Metabolic Effects of the Incretin Mimetic Exenatide in the Treatment of Type 2 Diabetes

Interventional studies have demonstrated the impact of hyperglycemia on the development of vascular complications associated with type 2 diabetes, which underscores the importance of safely lowering glucose to as near-normal as possible. Among the current challenges to reducing the risk of vascular disease associated with diabetes is the management of body weight in a predominantly overweight patient population, and in which weight gain is likely with many current therapies. Exenatide is the first in a new class of agents termed incretin mimetics, which replicate several glucoregulatory effects of the endogenous incretin hormone, glucagon-like peptide-1 (GLP-1). Currently approved in the US as an injectable adjunct to metformin and/or sulfonylurea therapy, exenatide improves glycemic control through multiple mechanisms of action including: glucose-dependent enhancement of insulin secretion that potentially reduces the risk of hypoglycemia compared with insulin secretagogues; restoration of first-phase insulin secretion typically deficient in patients with type 2 diabetes; suppression of inappropriately elevated glucagon secretion to reduce postprandial hepatic output; and slowing the rate of gastric emptying to regulate glucose appearance into the circulation. Clinical trials in patients with type 2 diabetes treated with subcutaneous exenatide twice daily demonstrated sustained improvements in glycemic control, evidenced by reductions in postprandial and fasting glycemia and glycosylated hemoglobin (HbA1c) levels. Notably, improvements in glycemic control with exenatide were coupled with progressive reductions in body weight, which represents a distinct therapeutic benefit for patients with type 2 diabetes. Acute effects of exenatide on beta-cell responsiveness along with significant reductions in body weight in patients with type 2 diabetes may have a positive impact on disease progression and potentially decrease the risk of associated long-term complications

Breast Cancer Index is a predictive biomarker of treatment benefit and outcome from extended tamoxifen therapy: final analysis of the Trans-aTTom study

PURPOSE: The Breast Cancer Index (BCI) HOXB13/IL17BR (H/I) ratio predicts benefit from extended endocrine therapy in hormone receptor–positive (HR(+)) early-stage breast cancer. Here, we report the final analysis of the Trans-aTTom study examining BCI (H/I)'s predictive performance. EXPERIMENTAL DESIGN: BCI results were available for 2,445 aTTom trial patients. The primary endpoint of recurrence-free interval (RFI) and secondary endpoints of disease-free interval (DFI) and disease-free survival (DFS) were examined using Cox proportional hazards regression and log-rank test. RESULTS: Final analysis of the overall study population (N = 2,445) did not show a significant improvement in RFI with extended tamoxifen [HR, 0.90; 95% confidence interval (CI), 0.69–1.16; P = 0.401]. Both the overall study population and N0 group were underpowered due to the low event rate in the N0 group. In a pre-planned analysis of the N(+) subset (N = 789), BCI (H/I)-High patients derived significant benefit from extended tamoxifen (9.7% absolute benefit: HR, 0.33; 95% CI, 0.14–0.75; P = 0.016), whereas BCI (H/I)-Low patients did not (−1.2% absolute benefit; HR, 1.11; 95% CI, 0.76–1.64; P = 0.581). A significant treatment-to-biomarker interaction was demonstrated on the basis of RFI, DFI, and DFS (P = 0.037, 0.040, and 0.025, respectively). BCI (H/I)-High patients remained predictive of benefit from extended tamoxifen in the N(+)/HER2(−) subgroup (9.4% absolute benefit: HR, 0.35; 95% CI, 0.15–0.81; P = 0.047). A three-way interaction evaluating BCI (H/I), treatment, and HER2 status was not statistically significant (P = 0.849). CONCLUSIONS: Novel findings demonstrate that BCI (H/I) significantly predicts benefit from extended tamoxifen in HR(+) N(+) patients with HER2(−) disease. Moreover, BCI (H/I) demonstrates significant treatment to biomarker interaction across survival outcomes

Validation of the prognostic performance of Breast Cancer Index (BCI) in hormone receptor-positive (HR+) postmenopausal breast cancer patients in the TEAM trial

