An improved methodology for the recovery of Zea mays and other large crop pollen, with implications for environmental archaeology in the Neotropics

We present a simple sieving methodology to aid the recovery of large cultigen pollen grains, such as maize (Zea mays L.), manioc (Manihot esculenta Crantz), and sweet potato (Ipomoea batatas L.), among others, for the detection of food production using fossil pollen analysis of lake sediments in the tropical Americas. The new methodology was tested on three large study lakes located next to known and/or excavated pre-Columbian archaeological sites in South and Central America. Five paired samples, one treated by sieving, the other prepared using standard methodology, were compared for each of the three sites. Using the new methodology, chemically digested sediment samples were passed through a 53 µm sieve, and the residue was retained, mounted in silicone oil, and counted for large cultigen pollen grains. The filtrate was mounted and analysed for pollen according to standard palynological procedures. Zea mays (L.) was recovered from the sediments of all three study lakes using the sieving technique, where no cultigen pollen had been previously recorded using the standard methodology. Confidence intervals demonstrate there is no significant difference in pollen assemblages between the sieved versus unsieved samples. Equal numbers of exotic Lycopodium spores added to both the filtrate and residue of the sieved samples allow for direct comparison of cultigen pollen abundance with the standard terrestrial pollen count. Our technique enables the isolation and rapid scanning for maize and other cultigen pollen in lake sediments, which, in conjunction with charcoal and pollen records, is key to determining land-use patterns and the environmental impact of pre-Columbian societies

A temporal dimension to the influence of pollen rewards on bee behaviour and fecundity in Aloe tenuior

The net effect of pollen production on fecundity in plants can range from negative – when self-pollen interferes with fecundity due to incompatibility mechanisms, to positive – when pollen availability is associated with increased pollinator visitation and fecundity due to its utilization as a reward. We investigated the responses of bees to pollen and nectar rewards, and the effects of these rewards on pollen deposition and fecundity in the hermaphroditic succulent shrub Aloe tenuior. Self-pollinated plants failed to set fruit, but their ovules were regularly penetrated by self-pollen tubes, which uniformly failed to develop into seeds as expected from ovarian self-incompatibility (or strong early inbreeding depression). Bees consistently foraged for pollen during the morning and early afternoon, but switched to nectar in the late afternoon. As a consequence of this differential foraging, we were able to test the relative contribution to fecundity of pollen- versus nectar-collecting flower visitors. We exposed emasculated and intact flowers in either the morning or late afternoon to foraging bees and showed that emasculation reduced pollen deposition by insects in the morning, but had little effect in the afternoon. Despite the potential for self-pollination to result in ovule discounting due to late-acting self-sterility, fecundity was severely reduced in artificially emasculated plants. Although there were temporal fluctuations in reward preference, most bee visits were for pollen rewards. Therefore the benefit of providing pollen that is accessible to bee foragers outweighs any potential costs to fitness in terms of gender interference in this species

A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry

[EN] This document presents a comparison of demand forecasting methods, with the aim of improving demand forecasting and with it, the production planning system of Ecuadorian textile industry. These industries present problems in providing a reliable estimate of future demand due to recent changes in the Ecuadorian context. The impact on demand for textile products has been observed in variables such as sales prices and manufacturing costs, manufacturing gross domestic product and the unemployment rate. Being indicators that determine to a great extent, the quality and accuracy of the forecast, generating also, uncertainty scenarios. For this reason, the aim of this work is focused on the demand forecasting for textile products by comparing a set of classic methods such as ARIMA, STL Decomposition, Holt-Winters and machine learning, Artificial Neural Networks, Bayesian Networks, Random Forest, Support Vector Machine, taking into consideration all the above mentioned, as an essential input for the production planning and sales of the textile industries. And as a support, when developing strategies for demand management and medium-term decision making of this sector under study. Finally, the effectiveness of the methods is demonstrated by comparing them with different indicators that evaluate the forecast error, with the Multi-layer Neural Networks having the best results with the least error and the best performance.The authors are greatly grateful by the support given by the SDAS Research Group (https://sdas-group.com/).Lorente-Leyva, LL.; Alemany Díaz, MDM.; Peluffo-Ordóñez, DH.; Herrera-Granda, ID. (2021). 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The Latin American Consortium of Studies in Obesity (LASO)

