data, we observed that cancer survivors contracting a SARS-CoV-2 infection have substantially increased risks of lung metastatic progression and cancer-related death compared to cancer survivors who did not. These discoveries underscore the significant impact of respiratory viral infections on the resurgence of metastatic cancer, offering novel insights into the interconnection between infectious diseases and cancer metastasis.

Pilot Curriculum for Continued Professional Development of Radiation Oncology Nurses.

Purpose: Limited structured educational programs are available for the continued professional development of radiation oncology nurses. In this study, we evaluated a pilot curriculum focusing on clinical workflow and toxicity management for radiation oncology nurses at a single university-affiliated medical center network. Methods and Materials: Based on a previous multi-institutional needs assessment, a targeted curriculum on clinical workflow and toxicity management was developed, including didactic lectures, written disease-specific toxicity management guidelines, and standardized medication/laboratory order preference lists in the electronic health record. An anonymized survey was circulated to all participants pre- and postcurriculum. The survey was composed of Likert-type subjective questions and 11 objective knowledge-based questions (KBQs). Paired Likert-type data were analyzed using Wilcoxon signed ranks test. Objective question data were compared with the McNamar's mid P test. Results: Thirteen nurses participated in the pilot curriculum and 100% completed pre- and post curriculum surveys. After the didactics, nurses reported a significant increase in their understanding of the responsibilities of a nurse and overall process of care and their ability to explain computed tomography simulation, as well as their ability to assess, manage, and grade radiation-related toxicities (P < .01). There was significant improvement in the percent of correct answers on objective KBQs from a baseline of 52% to 80% after the curriculum (P < .01). Qualitatively, 70% (9/13) of nurses rated the curriculum as "extremely useful" and 30% (4/13) as "quite useful." Conclusions: Our pilot curriculum using a combination of in-person formal didactics, toxicity management guidelines, and electronic health record based order preference lists was well-received and showed promising results on KBQ assessment. This work may be used to guide the development of larger curricula for nurse onboarding and continuing education in a multicenter setting.