Purpose: Early-stage HR+ breast cancer patients face a prolonged risk of recurrence even after adjuvant endocrine therapy. The Breast Cancer Index (BCI) is significantly prognostic for overall (0-10 years) and late (5-10 years) distant recurrence risk (DR) in N0 and N1 patients. Here, BCI prognostic performance was evaluated in HR+ postmenopausal women from the TEAM trial.Experimental Design: 3544 patients were included in the analysis (N=1519 N0, N=2025 N+). BCI risk groups were calculated using pre-specified cut-points. Kaplan-Meier analyses and logranktests were used to assess the prognostic significance of BCI risk groups based on DR. Hazard ratios (HR) and confidence intervals (CI) were calculated using Cox models with and without clinical covariates.Results: For overall 10-year DR, BCI was significantly prognostic in N0 (N=1196) and N1 (N=1234) patients who did not receive prior chemotherapy (p<0.001). In patients who were DRfree for 5 years, 10-year late DR rates for low- and high-risk groups were 5.4% and 9.3% (N0 cohort, N=1285) and 4.8% and 12.2% (N1 cohort, N=1625) with multivariate HRs of 2.25 (95% CI: 1.30-3.88; p=0.004) and 2.67 (95% CI: 1.53-4.63; p=<0.001), respectively. Late DR performance was substantially improved using previously optimized cut-points, identifying BCIlow-risk groups with even lower 10-year late DR rates of 3.8% and 2.7% in N0 and N1 patients, respectively.Conclusions: The TEAM trial represents the largest prognostic validation study for BCI to date and provides a more representative assessment of late DR risk to guide individualized treatment decision-making for HR+ early-stage breast cancer patients

Tumor- and Circulating-Free DNA Methylation Identifies Clinically Relevant Small Cell Lung Cancer Subtypes

Small cell lung cancer (SCLC) is an aggressive malignancy composed of distinct transcriptional subtypes, but implementing subtyping in the clinic has remained challenging, particularly due to limited tissue availability. Given the known epigenetic regulation of critical SCLC transcriptional programs, we hypothesized that subtype-specific patterns of DNA methylation could be detected in tumor or blood from SCLC patients. Using genomic-wide reduced-representation bisulfite sequencing (RRBS) in two cohorts totaling 179 SCLC patients and using machine learning approaches, we report a highly accurate DNA methylation-based classifier (SCLC-DMC) that can distinguish SCLC subtypes. We further adjust the classifier for circulating-free DNA (cfDNA) to subtype SCLC from plasma. Using the cfDNA classifier (cfDMC), we demonstrate that SCLC phenotypes can evolve during disease progression, highlighting the need for longitudinal tracking of SCLC during clinical treatment. These data establish that tumor and cfDNA methylation can be used to identify SCLC subtypes and might guide precision SCLC therapy

Prediction of Late Disease Recurrence and Extended Adjuvant Letrozole Benefit by the HOXB13/IL17BR Biomarker

BackgroundBiomarkers to optimize extended adjuvant endocrine therapy for women with estrogen receptor (ER)–positive breast cancer are limited. The HOXB13/IL17BR (H/I) biomarker predicts recurrence risk in ER-positive, lymph node–negative breast cancer patients. H/I was evaluated in MA.17 trial for prognostic performance for late recurrence and treatment benefit from extended adjuvant letrozole.MethodsA prospective–retrospective, nested case-control design of 83 recurrences matched to 166 nonrecurrences from letrozole- and placebo-treated patients within MA.17 was conducted. Expression of H/I within primary tumors was determined by reverse-transcription polymerase chain reaction with a prespecified cutpoint. The predictive ability of H/I for ascertaining benefit from letrozole was determined using multivariable conditional logistic regression including standard clinicopathological factors as covariates. All statistical tests were two-sided.ResultsHigh H/I was statistically significantly associated with a decrease in late recurrence in patients receiving extended letrozole therapy (odds ratio [OR] = 0.35; 95% confidence interval [CI] = 0.16 to 0.75; P = .007). In an adjusted model with standard clinicopathological factors, high H/I remained statistically significantly associated with patient benefit from letrozole (OR = 0.33; 95% CI = 0.15 to 0.73; P = .006). Reduction in the absolute risk of recurrence at 5 years was 16.5% for patients with high H/I (P = .007). The interaction between H/I and letrozole treatment was statistically significant (P = .03).ConclusionsIn the absence of extended letrozole therapy, high H/I identifies a subgroup of ER-positive patients disease-free after 5 years of tamoxifen who are at risk for late recurrence. When extended endocrine therapy with letrozole is prescribed, high H/I predicts benefit from therapy and a decreased probability of late disease recurrence

