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Patients were hospitalized for acute care (n = 79, 26%), ICU-level care (n = 28, 9%), or died (n = 21, 7%) due to COVID-19. Patients with ≥2 comorbidities were more likely to require acute care (odds ratio [OR] 2.09 [95% confidence interval (CI), 1.23-3.55]). Cough was identified as a significant predictor of ICU hospitalization (OR 2.16 [95% CI, 1.03-4.57]). Importantly, mortality was associated with an active cancer diagnosis (OR 3.64 [95% CI, 1.40-9.5]) or advanced age (OR 3.86 [95% CI, 1.2-12.44]).

This study observed that patients with active cancer or advanced age are at an increased risk of death from COVID-19. These study observations can inform risk counseling related to COVID-19 for patients with a cancer diagnosis.

This study observed that patients with active cancer or advanced age are at an increased risk of death from COVID-19. These study observations can inform risk counseling related to COVID-19 for patients with a cancer diagnosis.Chlorophyll (Chl) serves a number of essential functions, capturing and converting light energy as a component of photosystem supercomplexes. Chl degradation during leaf senescence is also required for adequate degeneration of chloroplasts and salvaging of nutrients from senescent leaves. In this study, we performed genetic analysis to determine the functions of BALANCE of CHLOROPHYLL METABOLISM1 (BCM1) and BCM2, which control Chl levels by regulating synthesis and degradation, and STAY-GREEN (SGR)1 (also known as NON-YELLOWING1 [NYE1]) and SGR2, which encode Mg-dechelatase and catalyze Chl a degradation in Arabidopsis (Arabidopsis thaliana). Analysis of bcm1 bcm2 revealed that both BCM1 and BCM2 are involved in the regulation of Chl levels in presenescent leaves and Chl degradation in senescing leaves. Analysis of bcm1 bcm2 nye1 nye2 suggested that BCMs repress Chl-degrading activity in both presenescent and senescing leaves by regulating SGR activity. Furthermore, transactivation analysis and chromatin immunoprecipitation (ChIP) assay revealed that GOLDEN2-LIKE1 (GLK1), a central transcription factor regulating the expression of genes encoding photosystem-related proteins, such as light-harvesting Chl a/b-binding proteins (LHCPs), directly regulates the transcription of BCM1. LHCPs are stabilized by Chl binding, suggesting that GLKs control the amount of LHCP through transcriptional and post-translational regulation via BCM-mediated Chl-level regulation. Meanwhile, we generated a mutant of the BCM ortholog in lettuce (Lactuca sativa) by genome editing and found that it showed an early yellowing phenotype, but only a slight reduction in Chl in presenescent leaves. Thus, this study revealed a conserved but slightly diversified regulation of Chl and LHCP levels via the GLK-BCM pathway in eudicots.Phosphatidylinositol 4-phosphate 5-kinase (PIP5K) is involved in regulating various cellular processes through the signaling function of its product, phosphatidylinositol (4,5)-bisphosphate. Higher plants encode a large number of PIP5Ks forming distinct clades in their molecular phylogenetic tree. Although biological functions of PIP5K genes have been analyzed intensively in Arabidopsis thaliana, it remains unclear how those functions differ across clades of paralogs. We performed comparative functional analysis of the Arabidopsis genes encoding PIP5K1, PIP5K2 and PIP5K3, of which the first two and the last belong to closely related but distinct clades, to clarify their conserved and/or differentiated functions. Genetic analysis with their single and multiple mutants revealed that PIP5K1 and PIP5K3 have non-overlapping functions, with the former in total plant growth and the latter in root hair elongation, whereas PIP5K2 redundantly functions in both phenomena. This pattern of functional redundancy is explainable in terms of the overlapping pattern of their promoter activities. In transformation rescue experiments, PIP5K3 promoter-directed PIP5K1-YFP completely rescued the short-root-hair phenotype of pip5k3. However, PIP5K3-YFP could substitute for PIP5K1-YFP only partially in rescuing the severe dwarfism of pip5k1pip5k2 when directed by the PIP5K1 promoter. Phylogenetic analysis of angiosperm PIP5Ks revealed that PIP5K3 orthologs have a faster rate of diversification in their amino-acid sequences compared with PIP5K1/2 orthologs after they arose through a eudicot-specific duplication event. These findings suggest that PIP5K3 specialized to promote root hair elongation and lost some of the protein-encoded functions retained by PIP5K1 and PIP5K2, whereas PIP5K1 differentiated from PIP5K2 only in its promoter-directed expression pattern.Traditionally, lust and pride have been considered pleasurable, yet sinful in the West. Conversely, guilt is often considered aversive, yet valuable. These emotions illustrate how evaluations about specific emotions and beliefs about their hedonic properties may often diverge. Evaluations about specific emotions may shape important aspects of emotional life (e.g. in emotion regulation, emotion experience and acquisition of emotion concepts). Yet these evaluations are often understudied in affective neuroscience. Prior work in emotion regulation, affective experience, evaluation/attitudes and decision-making point to anterior prefrontal areas as candidates for supporting evaluative emotion knowledge. Thus, we examined the brain areas associated with evaluative and hedonic emotion knowledge, with a focus on the anterior prefrontal cortex. Participants (N = 25) made evaluative and hedonic ratings about emotion knowledge during functional magnetic resonance imaging (fMRI). We found that greater activity in the medial prefrontal cortex (mPFC), ventromedial PFC (vmPFC) and precuneus was associated with an evaluative (vs hedonic) focus on emotion knowledge. Our results suggest that the mPFC and vmPFC, in particular, may play a role in evaluating discrete emotions.

