Response characteristics in the apex of the gerbil cochlea studied through auditory nerve recordings

In this study, we analyze the processing of low-frequency sounds in the cochlear apex through responses of auditory nerve fibers (ANFs) that innervate the apex. Single tones and irregularly spaced tone complexes were used to evoke ANF responses in Mongolian gerbil. The spike arrival times were analyzed in terms of phase locking, peripheral frequency selectivity, group delays, and the nonlinear effects of sound pressure level (SPL). Phase locking to single tones was similar to that in cat. Vector strength was maximal for stimulus frequencies around 500 Hz, decreased above 1 kHz, and became insignificant above 4 to 5 kHz. We used the responses to tone complexes to determine amplitude and phase curves of ANFs having a characteristic frequency (CF) below 5 kHz. With increasing CF, amplitude curves gradually changed from broadly tuned and asymmetric with a steep low-frequency flank to more sharply tuned and asymmetric with a steep high-frequency flank. Over the same CF range, phase curves gradually changed from a concave-upward shape to a concave-downward shape. Phase curves consisted of two or three approximately straight segments. Group delay was analyzed separately for these segments. Generally, the largest group delay was observed near CF. With increasing SPL, most amplitude curves broadened, sometimes accompanied by a downward shift of best frequency, and group delay changed along the entire range of stimulus frequencies. We observed considerable across-ANF variation in the effects of SPL on both amplitude and phase. Overall, our data suggest that mechanical responses in the apex of the cochlea are considerably nonlinear and that these nonlinearities are of a different character than those known from the base of the cochlea

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Racial differences in smoking abstinence rates in a multicenter, randomized, open-label trial in the United States

Background: This study evaluates differences in smoking abstinence between white and minority smokers using pharmaceutical aids. Methods: This is an analysis of data from a multi-center, randomized, clinical trial conducted in the United States. Of the 1,684 subjects randomized to one of three medications (nicotine inhaler, bupropion, or a combination of both), 60% were women and 10% were minority races. Results: Factors associated with a decreased likelihood of smoking at 12 weeks were older age (OR = 0.971, p\u3c 0.0001), being married (OR = 0.678, p= 0.0029), using bupropion SR (OR = 0.480, p∈\u3c∈0.0001), and using combination therapy (OR = 0.328, p∈\u3c∈0.0001). Factors associated with an increased likelihood of smoking were higher tobacco dependence scores (OR = 1.244, p \u3c 0.0001), prior quit attempts (OR = 1.812, p=0.004), and being a minority (OR = 1.849, p=0.0083). Compared to white smokers, minority smokers were significantly older at time of study entry (46 vs. 42 years, p\u3c 0.0001), less likely to be married (35% vs. 59%, p\u3c 0.0001), older at smoking initiation (21 vs. 19 years of age, p\u3c 0.0001), and had a lower abstinence rate (16% vs. 26%, p=0.0065). Conclusion: Regardless of the treatment used, minority smokers in the US have lower smoking abstinence after treatment for tobacco dependence. Future research should focus on the improvement in treatment strategies for minority smokers

Monitoring lactoferrin iron levels by fluorescence resonance energy transfer: A combined chemical and computational study

Three forms of lactoferrin (Lf) that differed in their levels of iron loading (Lf, LfFe, and LfFe2) were simultaneously labeled with the fluorophores AF350 and AF430. All three resulting fluorescent lactoferrins exhibited fluorescence resonance energy transfer (FRET), but they all presented different FRET patterns. Whereas only partial FRET was observed for Lf and LfFe, practically complete FRET was seen for the holo form (LfFe2). For each form of metal-loaded lactoferrin, the AF350–AF430 distance varied depending on the protein conformation, which in turn depended on the level of iron loading. Thus, the FRET patterns of these lactoferrins were found to correlate with their iron loading levels. In order to gain greater insight into the number of fluorophores and the different FRET patterns observed (i.e., their iron levels), a computational analysis was performed. The results highlighted a number of lysines that have the greatest influence on the FRET profile. Moreover, despite the lack of an X-ray structure for any LfFe species, our study also showed that this species presents modified subdomain organization of the N-lobe, which narrows its iron-binding site. Complete domain rearrangement occurs during the LfFe to LfFe2 transition. Finally, as an example of the possible applications of the results of this study, we made use of the FRET fingerprints of these fluorescent lactoferrins to monitor the interaction of lactoferrin with a healthy bacterium, namely Bifidobacterium breve. This latter study demonstrated that lactoferrin supplies iron to this bacterium, and suggested that this process occurs with no protein internalization.This work was supported by MINECO and FEDER (projects CTQ2012-32236, CTQ2011-23336, and BIO2012-39682-C02-02) and BIOSEARCH SA. F.C. and V.M.R. are grateful to the Spanish MINECO for FPI fellowships

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

Improving topological cluster reconstruction using calorimeter cell timing in ATLAS

Clusters of topologically connected calorimeter cells around cells with large absolute signal-to-noise ratio (topo-clusters) are the basis for calorimeter signal reconstruction in the ATLAS experiment. Topological cell clustering has proven performant in LHC Runs 1 and 2. It is, however, susceptible to out-of-time pile-up of signals from soft collisions outside the 25 ns proton-bunch-crossing window associated with the event’s hard collision. To reduce this effect, a calorimeter-cell timing criterion was added to the signal-to-noise ratio requirement in the clustering algorithm. Multiple versions of this criterion were tested by reconstructing hadronic signals in simulated events and Run 2 ATLAS data. The preferred version is found to reduce the out-of-time pile-up jet multiplicity by ∼50% for jet pT ∼ 20 GeV and by ∼80% for jet pT 50 GeV, while not disrupting the reconstruction of hadronic signals of interest, and improving the jet energy resolution by up to 5% for 20 < pT < 30 GeV. Pile-up is also suppressed for other physics objects based on topo-clusters (electrons, photons, τ -leptons), reducing the overall event size on disk by about 6% in early Run 3 pileup conditions. Offline reconstruction for Run 3 includes the timing requirement

Software Performance of the ATLAS Track Reconstruction for LHC Run 3

Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pileup) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60 pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two