Hypertension and hand-foot skin reactions related to VEGFR2 genotype and improved clinical outcome following bevacizumab and sorafenib

BACKGROUND: Hypertension (HT) and hand-foot skin reactions (HFSR) may be related to the activity of bevacizumab and sorafenib. We hypothesized that these toxicities would correspond to favorable outcome in these drugs, that HT and HFSR would coincide, and that VEGFR2 genotypic variation would be related to toxicity and clinical outcomes. METHODS: Toxicities (≥ grade 2 HT or HFSR), progression-free survival (PFS), and overall survival (OS) following treatment initiation were evaluated. Toxicity incidence and VEGFR2 H472Q and V297I status were compared to clinical outcomes. RESULTS: Individuals experiencing HT had longer PFS following bevacizumab therapy than those without this toxicity in trials utilizing bevacizumab in patients with prostate cancer (31.5 vs 14.9 months, n = 60, P = 0.0009), and bevacizumab and sorafenib in patients with solid tumors (11.9 vs. 3.7 months, n = 27, P = 0.052). HT was also linked to a > 5-fold OS benefit after sorafenib and bevacizumab cotherapy (5.7 versus 29.0 months, P = 0.0068). HFSR was a marker for prolonged PFS during sorafenib therapy (6.1 versus 3.7 months respectively, n = 113, P = 0.0003). HT was a risk factor for HFSR in patients treated with bevacizumab and/or sorafenib (OR(95%CI) = 3.2(1.5-6.8), P = 0.0024). Carriers of variant alleles at VEGFR2 H472Q experienced greater risk of developing HT (OR(95%CI) = 2.3(1.2 - 4.6), n = 170, P = 0.0154) and HFSR (OR(95%CI) = 2.7(1.3 - 5.6), n = 170, P = 0.0136). CONCLUSIONS: This study suggests that HT and HFSR may be markers for favorable clinical outcome, HT development may be a marker for HFSR, and VEGFR2 alleles may be related to the development of toxicities during therapy with bevacizumab and/or sorafenib

Uncertainty in On-The-Fly Epidemic Fitting

Abstract. The modern world features a plethora of social, technolog-ical and biological epidemic phenomena. These epidemics now spread at unprecedented rates thanks to advances in industrialisation, trans-port and telecommunications. Effective real-time decision making and management of modern epidemic outbreaks depends on the two factors: the ability to determine epidemic parameters as the epidemic unfolds, and the ability to characterise rigorously the uncertainties inherent in these parameters. This paper presents a generic maximum-likelihood-based methodology for online epidemic fitting of SIR models from a single trace which yields confidence intervals on parameter values. The method is fully automated and avoids the laborious manual efforts tra-ditionally deployed in the modelling of biological epidemics. We present case studies based on both synthetic and real data

Expression of OATP Family Members in Hormone-Related Cancers: Potential Markers of Progression

The organic anion transporting polypeptide (OATP) family of transporters has been implicated in prostate cancer disease progression probably by transporting hormones or drugs. In this study, we aimed to elucidate the expression, frequency, and relevance of OATPs as a biomarker in hormone-dependent cancers. We completed a study examining SLCO1B3, SLCO1B1 and SLCO2B1 mRNA expression in 381 primary, independent patient samples representing 21 cancers and normal tissues. From a separate cohort, protein expression of OATP1B3 was examined in prostate, colon, and bladder tissue. Based on expression frequency, SLCO2B1 was lower in liver cancer (P = 0.04) which also trended lower with decreasing differentiation (P = 0.004) and lower magnitude in pancreatic cancer (P = 0.05). SLCO2B1 also had a higher frequency in thyroid cancer (67%) than normal (0%) and expression increased with stage (P = 0.04). SLCO1B3 was expressed in 52% of cancerous prostate samples and increased SLCO1B3 expression trended with higher Gleason score (P = 0.03). SLCO1B3 expression was also higher in testicular cancer (P = 0.02). SLCO1B1 expression was lower in liver cancer (P = 0.04) which trended lower with liver cancer grade (P = 0.0004) and higher with colon cancer grade (P = 0.05). Protein expression of OATP1B3 was examined in normal and cancerous prostate, colon, and bladder tissue samples from an independent cohort. The results were similar to the transcription data, but showed distinct localization. OATPs correlate to differentiation in certain hormone-dependent cancers, thus may be useful as biomarkers for assessing clinical treatment and stage of disease

New spectral index and machine learning models for detecting coffee leaf miner infestation using sentinel-2 multispectral imagery.