For the sake of resilience and multifunctionality, let's diversify planted forests!

As of 2020, the world has an estimated 290 million ha of planted forests and this number is continuously increasing. Of these, 131 million ha are monospecific planted forests under intensive management. Although monospecific planted forests are important in providing timber, they harbor less biodiversity and are potentially more susceptible to disturbances than natural or diverse planted forests. Here, we point out the increasing scientific evidence for increased resilience and ecosystem service provision of functionally and species diverse planted forests (hereafter referred to as diverse planted forests) compared to monospecific ones. Furthermore, we propose five concrete steps to foster the adoption of diverse planted forests: (1) improve awareness of benefits and practical options of diverse planted forests among land-owners, managers, and investors; (2) incentivize tree species diversity in public funding of afforestation and programs to diversify current maladapted planted forests of low diversity; (3) develop new wood-based products that can be derived from many different tree species not yet in use; (4) invest in research to assess landscape benefits of diverse planted forests for functional connectivity and resilience to global-change threats; and (5) improve the evidence base on diverse planted forests, in particular in currently under-represented regions, where new options could be tested

Monitoreo de servicios ecosistémicos en un observatorio de cafetales agroforestales. Recomendaciones para el sector cafetalero

Ocho años de estudio de la ecofisiología del café, a través de experimentación y de modelación y el monitoreo de los servicios del ecosistema (SE) en una gran finca cafetalera en Costa Rica, revelaron varias recomendaciones prácticas para los agricultores y los formuladores de políticas. El sistema de cultivo estudiado dentro de nuestro observatorio colaborativo (Coffee-Flux), corresponde a un sistema agroforestal (SAF) a base de café bajo la sombra de grandes árboles de Erythrina poeppigiana (16% de la cubierta del dosel). Una gran cantidad de SE y limitantes dependen de las propiedades locales del suelo (en este caso Andisoles), especialmente de la erosión/infiltración, el agua/carbono y la capacidad de almacenamiento de nutrientes. Por lo tanto, para la evaluación de SE, el tipo de suelo es crucial. Una densidad adecuada de árboles de sombra (bastante baja aquí por la condición de libre crecimiento), redujo la severidad de las enfermedades de las hojas con la posibilidad de reducir el uso de plaguicidas y fungicidas. Un inventario simple del área basal en el collar de las plantas de café permitió estimar la biomasa subterránea y la edad promedio de la plantación, para juzgar su valor de mercado y decidir cuándo reemplazarla. Las fincas de café probablemente estén mucho más cerca de la neutralidad de C que lo indicado en el protocolo actual de C-neutralidad, que solo considera árboles de sombra, no los cafetos ni el suelo. Se proponen evaluaciones más completas, que ncluyen árboles, café, hojarasca, suelo y raíces en el balance C del SAF. Los árboles de sombra ofrecen muchos SE si se gestionan adecuadamente en el contexto local. En comparación con las condiciones a pleno sol, los árboles de sombra pueden (i) reducir la erosión laminar en un factor de 2; (ii) aumentar la fijación de N y el % de N reciclado en el sistema, reduciendo así los requisitos de fertilizantes; (iii) reducir la severidad de enfermedades de las hojas; (iv) aumentar el secuestro de C; (v) mejorar el microclima y (vi) reducir sustancialmente los efectos del cambio climático. En nuestro estudio de caso, no se encontró ningún efecto negativo sobre el rendimiento del café

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM