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En 2009, se estudió la composición, abundancia y dispersión diurna de los peces presentes en la quebrada El Venado, ubicada en el corregimiento de Córdoba, municipio de Buenaventura, Valle del Cauca, Colombia. La quebrada es uno de los afluentes del río Dagua que desemboca en la Bahía de Buenaventura, en la costa Pacífica de Colombia. Se realizaron 6 muestreos mensuales con la técnica de electropesca (Lagler, 1956), identificándose 37 especies de peces hasta el nivel de especie y 9 morfotipos hasta el nivel de género. Los órdenes Characiformes (Familia Characidae) y Siluriformes (Familia Loricariidae) dominaron entre los peces en la quebrada durante el estudio, especialmente en las estaciones cercanas al basurero. En la estación 3, el número de especies (n = 23), familias (n = 13) y órdenes (n = 4) fue relativamente bajo en comparación con las otras estaciones. Por lo general, los peces registraron comunidades más saludables aguas arriba del basurero. Debido a sus características adaptativas, algunos peces, especialmente de la Familia Loricariidae, toleraron mejor las condiciones de las aguas aguas abajo del basurero que otros (Familia Characidae).

One of the most powerful cosmological data sets when it comes to constraining neutrino masses is represented by galaxy power spectrum measurements, Pgg(k). The constraining power of Pgg(k) is however severely limited by uncertainties in the modeling of the scale-dependent galaxy bias b(k). In this work we present a new proof-of-principle for a method to constrain b(k) by using the cross-correlation between the cosmic microwave background (CMB) lensing signal and galaxy maps (C κg) using a simple but theoretically well-motivated parametrization for b(k). We apply the method using C κg measured by cross-correlating Planck lensing maps and the Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 11 (DR11) CMASS galaxy sample, and Pgg(k) measured from the BOSS DR12 CMASS sample. We detect a nonzero scale-dependence at moderate significance, which suggests that a proper modeling of b(k) is necessary in order to reduce the impact of nonlinearities and minimize the corresponding systematics. The accomplished increase in constraining power of Pgg(k) is demonstrated by determining a 95% confidence level upper bound on the sum of the three active neutrino masses Mν of Mν

Small RNA-seq is increasingly being used for profiling of small RNAs. Quantitative characteristics of long RNA-seq have been extensively described, but small RNA-seq involves fundamentally different methods for library preparation, with distinct protocols and technical variations that have not been fully and systematically studied. We report here the results of a study using common references (synthetic RNA pools of defined composition, as well as plasma-derived RNA) to evaluate the accuracy, reproducibility and bias of small RNA-seq library preparation for five distinct protocols and across nine different laboratories. We observed protocol-specific and sequence-specific bias, which was ameliorated using adapters for ligation with randomized end-nucleotides, and computational correction factors. Despite this technical bias, relative quantification using small RNA-seq was remarkably accurate and reproducible, even across multiple laboratories using different methods. These results provide strong evidence for the feasibility of reproducible cross-laboratory small RNA-seq studies, even those involving analysis of data generated using different protocols.

Small RNA-seq is increasingly being used for profiling of small RNAs. Quantitative characteristics of long RNA-seq have been extensively described, but small RNA-seq involves fundamentally different methods for library preparation, with distinct protocols and technical variations that have not been fully and systematically studied. We report here the results of a study using common references (synthetic RNA pools of defined composition, as well as plasma-derived RNA) to evaluate the accuracy, reproducibility and bias of small RNA-seq library preparation for five distinct protocols and across nine different laboratories. We observed protocol-specific and sequence-specific bias, which was ameliorated using adapters for ligation with randomized end-nucleotides, and computational correction factors. Despite this technical bias, relative quantification using small RNA-seq was remarkably accurate and reproducible, even across multiple laboratories using different methods. These results provide strong evidence for the feasibility of reproducible cross-laboratory small RNA-seq studies, even those involving analysis of data generated using different protocols.

