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The prevalence of obesity, defined as the body mass index (BMI) ≥ 30 kg/m2, has reached epidemic levels. Obesity is associated with an increased risk of various cancers, including gastrointestinal ones. Recent evidence has suggested that obesity disproportionately impacts males and females with cancer, resulting in varied transcriptional and metabolic dysregulation. This study aimed to elucidate the differences in the metabolic milieu of adenocarcinomas of the gastrointestinal (GI) tract both related and unrelated to sex in obesity. To demonstrate these obesity and sex-related effects, we utilized three primary data sources: serum metabolomics from obese and non-obese patients assessed via the Biocrates MxP Quant 500 mass spectrometry-based kit, the ORIEN tumor RNA-sequencing data for all adenocarcinoma cases to assess the impacts of obesity, and publicly available TCGA transcriptional analysis to assess GI cancers and sex-related differences in GI cancers specifically. We applied and integrated our unique transcriptional metabolic pipeline in combination with our metabolomics data to reveal how obesity and sex can dictate differential metabolism in patients. Differentially expressed genes (DEG) analysis of ORIEN obese adenocarcinoma as compared to normal-weight adenocarcinoma patients resulted in large-scale transcriptional reprogramming (4029 DEGs, adj. p < 0.05 and |logFC| > 0.58). Gene Set Enrichment and metabolic pipeline analysis showed genes enriched for pathways relating to immunity (inflammation, and CD40 signaling, among others) and metabolism. Specifically, we found alterations to steroid metabolism and tryptophan/kynurenine metabolism in obese patients, both of which are highly associated with disease severity and immune cell dysfunction. These findings were further confirmed using the TCGA colorectal adenocarcinoma (CRC) and esophageal adenocarcinoma (ESCA) data, which showed similar patterns of increased tryptophan catabolism for kynurenine production in obese patients. These patients further showed disparate alterations between males and females when comparing obese to non-obese patient populations. Alterations to immune and metabolic pathways were validated in six patients (two obese and four normal weight) via CD8+/CD4+ peripheral blood mononuclear cell RNA-sequencing and paired serum metabolomics, which showed differential kynurenine and lipid metabolism, which corresponded with altered T-cell transcriptome in obese populations. Overall, obesity is associated with differential transcriptional and metabolic programs in various disease sites. Further, these alterations, such as kynurenine and tryptophan metabolism, which impact both metabolism and immune phenotype, vary with sex and obesity together. This study warrants further in-depth investigation into obesity and sex-related alterations in cancers that may better define biomarkers of response to immunotherapy.

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.

IntroductionThe incidence of obesity, a condition characterized by systemic chronic inflammation, has reached pandemic proportions and is a poor prognostic factor in many pathologic states. However, its role on immune parameters has been diverse and at times contradictory. We have previously demonstrated that obesity can result in what has been called the "obesity paradox" which results in increased T cell exhaustion, but also greater efficacy of immune checkpoint blockade in cancer treatment.MethodsThe role of obesity, particularly in the context of aging, has not been robustly explored using preclinical models. We therefore evaluated how age impacts the immune environment on T cell development and function using diet-induced obese (DIO) mice.ResultsWe observed that DIO mice initially displayed greater thymopoiesis but then developed greater thymic involution over time compared to their lean counterparts. Both aging and obesity resulted in increased T cell memory conversion combined with increased expression of T cell exhaustion markers and Treg expansion. This increased T cell immunosuppression with age then resulted in a loss of anti-tumor efficacy by immune checkpoint inhibitors (ICIs) in older DIO mice compared to the younger DIO counterparts.DiscussionThese results suggest that both aging and obesity contribute to T cell dysfunction resulting in increased thymic involution. This combined with increased T cell exhaustion and immunosuppressive parameters affects immunotherapy efficacy reducing the advantage of obesity in cancer immunotherapy responses.

The role of immune checkpoint inhibitors for patients with gastroesophageal cancer with liver metastasis remains unclear. Our objective was to investigate whether immune checkpoint inhibitors are beneficial in patients with gastroesophageal cancer with liver metastasis. We searched PubMed, Embase, European Society for Medical Oncology, and American Society of Clinical Oncology meeting abstracts for phase 3 randomized clinical trials testing immune checkpoint inhibitors in metastatic/advanced gastroesophageal cancer from 2017 to 2023. Seven studies were included. Overall survival was similar among all patients (hazard ratio [HR] = 0.72 [95% confidence interval (CI) = 0.67 to 0.77], P  < .001), in patients without liver metastases (HR = 0.73 [95% CI = 0.67 to 0.81], P  < .001, I 2 = 0.0%), and in patients with liver metastases (HR = 0.74 [95% CI = 0.67 to 0.81], P  < .001, I 2 = 0.0%). Progression-free survival was also similar among all patients (HR = 0.63 [95% CI = 0.57 to 0.70], P  < .001), in patients without liver metastases (HR = 0.62 [95% CI = 0.51 to 0.76], P  < .001), and in patients with liver metastases (HR = 0.66 [95% CI = 0.57 to 0.76], P  < .001). Immune checkpoint inhibitors showed no difference in benefit in patients with gastroesophageal cancer, regardless of liver metastasis. Future studies could focus on deciphering the tumor microenvironment of liver metastasis as an area of translational research. [ABSTRACT FROM AUTHOR]

The recent successes of immunotherapy have shifted the paradigm in cancer treatment, but because only a percentage of patients are responsive to immunotherapy, it is imperative to identify factors impacting outcome. Obesity is reaching pandemic proportions and is a major risk factor for certain malignancies, but the impact of obesity on immune responses, in general and in cancer immunotherapy, is poorly understood. Here, we demonstrate, across multiple species and tumor models, that obesity results in increased immune aging, tumor progression and PD-1-mediated T cell dysfunction which is driven, at least in part, by leptin. However, obesity is also associated with increased efficacy of PD-1/PD-L1 blockade in both tumor-bearing mice and clinical cancer patients. These findings advance our understanding of obesity-induced immune dysfunction and its consequences in cancer and highlight obesity as a biomarker for some cancer immunotherapies. These data indicate a paradoxical impact of obesity on cancer. There is heightened immune dysfunction and tumor progression but also greater anti-tumor efficacy and survival after checkpoint blockade which directly targets some of the pathways activated in obesity.

