Understory plant diversity assessment of Szemao pine (Pinus kesiya var. langbianensis) plantations in Yunnan, China

Evaluación de la diversidad de plantas de sotobosque en plantaciones de pino Szemao (Pinus kesiya var. langbianensis) en Yunnan, China.— La sostenibilidad es un objetivo clave para la gestión tanto de bosques naturales como de plantaciones, mientras que los estudios sobre biodiversidad constituyen herramientas muy útiles para mejorar la conservación de especies amenazadas. El pino Szemao (Pinus kesiya var. langbianensis) es un árbol nativo de China que se usa en plantaciones. Este estudio evalúa la diversidad del sotobosque en plantaciones de pino Szemao (SP) y otros tipos de vegetación local, como bosques secundarios perennifolios (SE) y tierras de cultivo abandonadas (AF), en la provincia de Yunnan, China. El muestreo se realizó en tres rangos altitudinales, y se evaluó riqueza y cobertura de hierbas y arbustos además de factores ambientales. En general, la riqueza promedio y la diversidad de Shannon-Wiener fueron mayores en SE que en SP, y a su vez que en AF, mientras que la equitatividad tendió a ser mayor en SP. Asimismo, dichos índices tendieron a aumentar con la altitud en SP y AF, aunque en SE fueron mayores a altitudes bajas y medias. La inclusión de factores ambientales resaltó las diferencias entre rangos altitudinales, siendo el contenido de agua (en el estrato herbáceo) y el tipo de suelo (en el estrato arbustivo) las variables más significativas. Las plantaciones de pino Szemao en Yunnan afectan al sotobosque, encontrándose pocas especies raras o amenazadas en su interior. Las reservas naturales y los trasplantes podrían ser una alternativa para proteger a las especies amenazadas si se llevan a cabo anticipadamente a las plantaciones.Sustainability is a key objective for managers of both natural forests and plantations, and biodiversity assessments are important tools to improve conservation of endangered species. Szemao pine (Pinus kesiya var. langbianensis) is a native Chinese tree species used in plantations. This study evaluated differences in understory diversity among Szemao pine plantations (SP) and other local current vegetation types: secondary evergreen forests (SE) and abandoned farmlands (AF) in Yunnan Province. Sampling was performed at three elevation ranges, where species richness, species cover, and environmental variables in the herb and shrub layers were measured. We found that indexes for average richness and Shannon?Wiener diversity were higher in SE than in SP, which were in turn higher than in AF, while the index for evenness was higher in SP. These indexes increased with elevation in SP and AF, but were higher at low and medium elevations in SE. Inclusion of environmental factors highlighted elevation differences, with water content (at herb layer) and soil type (at shrub layer) being the most significant variables. In conclusion, plantations of Szemao pine negatively affect understory diversity in Yunnan, and furthermore, only a few rare or threatened species could be found in the plantations. Nature reserves and transplanting could protect threatened species if established before plantations.Fil: Wang, H.F.. Research Center for Eco-Environmental Sciences; ChinaFil: Lencinas, María Vanessa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; ArgentinaFil: Ross Friedman, Cynthia. Thompson Rivers University.; CanadáFil: Zhu, Z.X.. Institute of Botany. Chinese Academy of Sciences; ChinaFil: Qiu, J. Research Center for Eco-Environmental Sciences; Chin

On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection

Humans are the final decision makers in critical tasks that involve ethical and legal concerns, ranging from recidivism prediction, to medical diagnosis, to fighting against fake news. Although machine learning models can sometimes achieve impressive performance in these tasks, these tasks are not amenable to full automation. To realize the potential of machine learning for improving human decisions, it is important to understand how assistance from machine learning models affects human performance and human agency. In this paper, we use deception detection as a testbed and investigate how we can harness explanations and predictions of machine learning models to improve human performance while retaining human agency. We propose a spectrum between full human agency and full automation, and develop varying levels of machine assistance along the spectrum that gradually increase the influence of machine predictions. We find that without showing predicted labels, explanations alone slightly improve human performance in the end task. In comparison, human performance is greatly improved by showing predicted labels (>20% relative improvement) and can be further improved by explicitly suggesting strong machine performance. Interestingly, when predicted labels are shown, explanations of machine predictions induce a similar level of accuracy as an explicit statement of strong machine performance. Our results demonstrate a tradeoff between human performance and human agency and show that explanations of machine predictions can moderate this tradeoff.Comment: 17 pages, 19 figures, in Proceedings of ACM FAT* 2019, dataset & demo available at https://deception.machineintheloop.co