Abstract Background The lack of sufficient specificity and sensitivity among conventional cancer biomarkers, such as prostate specific antigen (PSA) for prostate cancer has been widely recognized after several decades of clinical implications. Autoantibodies (autoAb) among others are being extensively investigated as potential substitute markers, but remain elusive. One major obstacle is the lack of a sensitive and multiplex approach for quantifying autoAb against a large panel of clinically relevant tumor-associated antigens (TAA). Methods To circumvent preparation of phage lysates and purification of recombinant proteins, we identified B cell epitopes from a number of previously defined prostate cancer-associated antigens (PCAA). Peptide epitopes from cancer/testis antigen NY-ESO-1, XAGE-1b, SSX-2,4, as well as prostate cancer overexpressed antigen AMACR, p90 autoantigen, and LEDGF were then conjugated with seroMAP microspheres to allow multiplex measurement of autoAb present in serum samples. Moreover, simultaneous quantification of autoAb plus total PSA was achieved in one reaction, and termed the "A+PSA" assay. Results Peptide epitopes from the above 6 PCAA were identified and confirmed that autoAb against these peptide epitopes reacted specifically with the full-length protein. A pilot study was conducted with the A+PSA assay using pre-surgery sera from 131 biopsy-confirmed prostate cancer patients and 121 benign prostatic hyperplasia and/or prostatitis patients. A logistic regression-based A+PSA index was found to enhance sensitivities and specificities over PSA alone in distinguishing prostate cancer from nonmalignant cases. The A+PSA index also reduced false positive rate and improved the area under a receiver operating characteristic curve. Conclusions The A+PSA assay represents a novel platform that integrates autoAb signatures with a conventional cancer biomarker, which may aid in the diagnosis and prognosis of prostate cancer and others.

This study determined the efficacies of four classes of anthelmintics (AH) in a goat flock where anthelmintic resistance (AR) to ivermectin was suspected. We selected and randomly distributed 105 animals with >500 eggs per gram of feces into seven groups of 15 animals: an untreated control group and groups treated with ivermectin, eprinomectin, albendazole sulfoxide, albendazole, levamisole, and closantel. The goats were individually weighed and treated with the recommended dose. Fecal samples were collected 14 days post-treatment to determine the fecal egg counts and for a fecal egg count reduction test (FECRT). Coprocultures were also performed for identifying any resistant genera. A molecular assay (polymerase chain reaction, PCR) was used to confirm benzimidazole resistance. The FECRTs for the ivermectin, eprinomectin, albendazole sulfoxide, and albendazole treatments were

The text is a list of authors who have contributed to an article titled "Theme 02 - Genetics and Genomics" in the journal "Amyotrophic Lateral Sclerosis & Frontotemporal Degeneration." The article likely discusses the role of genetics and genomics in the development and progression of amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD). The list of authors is extensive and includes researchers from various institutions and countries, indicating a diverse range of perspectives and expertise in the field. [Extracted from the article]

Carbon steels can be heat treated to produce different microstructural variations and mechanical properties. At high temperatures the material plasticity and strength can be influenced by diffusional effects like the Portevin-Le Chatelier effect, leading to a commonly observed increased strength at elevated temperatures. The diffusional effects are influenced by the chemical composition, but also the heat treatment history that affects the local composition and especially the concentrations of free solute atoms. In this work, a numerical approach was implemented to reproduce the thermomechanical behaviour of two different microstructural variants of steel grade C45. The experimental data used to calibrate the model includes information of the plastic behaviour of material subjected to dynamic compression loading at a wide range of temperatures. Special emphasis was focused to describe the effects of the dynamic strain aging (DSA) on the flow stress. A strategy based on machine learning was implemented to obtain a model that reproduces the strengthening of the material due to diffusional effects. Cubic Support Vector Machine models were trained for both microstructure variants of the steel and different surfaces were obtained to describe the topology of the flow stress as function of temperature and strain rate. The model predictions were compared to the behaviour described by the Johnson-Cook model to estimate the influence of the DSA effect on the strength of the material at high strain rates and temperatures. Furthermore, the model quantifies how the microstructure affects the strength of the material and the strength of the DSA-hardening.