Background/Objectives: Recent epidemiological studies have revealed an upward trend in young-onset colorectal cancer (YOCRC) overall, whereas specific data on young-onset colorectal neuroendocrine neoplasms (YONEN) remain limited. This study investigated the demographic characteristics and survival trends in YONEN and compared these with those of young-onset colorectal adenocarcinoma (YOADC), the most common histologic subtype of YOCRC. Methods: A retrospective analysis was conducted from 2000 to 2019 using the Surveillance, Epidemiology, and End Results (SEER) database. Survival outcomes were assessed using univariate and multivariable Cox proportional models, with demographic differences evaluated via Wilcoxon rank sum and Chi-square tests. Results: Out of 61,705 patients aged 20–49 with colorectal cancer, 8% had NEN, and 92% had adenocarcinoma. The YONEN cohort had a higher proportion of Black patients and a lower proportion of White patients than the YOADC cohort (21% vs. 13% and 44% vs. 57%, respectively). NEN was more commonly found in the rectum (79%), and adenocarcinoma was mostly colonic (57%) in origin. YONEN patients had better survival than YOADC patients. Multivariate analysis in YONEN patients revealed that Hispanic patients had better overall survival compared to White patients (HR 0.67, 95% CI 0.47–0.95, p = 0.024). Conclusions: Racial disparities should be investigated further to aid in policymaking and targeted interventions. [ABSTRACT FROM AUTHOR]

Background: Immune checkpoint inhibitors (ICIs) have revolutionized cancer care, with increasing data demonstrating improved survival outcomes using ICIs among patients with advanced gastroesophageal cancer (GEC). ICIs are also associated with a lower incidence of grade ≥ 3 adverse events (AEs) compared to chemotherapy, suggesting that ICIs may have favorable effects on health-related quality of life (HRQoL). This meta-analysis sought to evaluate the effects of ICIs on the HRQoL of patients with advanced GEC. Methods: We conducted an online bibliographic search on Medline via PubMed using MeSH-based terms to retrieve randomized controlled trials (RCTs) that evaluated the effects of ICIs on HRQoL in patients with advanced GEC (we searched for all studies between 2018 and 2021). We included RCTs that incorporated ICIs as part of the intervention arm either as monotherapy (first or second line) or as a combination therapy (first-line) with another ICI or chemotherapy. We combined the HRQoL measures into a meta-analysis using standard random effects models, from which estimates of the average mean difference (MD) were obtained with 95% confidence intervals. We assessed the heterogeneity of the study outcomes using the Q and I2 statistics. Results: We identified 11 phase 3 RCTs that met the inclusion criteria, with a mean enrollment of 820 patients. Eight RCTs used an ICI plus chemotherapy combination in the intervention arm, three had ICIs as monotherapy, and one had doublet ICI therapy in the intervention arm. All RCTs used chemotherapy for the control arm. Collectively, the trials reported 37 HRQoL measures using five different HRQoL tools. The pooled analysis favored the intervention over the control arm in terms of the Functional Assessment of Cancer Therapy-Esophageal (FACT-E) scores [MD 2.7 (95% CI 0.1 to 5.3), p < 0.041]. In a subgroup analysis of eight RCTs comparing combination therapy with ICIs plus chemotherapy versus chemotherapy alone, the effect estimates favored the ICI arm regarding the FACT-E [MD 2.7 (95% CI 0.1 to 5.3), p < 0.041] and the EORTC QLQ-OES18 pain scale [MD −2.2 (95% CI −4.3 to −0.2), p < 0.030]. Likewise, the effect estimates favored the ICI monotherapy arm over the chemotherapy arm regarding the QLQ-STO22 hair loss subscale [MD −23.2 (95% CI −29.7 to −16.7), p < 0.001], QLQ-STO22 dysphagia subscale [MD 6.7 (95% CI 1.7 to 11.7), p = 0.009], EQ-5D pain scale [MD 6.9 (95% CI 2.9 to 10.9), p < 0.001], and QLQ-OES18 saliva subscale [MD 5.8 (95% CI 0.1 to 11.6), p = 0.046]. Conclusions: In this meta-analysis, we found that the inclusion of ICIs as a first-line treatment for advanced GEC yielded better HRQoL outcomes than chemotherapy alone. Further research on the impact of ICIs on HRQoL is needed, with increasing evidence that ICIs improve the survival outcomes in patients with advanced GEC. [ABSTRACT FROM AUTHOR]