The coffee leaf miner (Leucoptera coffeella) is a key coffee pest in Brazil that can cause severe defoliation and a negative impact on the productivity. Thus, it is essential to identify initial pest infestation for the sake of appropriate time control to avoid further economic damage to the coffee crops. A fast non-destructive method is an important tool that can be used to monitor the occurrence of the coffee leaf miner. The present work aims to identify the occurrence of coffee leaf miner infestation through a new vegetation index, using multispectral images from the Sentinel-2 satellite and the Google Earth Engine platform. Coffee leaf miner infestation was measured in the field in four cities in the state of Minas Gerais. The largest infestations occurred in September, October, and November but particularly in October 2021, in which the rate of infestation reached 85%, followed by September 2020 with a maximum infestation of 76%. The calculation steps of the vegetation indices and mappings were carried out in the Google Earth Engine cloud processing platform through the development of a script in JavaScript programming language. Combinations of two sensitive bands were selected to detect coffee leaf miner infestation, and from these, the 'Coffee-Leaf-Miner Index' was developed, which was compared with other existing vegetation indices in terms of their performance for coffee leaf miner detection. The combination of the NIR-BLUE and NIR-RED bands was more sensitive for the detection of coffee leaf miner infestation; therefore, the NIR, BLUE, and RED bands were selected to develop the new index. The 'Coffee-Leaf-Miner Index' presented the best performance among those evaluated, with a coefficient of determination of about 0.87, a root mean square error of 4.92% coffee leaf miner infestation, accuracy of 89.47%, and kappa coefficient of 95.39. The R2 range of other spectral indices which exist in the literature and which were used in this study was from 0.017 to 0.867, and the root mean square error ranged from 4.996 to 13.582% coffee leaf miner infestation. The machine learning method was then adopted using the supervised Random Forest and Support Vector Machine algorithms to recognize patterns of coffee leaf miner infestation in the field, only the Coffee-Leaf-Miner Index was used for the identification test of the coffee leaf miner infestation. The Support Vector Machine with linear Kernel type was applied to establish a discrimination model. The number of trees for the Random Forest classifier was 100. The Support Vector Machine presented a lower performance than the Random Forest algorithm, but the performance of both were above 80% for user and producer precision. Three bands (Blue, Red, NIR) were selected for the creation of the new index, which showed capacity for remote detection of coffee leaf miner infestation on a regional scale. Thus, 'Coffee-Leaf-Miner Index' can identify coffee leaf miner infestation thanks to all the complexity involved in detecting pests via orbital remote sensing

Mortality from cutaneous melanoma: evidence for contrasting trends between populations

In recent years several reports have been published concerning trends in melanoma mortality in different countries, some of which have indicated that rates are beginning to fall. Many of these reports, however, have been based on small populations and have used different forms of statistical analysis. Our objective was to analyse systematically to what degree the epidemic of melanoma mortality had evolved similarly in different populations and whether there were any divergent trends that might increase our understanding. Instead of using all available data, we focused on countries with a minimum time series of 30 years and a minimum of 100 deaths annually in at least one sex from melanoma. We first inspected sex-specific age-standardized mortality rates and then performed age-period-cohort modelling. We found that the increase in mortality observed after 1950 was more pronounced in the age group 60–79. Statistical modelling showed a general increase in mortality rates in generations born after the turn of the century. Downturns in mortality, essentially in women and starting with generations born just before World War II, were found in Australia (where the earliest decreases were noted), the Nordic countries and the USA. Small decreases in rates in more recent generations were found in the UK and Canada. However, in France, Italy and Czechoslovakia, mortality rates were seen to be still increasing in recent cohorts. Our analysis suggests that populations are at different places on the melanoma mortality epidemic curve. The three trend patterns we observed are in agreement with time differences between populations with respect to the promotion of sun protection and the surveillance of pigmented skin lesions. © 2000 Cancer Research Campaig