Aberrant Cytoplasm Localization and Protein Stability of SIRT1 is Regulated by PI3K/IGF-1R Signaling in Human Cancer Cells

SIRT1, an NAD-dependent histone/protein deacetylase, has classically been thought of as a nuclear protein. In this study, we demonstrate that SIRT1 is mainly localized in the nucleus of normal cells, but is predominantly localized in the cytoplasm of the cancer / transformed cells we tested. We found this predominant cytoplasmic localization of SIRT1 is regulated by elevated mitotic activity and PI3K/IGF-1R signaling in cancer cells. We show that aberrant cytoplasmic localization of SIRT1 is due to increased protein stability and is regulated by PI3K/IGF-1R signaling. In addition, we determined that SIRT1 is required for PI3K-mediated cancer cell growth. Our study represents the first identification that aberrant cytoplasm localization is one of the specific alternations to SIRT1 that occur in cancer cells, and PI3K/IGF-1R signaling plays an important role in the regulation of cytoplasmic SIRT1 stability. Our findings suggest that the over-expressed cytoplasmic SIRT1 in cancer cells may greatly contribute to its cancer-specific function by working downstream of the PI3K/IGF-1R signaling pathway

Novel genome polymorphisms in BCG vaccine strains and impact on efficacy

Bacille Calmette-Guérin (BCG) is an attenuated strain of Mycobacterium bovis currently used as a vaccine against tuberculosis. Global distribution and propagation of BCG has contributed to the in vitro evolution of the vaccine strain and is thought to partially account for the different outcomes of BCG vaccine trials. Previous efforts by several molecular techniques effectively identified large sequence polymorphisms among BCG daughter strains, but lacked the resolution to identify smaller changes. In this study, we have used a NimbleGen tiling array for whole genome comparison of 13 BCG strains. Using this approach, in tandem with DNA resequencing, we have identified six novel large sequence polymorphisms including four deletions and two duplications in specific BCG strains. Moreover, we have uncovered various polymorphisms in the phoP-phoR locus. Importantly, these polymorphisms affect genes encoding established virulence factors including cell wall complex lipids, ESX secretion systems, and the PhoP-PhoR two-component system. Our study demonstrates that major virulence factors are different among BCG strains, which provide molecular mechanisms for important vaccine phenotypes including adverse effect profile, tuberculin reactivity and protective efficacy. These findings have important implications for the development of a new generation of vaccines

Repetitive Sequence Variations in the Promoter Region of the Adhesin-Encoding Gene sabA of Helicobacter pylori Affect Transcription

The pathogenesis of diseases elicited by the gastric pathogen Helicobacter pylori is partially determined by the effectiveness of adaptation to the variably acidic environment of the host stomach. Adaptation includes appropriate adherence to the gastric epithelium via outer membrane protein adhesins such as SabA. The expression of sabA is subject to regulation via phase variation in the promoter and coding regions as well as repression by the two-component system ArsRS. In this study, we investigated the role of a homopolymeric thymine [poly(T)] tract -50 to -33 relative to the sabA transcriptional start site in H. pylori strain J99. We quantified sabA expression in H. pylori J99 by quantitative reverse transcription-PCR (RT-PCR), demonstrating significant changes in sabA expression associated with experimental manipulations of poly(T) tract length. Mimicking the length increase of this tract by adding adenines instead of thymines had similar effects, while the addition of other nucleotides failed to affect sabA expression in the same manner. We hypothesize that modification of the poly(T) tract changes DNA topology, affecting regulatory protein interaction(s) or RNA polymerase binding efficiency. Additionally, we characterized the interaction between the sabA promoter region and ArsR, a response regulator affecting sabA expression. Using recombinant ArsR in electrophoretic mobility shift assays (EMSA), we localized binding to a sequence with partial dyad symmetry -20 and +38 relative to the sabA + 1 site. The control of sabA expression by both ArsRS and phase variation at two distinct repeat regions suggests the control of sabA expression is both complex and vital to H. pylori infection

Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads.