PURPOSE: Early-onset colorectal cancer (EOCRC), defined as CRC diagnosed before age 50 years, has increased significantly worldwide. The majority of EOCRCs do not appear to be driven by genetic factors and may be influenced by environmental factors. We hypothesized that sociodemographic disparities exist in EOCRC. The purpose was of the study was to examine the geographic disparities in patients with EOCRC. METHODS: We retrospectively examined the SEER database from 1976 to 2016 to examine the geographic disparities in EOCRC. A total of 73,378 patients with EOCRC were included in the analysis. We performed univariate and multivariable analyses to evaluate overall survival (OS) and disease-specific survival (DSS). Sociodemographic factors, including the location of residence (metropolitan areas [MA] or rural areas [RA]), sex, race, insurance status, and marital status, were included in the statistical analysis. RESULTS: The incidence and mortality rates were consistently higher in RA versus MA during the study period. Multivariable analysis showed that patients living in RA had worse OS (hazard ratio [HR], 1.14; P <.01) and DSS (HR, 1.15; P <.001) compared with those living in MA. Similarly, non-Hispanic Black ethnicity and uninsured patients had significantly worse survival when compared with non-Hispanic White and insured patients, respectively. Married status showed better survival outcomes. CONCLUSION: Patients with EOCRC living in RA have worse outcomes. Understanding the mechanisms behind such socioeconomic disparities is important so that future studies can reduce these disparities. We highlighted geographic disparities in YOCRC pts and found worse outcomes for YOCRC pts in rural versus urban areas. [ABSTRACT FROM AUTHOR]

Simple Summary: Recent animal studies have shown a correlation between environmental temperature and tumor growth. Based on these studies, we hypothesized that esophageal cancer and gastric cancer patients living in warmer climates have improved survival as compared to patients living in colder climates. We conducted a study using the SEER (Surveillance, Epidemiology, and End Results) database and analyzed the cancer outcomes with the county-level average annual temperature in which those patients resided. We analyzed 17,408 esophageal cancer and 20,533 gastric cancer patients. We noted for the first time that higher environmental temperatures were associated with significant improvements in survival in patients with esophageal and gastric cancers. Further confirmatory population-based studies as well as mechanistic-bench studies are needed to support our findings. Background: Cold stress suppresses antitumor response in animal models, leading to tumor growth. Recent studies have also shown a negative correlation between the average annual temperature (AAT) and cancer incidence. We hypothesized that esophageal cancer (EC) and gastric cancer (GC) patients living in warmer climates have improved survival outcomes than those living in colder climates. Methods: We conducted a retrospective analysis using the Surveillance, Epidemiology, and End Results (SEER) database from 1996 to 2015. We retrieved the National Centers for Environmental Information data to calculate the county-level AAT. Cox multivariate regression models were performed to measure the association between temperature (measured continuously at diagnosis and in 5-degree increments) and OS/DSS, adjusting for variables. All associations were compared at a significance level of 0.05. The OS and DSS were summarized using Kaplan–Meier methods. All statistics were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA). Results: A total of 17,408 EC patients were analyzed. The average age of the cohort was 65 years, 79% of which were males and 21% were females. Of them, 61.6% had adenocarcinoma, and 37.6% were squamous. After adjusting for covariates, patients in regions with an AAT > 53.5 °F had an 11% improvement in OS [HR 0.89 (95% CI 0.86–0.92), p < 0.0001] and 13% in DSS [HR 0.87 (95% CI 0.84–0.90), p < 0.0001]. When the temperature was analyzed in 5 °F increments, with each increment, there was a 3% improvement in OS [HR 0.97 (95% CI 0.96–0.98), p < 0.0001] and 4% in DSS [HR 0.96 (95% CI 0.95–0.97), p < 0.0001]. Subgroup analysis of squamous and adenocarcinoma showed similar results. These findings were validated in 20,553 GC patients. After adjusting for covariates, patients in regions with an AAT > 53.5 had a 13% improvement in OS [HR 0.87 (95% CI 0.85–0.90), p < 0.0001] and 14% in DSS [HR 0.86 (95% CI 0.83–0.89), p < 0.0001]. When analyzed in 5 °F increments, with each increment, there was a 4% improvement in OS [HR 0.96 (95% CI 0.952–0.971), p < 0.0001] and 4% in DSS [HR 0.96 (95% CI 0.945–0.965), p < 0.0001]. Conclusion: We showed for the first time that higher environmental temperatures are associated with significant improvements in OS and DSS in patients with gastro-esophageal cancers, notwithstanding the limitations of a retrospective database analysis. Further confirmatory and mechanistic studies are required to implement specific interventional strategies. [ABSTRACT FROM AUTHOR]

Background: Our previous research on neuroendocrine and gastric cancers has shown that patients living in rural areas have worse outcomes than urban patients. This study aimed to investigate the geographic and sociodemographic disparities in esophageal cancer patients. Methods: We conducted a retrospective study on esophageal cancer patients between 1975 and 2016 using the Surveillance, Epidemiology, and End Results database. Both univariate and multivariable analyses were performed to evaluate overall survival (OS) and disease-specific survival (DSS) between patients residing in rural (RA) and urban (MA) areas. Further, we used the National Cancer Database to understand differences in various quality of care metrics based on residence. Results: N = 49,421 (RA [12%]; MA [88%]). The incidence and mortality rates were consistently higher during the study period in RA. Patients living in RA were more commonly males (p < 0.001), Caucasian (p < 0.001), and had adenocarcinoma (p < 0.001). Multivariable analysis showed that RA had worse OS (HR = 1.08; p < 0.01) and DSS (HR = 1.07; p < 0.01). Quality of care was similar, except RA patients were more likely to be treated at a community hospital (p < 0.001). Conclusions: Our study identified geographic disparities in esophageal cancer incidence and outcomes despite the similar quality of care. Future research is needed to understand and attenuate such disparities. [ABSTRACT FROM AUTHOR]

Introduction: The incidence of obesity, a condition characterized by systemic chronic inflammation, has reached pandemic proportions and is a poor prognostic factor in many pathologic states. However, its role on immune parameters has been diverse and at times contradictory. We have previously demonstrated that obesity can result in what has been called the "obesity paradox" which results in increased T cell exhaustion, but also greater efficacy of immune checkpoint blockade in cancer treatment. Methods: The role of obesity, particularly in the context of aging, has not been robustly explored using preclinical models. We therefore evaluated how age impacts the immune environment on T cell development and function using diet-induced obese (DIO) mice. Results: We observed that DIO mice initially displayed greater thymopoiesis but then developed greater thymic involution over time compared to their lean counterparts. Both aging and obesity resulted in increased T cell memory conversion combined with increased expression of T cell exhaustion markers and Treg expansion. This increased T cell immunosuppression with age then resulted in a loss of anti-tumor efficacy by immune checkpoint inhibitors (ICIs) in older DIO mice compared to the younger DIO counterparts. Discussion: These results suggest that both aging and obesity contribute to T cell dysfunction resulting in increased thymic involution. This combined with increased T cell exhaustion and immunosuppressive parameters affects immunotherapy efficacy reducing the advantage of obesity in cancer immunotherapy responses. [ABSTRACT FROM AUTHOR]

Pancreatic cancer is the fourth leading cause of cancer mortality in the United States. Chemotherapy in resectable pancreatic cancer has improved survival by 10-20%. It only converted 10-30% of the borderline resectable and locally advanced pancreatic cancers to be surgically resectable. Radiation therapy has a documented role in managing localized pancreatic cancer, more so for borderline and locally advanced pancreatic cancer, where it can potentially improve the resectability rate of a given neoadjuvant treatment. The role of radiation therapy in resected pancreatic cancer is controversial, but it is used routinely to treat positive margins after pancreatic cancer surgery. Radiation therapy paradigms continue to evolve with advancements in treatment modalities, delivery techniques, and combination approaches. Despite the advances, there continues to be a controversy on the role of radiation therapy in managing this disease. In this review article, we discuss the recent updates, delivery techniques, and motion management in radiation therapy and dissect the applicability of this therapy in pancreatic cancer. [ABSTRACT FROM AUTHOR]

Gastroesophageal cancers (GEC) have a poor survival rate of 20–30% at 5 years, often due to delayed presentations. Neoadjuvant chemoradiotherapy (CRT) followed by surgery or peri-operative chemotherapy and surgery are widely used as the standard of care for patients with resectable GEC. Immune checkpoint inhibitors (ICIs) have improved survival in metastatic and recurrent GEC which led to their application in resectable GEC. Based on the pivotal CheckMate 577 study results, the Food and Drug Administration (FDA) approved nivolumab for patients with completely resected high-risk esophageal or gastroesophageal junction cancer (GEJC). Several ongoing trials with many ICIs could potentially improve resectable GEC outcomes. This review explores the rationale for using ICIs in resectable GEC and discusses the significance of reported clinical trials. Finally, we will examine some ongoing clinical trials and the challenges as well as prospects of ICIs in resectable GEC. [ABSTRACT FROM AUTHOR]

The use of social media, such as Twitter, has changed the information landscape for citizens' participation in crisis response and recovery activities. Given that drought progression is slow and also spatially extensive, an interesting set of questions arise, such as how the usage of Twitter by a large population may change during the development of a major drought alongside how the changing usage facilitates drought detection. For this reason, contemporary analysis of how social media data, in conjunction with meteorological records, was conducted towards improvement in the detection of drought and its progression. The research utilized machine learning techniques applied over satellite-derived drought conditions in Colorado. Three different machine learning techniques were examined: the generalized linear model, support vector machines and deep learning, each applied to test the integration of Twitter data with meteorological records as a predictor of drought development. It is found that the integration of data resources is viable given that the Twitter-based model outperformed the control run which did not include social media input. Eight of the ten models tested showed quantifiable improvements in the performance over the control run model, suggesting that the Twitter-based model was superior in predicting drought severity. Future work lies in expanding this method to depict drought in the western U.S. [ABSTRACT FROM AUTHOR]

Importance: Immune checkpoint inhibitors (ICI) have revolutionized the treatment for gastroesophageal cancers (GEC). It is important to investigate the factors that influence the response to anti-PD-1/PD-L1 ICIs. Objective: To assess the benefits of PD-1/PD-L1 ICIs in advanced GEC and perform subgroup analysis to identify patient populations who would benefit from ICI. Data sources: PubMed, Embase, Scopus, and the Cochrane Library databases were systematically searched from database inception to September 2021 for all relevant articles. We also reviewed abstracts and presentations from all major conference proceedings including relevant meetings of the American Society of Clinical Oncology (ASCO), and the European Society for Medical Oncology (ESMO) during the last four years (2018 to 2021) and reviewed citation lists. Study selection, data extraction, and synthesis: Full articles and presentations were further assessed if the information suggested that the study was a phase 2/3 randomized controlled trial (RCT) comparing PD-1/PD-L1 inhibitor either alone, or in combination with standard therapy vs. standard therapy in advanced GEC. The full text of the resulting studies/presentations and extracted data were reviewed independently according to PRISMA guidelines. Main outcomes and measures: The main outcomes were OS, PFS, and treatment-related adverse events (TRAEs). Results: A total of 168 studies were assessed for eligibility, and 17 RCTs with 12,312 patients met the inclusion criteria. There was an OS benefit in the overall population with ICIs (HR 0.78; 95% CI 0.73–0.83 p < 0.001). Immunotherapy showed better OS benefit in males (HR 0.77 95% CI 0.72–0.83; p < 0.001) than females (HR 0.89; 95% CI 0.80–0.99 p < 0.03), esophageal primary tumors (HR 0.70 95% CI 0.64–0.76 p < 0.001) vs. gastric cancer (HR 0.84 95% CI 0.74–0.94 p 0.002) or GEJ cancer (HR 0.84 95% CI 0.72–0.98 p 0.024) and in squamous cell carcinoma (HR 0.71 95% CI 0.66–0.77 p < 0.001) vs. adenocarcinoma (HR 0.85 95% CI 0.78–0.93 p < 0.001). PD-L1 positive patients seemed to benefit more (HR 0.74 95% CI 0.67–0.82 p < 0.001) compared to PD-L1 negative patients (HR 0.86 95% CI 0.74–1.00 p < 0.043), and Asians showed OS benefit (HR 0.76 95% CI 0.67–0.87 p < 0.001) compared to their White counterparts (HR 0.92 95% CI 0.74–1.14; p 0.424). Conclusions and relevance: ICIs improve survival in advanced GEC without significantly increasing the side effects. However, certain subgroups of patients such as males, Asians, and those with esophageal primary, PD-L1 positive tumors and squamous cell carcinoma benefit more from such treatments. Further translational research is needed to understand the mechanistic links and develop new biomarkers. [ABSTRACT FROM AUTHOR]

