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In spring 2021, Nepal underwent a record wildfire season in which active fires were detected at a rate 10 times greater than the 2002–2020 average. Prior to these major wildfire events, the country experienced a prolonged precipitation deficit and extreme drought during the post-monsoon period (starting in October 2020). An analysis using observational, reanalysis, and climate model ensemble data indicates that both climate variability and climate change-induced severe drought conditions were at play. Further analysis of climate model outputs suggests the likely reoccurrence of drought conditions, thus favoring active wildfire seasons in Nepal throughout the twenty-first century. While the inter-model uncertainty is large and direct modeling of wildfire spread and suppression has not been completed, the demonstrated relationship between a drought index (the standardized precipitation and evapotranspiration index) and subsequent fire activity may offer actionable opportunities for forest managers to employ the monitoring and projection of climate anomalies at sub-seasonal to decadal timescales to inform their management strategies for Nepal’s wildlands.

Growing tumors are dynamic and nonlinear ecosystems, wherein cancer cells adapt to their local microenvironment, and these adaptations further modify the environment, inducing more changes. From nascent intraductal neoplasms to disseminated metastatic disease, several levels of evolutionary adaptations and selections occur. Here, we focus on one example of such an adaptation mechanism, namely, "niche construction" promoted by adaptation to acidosis, which is a metabolic adaptation to the early harsh environment in intraductal neoplasms. The avascular characteristics of ductal carcinoma in situ (DCIS) make the periluminal volume profoundly acidic, and cancer cells must adapt to this to survive. Based on discovery proteomics, we hypothesized that a component of acid adaptation involves production of collagen by pre-cancer cells that remodels the extracellular matrix (ECM) and stabilizes cells under acid stress. The proteomic data were surprising as collagen production and deposition are commonly believed to be the responsibility of mesenchymally derived fibroblasts, and not cells of epithelial origin. Subsequent experiments in 3D culture, spinning disk and second harmonic generation microscopy of DCIS lesions in patients' samples are concordant. Collagen production assay by acid-adapted cells in vitro demonstrated that the mechanism of induction involves the RAS and SMAD pathways. Secretome analyses show upregulation of ECM remodeling enzymes such as TGM2 and LOXL2 that are collagen crosslinkers. These data strongly indicate that acidosis in incipient cancers induces collagen production by cancer cells and support the hypothesis that this adaptation initiates a tumor-permissive microenvironment promoting survival and growth of nascent cancers.

Background Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose To standardize a set of 174 radiomic features. Materials and Methods Radiomic features were assessed in three phases. In phase I, 487 features were derived from the basic set of 174 features. Twenty-five research teams with unique radiomics software implementations computed feature values directly from a digital phantom, without any additional image processing. In phase II, 15 teams computed values for 1347 derived features using a CT image of a patient with lung cancer and predefined image processing configurations. In both phases, consensus among the teams on the validity of tentative reference values was measured through the frequency of the modal value and classified as follows: less than three matches, weak; three to five matches, moderate; six to nine matches, strong; 10 or more matches, very strong. In the final phase (phase III), a public data set of multimodality images (CT, fluorine 18 fluorodeoxyglucose PET, and T1-weighted MRI) from 51 patients with soft-tissue sarcoma was used to prospectively assess reproducibility of standardized features. Results Consensus on reference values was initially weak for 232 of 302 features (76.8%) at phase I and 703 of 1075 features (65.4%) at phase II. At the final iteration, weak consensus remained for only two of 487 features (0.4%) at phase I and 19 of 1347 features (1.4%) at phase II. Strong or better consensus was achieved for 463 of 487 features (95.1%) at phase I and 1220 of 1347 features (90.6%) at phase II. Overall, 169 of 174 features were standardized in the first two phases. In the final validation phase (phase III), most of the 169 standardized features could be excellently reproduced (166 with CT; 164 with PET; and 164 with MRI). Conclusion A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Kuhl and Truhn in this issue.

Historically, the precipitation trend over the past few decades in the Contiguous United States (CONUS) exhibits a "Dry‐West Wet‐East" pattern; this is manifested by recent droughts/floods in the western/eastern US. However, it remains elusive what atmospheric phenomenon has potentially driven such a remarkable, and impactful precipitation pattern. Here we found that a coupled climate mode—the Pacific Meridional Mode (PMM) exerted strong impacts on the precipitation pattern over the CONUS during the summer season. We discovered a significant association between the PMM index and precipitation across the majority of the CONUS; this was manifested as a zonal dipole pattern—negative correlations in the western U.S. along with positive correlations in the eastern and central U.S. Overall, the physical mechanisms based on observations were supported by using Atmospheric Model Intercomparison Project simulations available from the Coupled Model Intercomparison Project Phase 6. Plain Language Summary: Historically, the Contiguous United States (CONUS) was parched in the West and soaked in the East. Despite the importance of this distinct spatial pattern of precipitation variability, the drivers of this hydroclimatic phenomenon remain elusive. Therefore, there is big knowledge gap in understanding the zonal precipitation pattern during the historical period. Here we find that the Pacific Meridional Mode (PMM) can exert strong impacts on the zonal precipitation pattern over the CONUS during the summer season. We discovered a significant association between the PMM index and the precipitation across the majority of the CONUS; this was manifested as a zonal dipole pattern—negative correlations in the western U.S. along with positive correlations in the eastern and central U.S. Overall, the physical mechanisms based on observations were supported by the Atmospheric Model Intercomparison Project experiments of the Coupled Model Intercomparison Project (Phase 6). Our research results explain in large part the zonal precipitation pattern ("Dry‐West Wet‐East") in the CONUS, and perhaps more importantly, the viability of the PMM being used as a potential predictor/indicator for summertime precipitation over the U.S. Key Points: The Pacific Meridional Mode (PMM) exerted strong impacts on the precipitation pattern over the CONUS during the summer seasonThe modulation on precipitation is manifested as a zonal dipole pattern, tied to teleconnections associated PMM sea‐surface temperature anomaliesThe physical mechanisms based on observations were supported by CMIP6 climate model simulations [ABSTRACT FROM AUTHOR]

Recent reports indicate that hypoxia influences the circadian clock through the transcriptional activities of hypoxia-inducible factors (HIFs) at clock genes. Unexpectedly, we uncover a profound disruption of the circadian clock and diurnal transcriptome when hypoxic cells are permitted to acidify to recapitulate the tumor microenvironment. Buffering against acidification or inhibiting lactic acid production fully rescues circadian oscillation. Acidification of several human and murine cell lines, as well as primary murine T cells, suppresses mechanistic target of rapamycin complex 1 (mTORC1) signaling, a key regulator of translation in response to metabolic status. We find that acid drives peripheral redistribution of normally perinuclear lysosomes away from perinuclear RHEB, thereby inhibiting the activity of lysosome-bound mTOR. Restoring mTORC1 signaling and the translation it governs rescues clock oscillation. Our findings thus reveal a model in which acid produced during the cellular metabolic response to hypoxia suppresses the circadian clock through diminished translation of clock constituents.

PurposeTo study the variability in volume change estimates of pulmonary nodules due to segmentation approaches used across several algorithms and to evaluate these effects on the ability to predict nodule malignancy.MethodsWe obtained 100 patient image datasets from the National Lung Screening Trial (NLST) that had a nodule detected on each of two consecutive low dose computed tomography (LDCT) scans, with an equal proportion of malignant and benign cases (50 malignant, 50 benign). Information about the nodule location for the cases was provided by a screen capture with a bounding box and its axial location was indicated. Five participating quantitative imaging network (QIN) institutions performed nodule segmentation using their preferred semi-automated algorithms with no manual correction; teams were allowed to provide additional manually corrected segmentations (analyzed separately). The teams were asked to provide segmentation masks for each nodule at both time points. From these masks, the volume was estimated for the nodule at each time point; the change in volume (absolute and percent change) across time points was estimated as well. We used the concordance correlation coefficient (CCC) to compare the similarity of computed nodule volumes (absolute and percent change) across algorithms. We used Logistic regression model on the change in volume (absolute change and percent change) of the nodules to predict the malignancy status, the area under the receiver operating characteristic curve (AUROC) and confidence intervals were reported. Because the size of nodules was expected to have a substantial effect on segmentation variability, analysis of change in volumes was stratified by lesion size, where lesions were grouped into those with a longest diameter of