As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples. We term this approach leaderboard metagenome sequencing. To explore protocol optimization for leaderboard metagenomics in real samples, we introduce a benchmark of library prep and sequencing using internal references generated by synthetic long-read technology, allowing us to evaluate high-throughput library preparation methods against gold-standard reference genomes derived from the samples themselves. We introduce a low-cost protocol for high-throughput library preparation and sequencing

Contrasting effects of CO₂ fertilization, land-use change and warming on seasonal amplitude of Northern Hemisphere CO₂ exchange

Continuous atmospheric CO₂ monitoring data indicate an increase in the amplitude of seasonal CO₂-cycle exchange (SCA_(NBP)) in northern high latitudes. The major drivers of enhanced SCA_(NBP) remain unclear and intensely debated, with land-use change, CO₂ fertilization and warming being identified as likely contributors. We integrated CO₂-flux data from two atmospheric inversions (consistent with atmospheric records) and from 11 state-of-the-art land-surface models (LSMs) to evaluate the relative importance of individual contributors to trends and drivers of the SCA_(NBP) of CO₂ fluxes for 1980–2015. The LSMs generally reproduce the latitudinal increase in SCA_(NBP) trends within the inversions range. Inversions and LSMs attribute SCA_(NBP) increase to boreal Asia and Europe due to enhanced vegetation productivity (in LSMs) and point to contrasting effects of CO₂ fertilization (positive) and warming (negative) on SCA_(NBP). Our results do not support land-use change as a key contributor to the increase in SCA_(NBP). The sensitivity of simulated microbial respiration to temperature in LSMs explained biases in SCA_(NBP) trends, which suggests that SCA_(NBP) could help to constrain model turnover times

COSINUS: Cryogenic Calorimeters for the Direct Dark Matter Search with NaI Crystals

COSINUS (Cryogenic Observatory for SIgnatures seen in Next-generation Underground Searches) is an experiment employing cryogenic calorimeters, dedicated to direct dark matter search in underground laboratories. Its goal is to cross-check the annual modulation signal the DAMA collaboration has been detecting for about 20 years (Bernabei et al. in Nucl Part Phys Proc 303-305:74-79, 2018. 10.1016/j.nuclphysbps.2019.03.015) and which has been ruled out by other experiments in certain dark matter scenarios. COSINUS can provide a model-independent test by the use of the same target material (NaI), with the additional chance of discriminating beta/gamma events from nuclear recoils on an event-by-event basis, by the application of a well-established temperature sensor technology developed within the CRESST collaboration. Each module is constituted by two detectors: the light detector, that is a silicon beaker equipped with a transition edge sensor (TES), and the phonon detector, a small cubic NaI crystal interfaced with a carrier of a harder material (e.g. CdWO4), also instrumented with a TES. This technology had so far never been applied to NaI crystals because of several well-known obstacles, and COSINUS is the first experiment which succeeded in operating NaI crystals as cryogenic calorimeters. Here, we present the COSINUS project, describe the achievements and the challenges of the COSINUS prototype development and discuss the status and the perspectives of this NaI-based cryogenic frontier

Greater Fructose Consumption Is Associated with Cardiometabolic Risk Markers and Visceral Adiposity in Adolescents

Though adolescents consume more fructose than any other age group, the relationship between fructose consumption and markers of cardiometabolic risk has not been established in this population. We determined associations of total fructose intake (free fructose plus one-half the intake of free sucrose) with cardiometabolic risk factors and type of adiposity in 559 adolescents aged 14–18 y. Fasting blood samples were measured for glucose, insulin, lipids, adiponectin, and C-reactive protein. Diet was assessed with 4–7 24-h recalls and physical activity (PA) was determined by accelerometry. Fat-free soft tissue (FFST) mass and fat mass were measured by DXA. The s.c. abdominal adipose tissue (SAAT) and visceral adipose tissue (VAT) were assessed using MRI. Multiple linear regression, adjusting for age, sex, race, Tanner stage, FFST mass, fat mass, PA, energy intake, fiber intake, and socioeconomic status, revealed that fructose intake was associated with VAT (β = 0.13; P = 0.03) but not SAAT (P = 0.15). Significant linear upward trends across tertiles of fructose intake were observed for systolic blood pressure, fasting glucose, HOMA-IR, and C-reactive protein after adjusting for the same covariates (all P-trend 0.05). In adolescents, higher fructose consumption is associated with multiple markers of cardiometabolic risk, but it appears that these relationships are mediated by visceral obesity