Upon chronic antigen exposure, CD8+ T cells become exhausted, acquiring a dysfunctional state correlated with the inability to control infection or tumor progression. In contrast, stem-like CD8+ T progenitors maintain the ability to promote and sustain effective immunity. Adenovirus (Ad)–vectored vaccines encoding tumor neoantigens have been shown to eradicate large tumors when combined with anti–programmed cell death protein 1 (αPD-1) in murine models; however, the mechanisms and translational potential have not yet been elucidated. Here, we show that gorilla Ad vaccine targeting tumor neoepitopes enhances responses to αPD-1 therapy by improving immunogenicity and antitumor efficacy. Single-cell RNA sequencing demonstrated that the combination of Ad vaccine and αPD-1 increased the number of murine polyfunctional neoantigen-specific CD8+ T cells over αPD-1 monotherapy, with an accumulation of Tcf1+ stem-like progenitors in draining lymph nodes and effector CD8+ T cells in tumors. Combined T cell receptor (TCR) sequencing analysis highlighted a broader spectrum of neoantigen-specific CD8+ T cells upon vaccination compared to αPD-1 monotherapy. The translational relevance of these data is supported by results obtained in the first 12 patients with metastatic deficient mismatch repair (dMMR) tumors vaccinated with an Ad vaccine encoding shared neoantigens. Expansion and diversification of TCRs were observed in post-treatment biopsies of patients with clinical response, as well as an increase in tumor-infiltrating T cells with an effector memory signature. These findings indicate a promising mechanism to overcome resistance to PD-1 blockade by promoting immunogenicity and broadening the spectrum and magnitude of neoantigen-specific T cells infiltrating tumors. Immunotherapy that is not monkeying around: Adenoviral vaccines encoding for tumor neoantigens have shown promise treating solid tumors when combined with anti–programmed cell death protein 1 (αPD-1) preclinically; however, the mechanism is not well understood. To elucidate this, Chen et al. generated Great Ape adenovirus (GAd) vaccines and treated tumor-bearing mice in combination with αPD-1 to elicit an accumulation of Tcf1+ stem-like CD8+ T cell progenitors, improving immunogenicity and antitumor efficacy. In addition, they performed a first-in-human trial on patients with metastatic mismatch repair–deficient tumors and saw a clinical response, suggesting this as a promising therapy to overcome resistance to αPD-1 treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: Studies have shown that obesity is associated with many adverse health effects, including worse cancer outcomes. Many studies paradoxically suggest a survival benefit for obesity in treatment outcomes of cancers such as non-small-cell lung cancer. This relationship is not seen in animal models. We hypothesize that this relationship is secondary to suboptimal quantification of adiposity, enhanced immunotherapy response, and variables such as sex, medications, and smoking status. There are many ways to measure and classify adiposity, but the ability to distinguish abdominal obesity is likely key in predicting accurate prognosis. There are many ways obesity impacts cancer treatment course from diagnosis to survivorship. In this paper, we aim to analyze the factors contributing to the obesity paradox and its effect on lung cancer. This can aid the treatment and prognosis of lung cancer and may support further research into obesity-specific impacts on this malignancy. There is a paradoxical relationship between obesity, as measured by BMI, and many types of cancer, including non-small-cell lung cancer. Obese non-small-cell lung cancer patients have been shown to fare better than their non-obese counterparts. To analyze the multifaceted effects of obesity on oncologic outcomes, we reviewed the literature on the obesity paradox, methods to measure adiposity, the obesity-related derangements in immunology and metabolism, and the oncologic impact of confounding variables such as gender, smoking, and concomitant medications such as statins and metformin. We analyzed how these aspects may contribute to the obesity paradox and cancer outcomes with a focus on lung cancer. We concluded that the use of BMI to measure adiposity is limited and should be replaced by a method that can differentiate abdominal obesity. We also concluded that the concomitant metabolic and immunologic derangements caused by obesity contribute to the obesity paradox. Medications, gender, and smoking are additional variables that impact oncologic outcomes, and further research needs to be performed to solidify the mechanisms. [ABSTRACT FROM AUTHOR]

A robust and intuitive understanding of fluid mechanics—the applied science of fluid motion—is foundational within many engineering disciplines, including aerospace, chemical, civil, mechanical, naval, and ocean engineering. In‐depth knowledge of fluid mechanics is critical to safe and economical design of engineering applications employed globally everyday, such as automobiles, aircraft, and sea craft, and to meeting global 21st century engineering challenges, such as developing renewable energy sources, providing access to clean water, managing the environmental nitrogen cycle, and improving urban infrastructure. Despite the fundamental nature of fluid mechanics within the broader undergraduate engineering curriculum, students often characterize courses in fluid mechanics as mathematically onerous, conceptually difficult, and aesthetically uninteresting; anecdotally, undergraduates may choose to opt‐out of fluids engineering‐related careers based on their early experiences in fluids courses. Therefore, the continued development of new frameworks for engineering instruction in fluid mechanics is needed. Toward that end, this paper introduces mobile instructional particle image velocimetry (mI‐PIV), a low‐cost, open‐source, mobile application‐based educational tool under development for smartphones and tablets running Android. The mobile application provides learners with both technological capability and guided instruction that enables them to visualize and experiment with authentic flow fields in real time. The mI‐PIV tool is designed to generate interest in and intuition about fluid flow and to improve understanding of mathematical concepts as they relate to fluid mechanics by providing opportunities for fluids‐related active engagement and discovery in both formal and informal learning contexts. [ABSTRACT FROM AUTHOR]