Radiomics is to provide quantitative descriptors of normal and abnormal tissues during classification and prediction tasks in radiology and oncology. Quantitative Imaging Network members are developing radiomic "feature" sets to characterize tumors, in general, the size, shape, texture, intensity, margin, and other aspects of the imaging features of nodules and lesions. Efforts are ongoing for developing an ontology to describe radiomic features for lung nodules, with the main classes consisting of size, local and global shape descriptors, margin, intensity, and texture-based features, which are based on wavelets, Laplacian of Gaussians, Law's features, gray-level co-occurrence matrices, and run-length features. The purpose of this study is to investigate the sensitivity of quantitative descriptors of pulmonary nodules to segmentations and to illustrate comparisons across different feature types and features computed by different implementations of feature extraction algorithms. We calculated the concordance correlation coefficients of the features as a measure of their stability with the underlying segmentation; 68% of the 830 features in this study had a concordance CC of ≥0.75. Pairwise correlation coefficients between pairs of features were used to uncover associations between features, particularly as measured by different participants. A graphical model approach was used to enumerate the number of uncorrelated feature groups at given thresholds of correlation. At a threshold of 0.75 and 0.95, there were 75 and 246 subgroups, respectively, providing a measure for the features' redundancy.

The polarization state of transionospheric high frequency (HF) radio waves can be determined using the crossed-dipole antennas of the Radio Receiver Instrument (RRI) onboard Enhanced Polar Outflow Probe (e-POP) on the CAScade, Smallsat, and IOnospheric Polar Explorer/Swarm-E satellite. Coordinated experiments between ground radars and RRI showed that the radio waves have high ellipticity angles (elliptical or circular polarization) for propagation direction 6°-25° from the perpendicular direction to the local geomagnetic field. However, from magnetoionic theory and a typical assumption of roughly equal power in the O- and X-modes, radio waves can have high ellipticity angles only when the propagation direction is within 10° of perpendicularity. This investigation uses coordinated experiments between the Saskatoon SuperDARN radar and RRI. Magnetoionic modeling reveals that the relative strengths of the O- and X-modes for the HF radio waves transmitted from the Saskatoon SuperDARN change significantly poleward of the radar. Differences in the relative power between the two wave modes were found to significantly modify the polarization state of radio waves, and govern the sense of rotation of the wave. Even a relatively modest 2-5 dB power difference in the X-mode over the O-mode was found to result in unexpected observations of circularly polarized radio waves at aspect angles 6°-10° from perpendicular, and unexpected elliptically polarized waves observed at aspect angles more than 10° from perpendicular. Therefore, a combination of RRI observations and modeling, which accounts for relative differences in the O- and X-mode powers, was used here to better understand the unexpected observations of polarization states of transionospheric radio waves. [ABSTRACT FROM AUTHOR]

Background.  The epidemic of sexually transmitted hepatitis C virus (HCV) infection among human immunodeficiency virus (HIV)-infected men who have sex with men (MSM) has been documented for over a decade. Despite this, there is no consensus as to the risk factors for sexual acquisition of HCV in these men. Methods.  We obtained paired semen and blood samples at 2-week intervals from HIV-infected MSM with recent and chronic HCV infection and quantified HCV in semen. Results.  Hepatitis C virus was quantified in 59 semen specimens from 33 men. Hepatitis C virus was shed in 16 (27%) of semen specimens from 11 (33%) of the men. Median HCV viral load (VL) in semen was 1.49 log10 IU/mL. Hepatitis C virus VL in blood was significantly higher at the time of HCV shedding in semen than when HCV shedding in semen was not detected (P = .002). Furthermore, there was a significant correlation between the HCV VL in blood and semen overall (rs = 0.41; P = .001), and in the subgroup with recent HCV infection (rs = 0.37; P = .02), but not in the subgroup with chronic HCV infection (rs = 0.34; P = .1). Conclusions.  One third of HIV-infected MSM coinfected with HCV shed HCV into their semen. Based on the HCV VL in semen in this study, an average ejaculate would deliver up to 6630 IU of virus into the rectum of the receptive partner. Therefore, our data strongly support that condoms should be used during anal intercourse among MSM to prevent transmission of HCV.

As anticancer therapies designed to target specific molecular pathways have been developed, it has become critical to develop methods to assess the response induced by such agents. Although traditional, anatomic CT, and MRI examinations are useful in many settings, increasing evidence suggests that these methods cannot answer the fundamental biologic and physiologic questions essential for assessment and, eventually, prediction of treatment response in the clinical trial setting, especially in the critical period soon after treatment is initiated. To optimally apply advances in quantitative imaging methods to trials of targeted cancer therapy, new infrastructure improvements are needed that incorporate these emerging techniques into the settings where they are most likely to have impact. In this review, we first elucidate the needs for therapeutic response assessment in the era of molecularly targeted therapy and describe how quantitative imaging can most effectively provide scientifically and clinically relevant data. We then describe the tools and methods required to apply quantitative imaging and provide concrete examples of work making these advances practically available for routine application in clinical trials. We conclude by proposing strategies to surmount barriers to wider incorporation of these quantitative imaging methods into clinical trials and, eventually, clinical practice. Our goal is to encourage and guide the oncology community to deploy standardized quantitative imaging techniques in clinical trials to further personalize care for cancer patients and to provide a more efficient path for the development of improved targeted therapies.

Lung cancer screening identifies cancers with heterogeneous behaviors. Some lung cancers will be identified among patients who had prior negative CT screens and upon follow-up scans develop a de novo nodule that was determined to be cancerous. Other lung cancers will be identified among patients who had one or more prior stable positive scans that were not determined to be lung cancer (indeterminate pulmonary nodules), but in follow-up scans was diagnosed with an incidence lung cancer. Using data from the CT arm of the National Lung Screening Trial, this analysis investigated differences in patient characteristics and survival endpoints between prevalence-, interval-, and screen-detected lung cancers, characterized based on sequence of screening results. Lung cancers immediately following a positive baseline (T0), and prior to the T1 screen, formed the prevalence cohort. Interval cancers were diagnosed following a negative screen at any time point prior to the next screening round. Two cohorts of screen-detected lung cancers (SDLC) were identified that had a baseline positive screen that was that was not determined to be lung cancer (i.e., an indeterminate pulmonary nodule), but in follow-up scans was diagnosed with an incidence lung cancer 12 (SDLC1) or 24 (SDLC2) months later. Two other incidence cohorts had screen-detected lung cancers that had baseline negative screen and upon follow-up scans developed a de novo nodule determined to be cancerous at 12 (SDLC3) or 24 (SDLC4) months later. Differences in patient characteristics, progression-free survival (PFS), and overall survival (OS) were assessed. The lung cancer-specific death rate was higher for SDLC3/SDLC4 compared to SDLC1/SDLC2 lung cancers (136.6/1,000 person-years vs. 71.3/1,000 person-years, P < 0.001). Moreover, PFS and OS were significantly lower for SDLC3/SDLC4 compared to SDLC1/SDLC2 (P < 0.004; P < 0.002, respectively). The findings were consistent when stratified by stage and histology. Multivariable Cox proportional models revealed that the SDLC3/SDLC4 case groups were associated with significantly poorer PFS (HR = 1.89; 95% CI 1.31-2.74) and OS (HR = 1.80; 95% CI 1.21-2.67) compared to SDLC1/SDLC2 lung cancers (HR = 1.00). Lung cancer patients who develop a de novo nodule that determined to be cancerous (i.e., at least one negative CT screen prior to cancer diagnosis) had poorer survival outcomes compared to patients who had at least one positive screen prior to cancer diagnosis. As such, the observation that de novo screen-detected are associated with poorer survival could be attributed to faster growing, more aggressive cancers that arose from a lung environment previously lacking focal abnormalities.