Current, high-quality data are needed to evaluate the health impact of the epidemic of obesity in Latin America. The Latin American Consortium of Studies of Obesity (LASO) has been established, with the objectives of (i) Accurately estimating the prevalence of obesity and its distribution by sociodemographic characteristics; (ii) Identifying ethnic, socioeconomic and behavioural determinants of obesity; (iii) Estimating the association between various anthropometric indicators or obesity and major cardiovascular risk factors and (iv) Quantifying the validity of standard definitions of the various indexes of obesity in Latin American population. To achieve these objectives, LASO makes use of individual data from existing studies. To date, the LASO consortium includes data from 11 studies from eight countries (Argentina, Chile, Colombia, Costa Rica, Dominican Republic, Peru, Puerto Rico and Venezuela), including a total of 32 462 subjects. This article describes the overall organization of LASO, the individual studies involved and the overall strategy for data analysis. LASO will foster the development of collaborative obesity research among Latin American investigators. More important, results from LASO will be instrumental to inform health policies aiming to curtail the epidemic of obesity in the region

Use of mitogenic cascade blockers for treatment of C-Raf induced lung adenoma in vivo: CI-1040 strongly reduces growth and improves lung structure

BACKGROUND: Signaling networks promoting cell growth and proliferation are frequently deregulated in cancer. Tumors often are highly dependent on such signaling pathways and may become hypersensitive to downregulation of key components within these signaling cascades. The classical mitogenic cascade transmits stimuli from growth factor receptors via Ras, Raf, MEK and ERK to the cell nucleus and provides attractive molecular targets for cancer treatment. For example, Ras and Raf kinase inhibitors are already in a number of ongoing phase II and phase III clinical trials. In this study the effect of the Raf kinase inhibitor BAY 43-9006 and of the MEK inhibitor CI-1040 (PD184352) on a Raf dependent lung tumor mouse model was analyzed in detail. METHODS: We have generated a lung cancer mouse model by targeting constitutively active C-Raf kinase to the lung. These mice develop adenomas within 4 months of life. At this time-point they received daily intraperitoneal injections of either 100 mg/kg BAY 43-9006 or CI-1040 for additional 21 days. Thereafter, lungs were isolated and the following parameters were analyzed using histology and immunohistochemistry: overall lung structure, frequency of adenoma foci, proliferation rate, ERK activity, caspase-3 activation, and lung differentiation. RESULTS: Both inhibitors were equally effective in vitro using a sensitive Raf/MEK/ERK ELISA. In vivo, the systemic administration of the MEK inhibitor CI-1040 reduced adenoma formation to a third and significantly restored lung structure. The proliferation rate of lung cells of mice treated with CL-1040 was decreased without any obvious effects on differentiation of pneumocytes. In contrast, the Raf inhibitor BAY 43-9006 did not influence adenoma formation in vivo. CONCLUSION: The MEK inhibitor CI-1040 may be used for the treatment of Ras and/or Raf-dependent human malignancies

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Measurement of the cross-section of high transverse momentum vector bosons reconstructed as single jets and studies of jet substructure in pp collisions at √s = 7 TeV with the ATLAS detector

This paper presents a measurement of the cross-section for high transverse momentum W and Z bosons produced in pp collisions and decaying to all-hadronic final states. The data used in the analysis were recorded by the ATLAS detector at the CERN Large Hadron Collider at a centre-of-mass energy of √s = 7 TeV;{\rm Te}{\rm V}$and correspond to an integrated luminosity of$4.6\;{\rm f}{{{\rm b}}^{-1}}$. The measurement is performed by reconstructing the boosted W or Z bosons in single jets. The reconstructed jet mass is used to identify the W and Z bosons, and a jet substructure method based on energy cluster information in the jet centre-of-mass frame is used to suppress the large multi-jet background. The cross-section for events with a hadronically decaying W or Z boson, with transverse momentum${{p}_{{\rm T}}}\gt 320\;{\rm Ge}{\rm V}$and pseudorapidity$|\eta |\lt 1.9$, is measured to be${{\sigma }_{W+Z}}=8.5\pm 1.7$ pb and is compared to next-to-leading-order calculations. The selected events are further used to study jet grooming techniques

Circulating DNA: Diagnostic Tool and Predictive Marker for Overall Survival of NSCLC Patients

PURPOSE: The purpose of our study was to determine whether the amounts of circulating DNA (cDNA) could discriminate between NSCLC patients and healthy individuals and assess its value as a prognostic marker of this disease. METHODS: We conducted a study of 309 individuals and the cDNA levels were assessed through real-time PCR methodology. RESULTS: We found increased cDNA levels in NSCLC patients compared to control individuals. We also found a decreased overall survival time in patients presenting high cDNA levels, when compared to lower cDNA concentrations. CONCLUSIONS: Quantification of cDNA may be a good tool for NSCLC detection with potential for clinical applicability