Accurate measurement of honeybee (Apis mellifera) traffic in the vicinity of the hive is critical in systems that continuously monitor honeybee colonies to detect deviations from the norm. BeePIV, the algorithm we describe and evaluate in this article, is a new significant result in our longitudinal investigation of honeybee flight and traffic in electronic beehive monitoring. BeePIV converts frames from bee traffic videos to particle motion frames with uniform background, applies particle image velocimetry to these motion frames to compute particle displacement vector fields, classifies individual displacement vectors as incoming, outgoing, and lateral, and uses the respective vector counts to measure incoming, outgoing, and lateral bee traffic. We evaluate BeePIV on twelve 30-s color videos with a total frame count of 8928 frames for which we obtained the ground truth by manually counting every full bee motion in each frame. The bee motion counts obtained from these videos with BeePIV come closer to the human bee motion counts than the bee motion counts obtained with our previous video-based bee counting methods. We use BeePIV to compute incoming and outgoing bee traffic curves for two different hives over a period of seven months and observe that these curves closely follow each other. Our observations indicate that bee traffic curves obtained by BeePIV may be used to predict colony failures. Our experiments suggest that BeePIV can be used in situ on the raspberry pi platform to process bee traffic videos. Dataset: The supplementary materials for our article include three video sets for the reader to appreciate how BeePIV processes bee traffic videos. Each set consists of three videos. The first video is an original raw video captured by our deployed BeePi electronic beehive monitoring system; the second video is the corresponding video that consists of the white background particle motion frames extracted from the first video; the third video is the video of displacement vectors extracted by PIV from each pair of consecutive white background frames from the second video. All computation is executed on a raspberry pi 3 model B v1.2 with four cores. [ABSTRACT FROM AUTHOR]

Introduction: Hepatocellular carcinoma (HCC) is the most common form of liver cancer worldwide and carries a poor prognosis. Historically, sorafenib was the only available systemic treatment for advanced HCC. However, in recent years, 6 new treatments have been approved by the US Food and Drug Administration (FDA): regorafenib, lenvatinib, cabozantinib, pembrolizumab, ramucirumab, and nivolumab. Data are lacking regarding the most appropriate sequencing pathway for these agents. Our objective was to conduct a comprehensive cost effectiveness analysis (CEA) of different 1st- and 2nd-line treatment pathways for HCC reflecting all new drug approvals, and then use our data to provide guidance for clinicians on which pathway is the most cost-effective. Materials and Methods: Markov models were used to evaluate the cost effectiveness of 8 different 1st- and 2nd-line treatment sequences. The model allowed for 9 possible states. Cost effectiveness ratios (CER) and incremental CER (ICER) were calculated to compare costs between different pathways and against a willingness-to-pay (WTP) threshold. Efficacy and toxicity data were extracted from the landmark trials for each agent. All agents except ramucirumab were included. The cost of each agent was based on the wholesale acquisition cost (WAC) in USD as of June 2019. Monte-Carlo methods were used to simulate the experience of 1,000,000 patients per treatment sequence for a 12-month period. Results: The pathway with the lowest CER was sorafenib, followed by pembrolizumab (USD 227,741.03/quality-adjusted life year [QALY]). ICER analysis supported implementing 2nd-line pembrolizumab-based pathways at a higher WTP threshold of 300,000/quality-adjusted life year. Sensitivity analysis did not substantially change these results. Conclusions: The most cost-effective strategy was 1st-line tyrosine kinase inhibitor therapy followed by 2nd-line immunotherapy. All pathways exceeded a commonly accepted WTP of USD 100–150,000/QALY. Our preliminary results warrant further studies to best inform real-world practices. [ABSTRACT FROM AUTHOR]

Background: Antiangiogenic-targeting agents have low response rates in patients with nonpancreatic neuroendocrine tumors (NETs). Nintedanib is an oral antiangiogenic agent that has inhibitory effects on the fibroblast growth factor receptor, which is highly expressed in NETs. The authors hypothesized that nintedanib would be active in patients with nonpancreatic NETs.Methods: Patients with advanced, grade 1 or 2, nonpancreatic NETs who were receiving a stable dose of somatostatin analogue were enrolled. Nintedanib was administered at a dose of 200 mg twice daily in 28-day cycles. The primary endpoint was progression-free survival (PFS) at 16 weeks.Results: Thirty-two patients were enrolled, and 30 were evaluable for the primary outcome. Most had radiographic disease progression within 12 months before enrollment. The 16-week PFS rate was 83%, and the median PFS and overall survival were 11.0 months and 32.7 months, respectively. Nintedanib was well tolerated and delayed deterioration in quality of life. The baseline serotonin level had a strong, positive correlation with activated but exhausted T cells.Conclusions: Nintedanib is active in nonpancreatic NETs. The immunosuppressive effect of serotonin should be targeted in future clinical trials. [ABSTRACT FROM AUTHOR]