Author(s): Sultan Damgaci [sup.1] [sup.2], Pedro M. Enriquez-Navas [sup.1], Shari Pilon-Thomas [sup.3] [sup.4], Albert Guvenis [sup.2], Robert J. Gillies [sup.1] [sup.5], Arig Ibrahim-Hashim [sup.1] Author Affiliations: (1) Department of Cancer [...]

We present two methods for improved calibration of multi-point electron density measurements from incoherent scatter radars (ISR). They are based on the well-established Flatfield correction method used in imaging and photography, where we exploit the analogy between independent measurements in separate pixels in one image sensor and multi-beam radar measurements. Applying these correction methods adds to the current efforts of estimating the magic constant or system constant made for the calibration of multi-point radars, increasing data quality and usability by correcting for variable, unaccounted, and unpredictable variations in system gain. This second-level calibration is especially valuable for studies of plasma patches, irregularities, turbulence, and other research where inter-beam changes and fluctuations of electron density are of interest. The methods are strictly based on electron density data measured by the individual radar and require no external input. This is of particular interest when independent measurements of electron densities for calibration are available only in one pointing direction or not at all. A correction factor is estimated in both methods, which is subsequently used to scale the electron density measurements of a multi-beam ISR experiment run on a phased array radar such as RISR-N, RISR-C, PFISR, or the future EISCAT3D radar. This procedure could improve overall data quality if used as part of the data-processing chain for multi-beam ISRs, both for existing data and for future experiments on new multi-beam radars. [ABSTRACT FROM AUTHOR]

To investigate the transition from non-cancerous to metastatic from a physical sciences perspective, the Physical Sciences-Oncology Centers (PS-OC) Network performed molecular and biophysical comparative studies of the non-tumorigenic MCF-10A and metastatic MDA-MB-231 breast epithelial cell lines, commonly used as models of cancer metastasis. Experiments were performed in 20 laboratories from 12 PS-OCs. Each laboratory was supplied with identical aliquots and common reagents and culture protocols. Analyses of these measurements revealed dramatic differences in their mechanics, migration, adhesion, oxygen response, and proteomic profiles. Model-based multi-omics approaches identified key differences between these cells' regulatory networks involved in morphology and survival. These results provide a multifaceted description of cellular parameters of two widely used cell lines and demonstrate the value of the PS-OC Network approach for integration of diverse experimental observations to elucidate the phenotypes associated with cancer metastasis.

To investigate the transition from non-cancerous to metastatic from a physical sciences perspective, the Physical Sciences-Oncology Centers (PS-OC) Network performed molecular and biophysical comparative studies of the non-tumorigenic MCF-10A and metastatic MDA-MB-231 breast epithelial cell lines, commonly used as models of cancer metastasis. Experiments were performed in 20 laboratories from 12 PS-OCs. Each laboratory was supplied with identical aliquots and common reagents and culture protocols. Analyses of these measurements revealed dramatic differences in their mechanics, migration, adhesion, oxygen response, and proteomic profiles. Model-based multi-omics approaches identified key differences between these cells' regulatory networks involved in morphology and survival. These results provide a multifaceted description of cellular parameters of two widely used cell lines and demonstrate the value of the PS-OC Network approach for integration of diverse experimental observations to elucidate the phenotypes associated with cancer metastasis.