The treatment responses of immune checkpoint inhibitors in metastatic renal cell carcinoma (mRCC) vary, requiring reliable prognostic biomarkers. We assessed the prognostic ability of computed tomography (CT) texture analysis in patients with mRCC treated with programmed death receptor-1 (PD-1)/programmed death ligand-1 (PD-L1) inhibitors.

Sixty-eight patients with mRCC treated with PD-1/PD-L1 inhibitors between 2012 and 2019 were revaluated. Using baseline and first follow-up CT, baseline and follow-up texture models were developed to predict overall survival (OS) and progression-free survival (PFS) using least absolute shrinkage and selection operator Cox-proportional hazards analysis. Patients were divided into high-risk or low-risk group, and the survival difference was assessed using Kaplan-Meier and log-rank test. Multivariable Cox models were constructed by including only the clinical variables (clinical models) and by combining the clinical variables and the texture models (combined clinical-texture models), and their predictive performance was evaluated using Harrell's C-index.

The baseline texture models distinguished longer- and shorter-term survivors for both OS (median, 60.1 vs. 17.0 months; P = .048) and PFS (5.2 vs. 2.8 months; P = .003). The follow-up texture models distinguished longer- and shorter-term overall survivors (40.3 vs. 15.2 months; P = .008) but not for PFS (5.0 vs. Didox solubility dmso 3.6 months; P = .25). The combined clinical-texture model outperformed the clinical model in both predicting the OS (C-index, 0.70 vs. 0.63; P = .03) and PFS (C-index, 0.63 vs. 0.55; P = .04).

CT texture analysis performed at baseline and early after starting PD-1/PD-L1 inhibitors is associated with clinical outcomes of patients with mRCC.

CT texture analysis performed at baseline and early after starting PD-1/PD-L1 inhibitors is associated with clinical outcomes of patients with mRCC.

Cardiovascular immune-related adverse events (CV-irAEs) associated with immune checkpoint inhibitors (ICIs) may have been underreported given that most previous reports were retrospective. We aimed to evaluate the incidence, clinical characteristics, and predictors of CV-irAEs and determine the feasibility of serial cardiac monitoring using a combination of B-type natriuretic peptide, cardiac troponin T, and electrocardiogram for the prediction of future symptomatic (grade ≥2) CV-irAEs.

This was a prospective observational study that included 129 consecutive patients with non-small-cell lung cancer who received ICI monotherapy at a single center. Serial cardiac monitoring was performed during ICI monotherapy.

A total of 35 (27%) patients developed any grade ≥1 CV-irAEs with a median time of onset of 72 (interquartile range 44-216) days after ICI treatment initiation. Multivariate Fine-Gray regression analysis showed that prior acute coronary syndrome (adjusted hazard ratio [HR] 3.15 (95% [CI], 2.03-4.91), prior heart failure hospitalization (adjusted HR 1.65 [95% CI, 1.17-2.33]), and achievement of disease control (adjusted HR 1.91, [95% CI, 1.16-3.14]) were significantly associated with grade ≥1 CV-irAEs. Serial cardiac monitoring revealed that patients with preceding grade 1 CV-irAEs were associated with a significantly higher risk of onset of grade ≥2 CV-irAEs compared with those without preceding grade 1 CV-irAEs (HR 6.17 [95% CI, 2.97-12.83]).

CV-irAEs were more common than previously recognized and have several predictors. Moreover, serial cardiac monitoring may be feasible for the prediction of future grade ≥2 CV-irAEs.

CV-irAEs were more common than previously recognized and have several predictors. Moreover, serial cardiac monitoring may be feasible for the prediction of future grade ≥2 CV-irAEs.The recent, rapid advances in immuno-oncology have revolutionized cancer treatment and spurred further research into tumor biology. Yet, cancer patients respond variably to immunotherapy despite mounting evidence to support its efficacy. Current methods for predicting immunotherapy response are unreliable, as these tests cannot fully account for tumor heterogeneity and microenvironment. An improved method for predicting response to immunotherapy is needed. Recent studies have proposed radiomics-the process of converting medical images into quantitative data (features) that can be processed using machine learning algorithms to identify complex patterns and trends-for predicting response to immunotherapy. Because patients undergo numerous imaging procedures throughout the course of the disease, there exists a wealth of radiological imaging data available for training radiomics models. And because radiomic features reflect cancer biology, such as tumor heterogeneity and microenvironment, these models have enormous potential to predict immunotherapy response more accurately than current methods. Models trained on preexisting biomarkers and/or clinical outcomes have demonstrated potential to improve patient stratification and treatment outcomes. In this review, we discuss current applications of radiomics in oncology, followed by a discussion on recent studies that use radiomics to predict immunotherapy response and toxicity.

Polypharmacy is prevalent in older adults starting cancer treatment and associated with potentially inappropriate medications (PIM), potential drug-drug interactions (DDI), and drug-cancer treatment interactions (DCI). For a large cohort of vulnerable older adults with advanced cancer starting treatment, we describe patterns of prescription and nonprescription medication usage, the prevalence of PIM, and the prevalence, severity, and type of DDI/DCI.

This secondary analysis used baseline data from a randomized study enrolling patients aged ≥70 years with advanced cancer starting a new systemic cancer treatment (University of Rochester Cancer Center [URCC] 13059; PI Mohile). PIM were categorized using 2019 Beers criteria and Screening Tool of Older Persons' Prescriptions. Potential DDI/DCI were evaluated using Lexi-Interact Online. Medication classification followed the World Health Organization Anatomical Therapeutic Chemical system. Bivariate associations were evaluated between sociodemographic and geriatric assessment (GA) measures and medication measures.