The well-being of a honeybee (Apis mellifera) colony depends on forager traffic. Consistent discrepancies in forager traffic indicate that the hive may not be healthy and require human intervention. Honeybee traffic in the vicinity of a hive can be divided into three types: incoming, outgoing, and lateral. These types constitute directional traffic, and are juxtaposed with omnidirectional traffic where bee motions are considered regardless of direction. Accurate measurement of directional honeybee traffic is fundamental to electronic beehive monitoring systems that continuously monitor honeybee colonies to detect deviations from the norm. An algorithm based on digital particle image velocimetry is proposed to measure directional traffic. The algorithm uses digital particle image velocimetry to compute motion vectors, analytically classifies them as incoming, outgoing, or lateral, and returns the classified vector counts as measurements of directional traffic levels. Dynamic time warping is used to compare the algorithm's omnidirectional traffic curves to the curves produced by a previously proposed bee motion counting algorithm based on motion detection and deep learning and to the curves obtained from a human observer's counts on four honeybee traffic videos (2976 video frames). The currently proposed algorithm not only approximates the human ground truth on par with the previously proposed algorithm in terms of omnidirectional bee motion counts but also provides estimates of directional bee traffic and does not require extensive training. An analysis of correlation vectors of consecutive image pairs with single bee motions indicates that correlation maps follow Gaussian distribution and the three-point Gaussian sub-pixel accuracy method appears feasible. Experimental evidence indicates it is reasonable to treat whole bees as tracers, because whole bee bodies and not parts thereof cause maximum motion. To ensure the replicability of the reported findings, these videos and frame-by-frame bee motion counts have been made public. The proposed algorithm is also used to investigate the incoming and outgoing traffic curves in a healthy hive on the same day and on different days on a dataset of 292 videos (216,956 video frames). [ABSTRACT FROM AUTHOR]

Background: The incidence of neuroendocrine tumors (NETs) is rapidly rising. There are very few studies investigating the role of sociodemographic factors in NETs. This study was aimed at examining how geographic and sociodemographic characteristics shape outcomes in the NET population.Methods: A retrospective analysis using the Surveillance, Epidemiology, and End Results database was performed, and the NET patient population from 1973 to 2015 was studied. Univariate and multivariable analyses were performed to evaluate patients' disease-specific survival (DSS) and overall survival (OS). Geographic and sociodemographic factors, including the location of residence (urban area [UA] vs rural area [RA]), sex, race, insurance status, and marital status, were included in the analysis.Results: A total of 53,034 patients (5517 in RAs and 47,517 in UAs) were included in the analysis. The incidence of NETs was found to be rising in both RAs and UAs but more rapidly in RAs (with the highest incidence in 2006-2015: 5.93 per 100,000 in RAs vs 4.10 per 100,000 in UAs). Patients from RAs presented at advanced stages in comparison with patients from UAs (regional, 18% vs 16%; distant, 15% vs 13%; P < .01). In the multivariable model, RA patients had a trend toward poorer OS (hazard ratio, 1.05; P = .053) in comparison with UA patients. The multivariable analysis showed significantly worse DSS and OS for uninsured, single, and male patients in comparison with insured, married, and female patients, respectively.Conclusions: This study has identified sociodemographic disparities in NET outcomes. Access to health care could be a potential contributing factor, although differences in environmental exposure, health behavior, and tumor biology could also be responsible. [ABSTRACT FROM AUTHOR]

Background: Pancreatic neuroendocrine tumors (panNETs) are a rare group of tumors that make up 2%–3% of pancreatic tumors. Recommended treatment for panNETs generally consists of resection for symptomatic or large asymptomatic tumors; however, optimal management for localized disease is still controversial, with conflicting recommendations in established guidelines. Our study aim is to compare surgical intervention versus active surveillance in nonmetastatic panNETs by size of primary tumor. Materials and Methods: Using the National Cancer Database, we identified 2,004 patients diagnosed with localized well‐differentiated, nonfunctional panNETs (NF‐panNETs) between 2004 and 2015. Patients' clinicopathologic characteristics, treatment modalities, and overall survival (OS) were analyzed using frequency statistics, chi‐square, and Kaplan‐Meier curves. The objective of the study is to assess the outcome of surgical resection versus nonoperative management in patients with panNETs with different tumor sizes. Results: Tumor sizes were divided into three categories: <1 cm, 1–2 cm, and >2 cm. The number of patients with tumor size <1 cm, 1–2 cm, and >2 cm was 220 (11%), 794 (39.6%), and 990 (49.4%), respectively. Overall, 1,781 underwent surgical resection, whereas 223 patients did not. Median follow‐up was 25.9 months. After adjusting for covariates, surgical resection was associated with improved OS in patients with tumor size 1–2 cm (hazard ratio [HR] = 0.37) and >2c m (HR = 0.30) but not <1 cm (HR = 2.81). Independent prognostic factors were age at diagnosis, Charlson‐Deyo comorbidity score, stage, tumor location, and surgical resection. Higher tumor grade was not associated with worse OS. Conclusion: Our findings suggest that active surveillance is potentially a safe approach for NF‐panNETs <1 cm. Larger tumors likely need active intervention. Intermediate‐grade tumors did not result in worse survival outcome compared with low‐grade tumors. Future studies might consider prospective randomized clinical trials to validate our findings. Implications for Practice: The present study seeks to address the discrepancy in treatment recommendations in the management of nonfunctional pancreatic neuroendocrine tumors (NF‐panNETs) by evaluating whether surgical resection is associated with improved overall survival in different tumor size groups as well as elucidating independent prognostic factors in patients with NF‐panNETs. Data from the National Cancer Database were reviewed. This study's findings suggest that active surveillance is potentially a safe approach for NF‐panNETs <1 cm. Larger tumors likely need active intervention. Independent prognostic factors include age at diagnosis, Charlson‐Deyo comorbidity score, stage, tumor location, and surgical resection. These findings will help guide medical and surgical oncologists when formulating treatment plans for patients with small NF‐panNETs. Optimal management for pancreatic neuroendocrine tumors is controversial. This article evaluates whether surgical resection is associated with improved overall survival in different tumor size groups. [ABSTRACT FROM AUTHOR]

Omnidirectional bee traffic is the number of bees moving in arbitrary directions in close proximity to the landing pad of a given hive over a given period of time. Video bee traffic analysis has the potential to automate the assessment of omnidirectional bee traffic levels, which, in turn, may lead to a complete or partial automation of honeybee colony health assessment. In this investigation, we proposed, implemented, and partially evaluated a two-tier method for counting bee motions to estimate levels of omnidirectional bee traffic in bee traffic videos. Our method couples motion detection with image classification so that motion detection acts as a class-agnostic object location method that generates a set of regions with possible objects and each such region is classified by a class-specific classifier such as a convolutional neural network or a support vector machine or an ensemble of classifiers such as a random forest. The method has been, and is being iteratively field tested in BeePi monitors, multi-sensor electronic beehive monitoring systems, installed on live Langstroth beehives in real apiaries. Deployment of a BeePi monitor on top of a beehive does not require any structural modification of the beehive's woodenware, and is not disruptive to natural beehive cycles. To ensure the replicability of the reported findings and to provide a performance benchmark for interested research communities and citizen scientists, we have made public our curated and labeled image datasets of 167,261 honeybee images and our omnidirectional bee traffic videos used in this investigation. Dataset: The three image datasets (BEE1, BEE2_1S and BEE2_2S) used in this investigation are publicly available at https://usu.box.com/s/0a5yurmn7ija15cp236awa1re65mbcnr , https://usu.box.com/s/p7y8v95ot9u9jvjbbayci61no3lzbgx3 and https://usu.box.com/s/3ccizd5b1qzcqcs4t0ivawmrxbgva7ym , respectively. The omnidirectional bee traffic videos and the corresponding human bee motion counts are included in the Supplementary Materials. [ABSTRACT FROM AUTHOR]

Electronic beehive monitoring extracts critical information on colony behavior and phenology without invasive beehive inspections and transportation costs. As an integral component of electronic beehive monitoring, audio beehive monitoring has the potential to automate the identification of various stressors for honeybee colonies from beehive audio samples. In this investigation, we designed several convolutional neural networks and compared their performance with four standard machine learning methods (logistic regression, k-nearest neighbors, support vector machines, and random forests) in classifying audio samples from microphones deployed above landing pads of Langstroth beehives. On a dataset of 10,260 audio samples where the training and testing samples were separated from the validation samples by beehive and location, a shallower raw audio convolutional neural network with a custom layer outperformed three deeper raw audio convolutional neural networks without custom layers and performed on par with the four machine learning methods trained to classify feature vectors extracted from raw audio samples. On a more challenging dataset of 12,914 audio samples where the training and testing samples were separated from the validation samples by beehive, location, time, and bee race, all raw audio convolutional neural networks performed better than the four machine learning methods and a convolutional neural network trained to classify spectrogram images of audio samples. A trained raw audio convolutional neural network was successfully tested in situ on a low voltage Raspberry Pi computer, which indicates that convolutional neural networks can be added to a repertoire of in situ audio classification algorithms for electronic beehive monitoring. The main trade-off between deep learning and standard machine learning is between feature engineering and training time: while the convolutional neural networks required no feature engineering and generalized better on the second, more challenging dataset, they took considerably more time to train than the machine learning methods. To ensure the replicability of our findings and to provide performance benchmarks for interested research and citizen science communities, we have made public our source code and our curated datasets. Dataset: The curated datasets for this article (BUZZ1 and BUZZ2) are publicly available at https://usu.app.box.com/v/BeePiAudioData ; Python source code for data capture is publicly available at https://github.com/VKEDCO/PYPL/tree/master/beepi/py/src/29Jan2016 ; Python source code for the deep learning and machine learning experiments is publicly available at https://github.com/sarba-jit/EBM_Audio_Classification. [ABSTRACT FROM AUTHOR]

Background: There is limited literature about the clinicopathological characteristics and outcomes of rare histologic variants of gallbladder cancer (GBC). Methods: Using SEER database, surgically managed GBC patients with microscopically confirmed adenocarcinoma, adenosquamous/squamous cell carcinoma and papillary carcinoma were identified from 1988 to 2009. Patients with second primary cancer and distant metastasis at presentation were excluded. The effect of clinicopathological variables on overall survival (OS) and disease specific survival (DSS) were analyzed using univariate and multivariate proportional hazards modeling. All associations were considered statistically significant at an alpha error of 0.01. Results: Out of 4738 cases, 217 adenosquamous/squamous (4.6%), 367 papillary (7.7%), and 4154 adenocarcinomas (87.7%) were identified. Median age was 72 years. Higher tumor grade (grade 2, 3, 4 versus grade 1), higher T stage (T2, T3, T4 versus T1), lymph node positivity (N1 versus N0) and adenosquamous/squamous histology (versus adenocarcinoma) had worse OS and DSS (p < .001). Papillary GBC had better OS and DSS than adenocarcinoma (HR = 0.7; p < .001). Radical surgery (versus simple cholecystectomy) had better OS (HR = 0.83, p = 0.002) in multivariate analysis. OS rates at 3 and 5 years were 0.56 and 0.44 for papillary, 0.3 and 0.22 for adenocarcinoma, and 0.14 and 0.12 for adenosquamous/squamous histology, while DSS rates at 3 and 5 years were 0.67 and 0.61 for papillary, 0.38 and 0.31 for adenocarcinoma, and 0.17 and 0.16 for adenosquamous/squamous subtypes respectively. Conclusion: Papillary GBC had better survival outcomes while adenosquamous/squamous GBC had worse survival outcomes compared to gallbladder adenocarcinoma. [ABSTRACT FROM AUTHOR]