Evidential statistics as a statistical modern synthesis to support 21st century science

During the 20th century, population ecology and science in general relied on two very different statistical paradigms to solve its inferential problems: error statistics (also referred to as classical statistics and frequentist statistics) and Bayesian statistics. A great deal of good science was done using these tools, but both schools suffer from technical and philosophical difficulties. At the turning of the 21st century (Royall in Statistical evidence: a likelihood paradigm. Chapman & Hall, London, 1997 ; Lele in The nature of scientific evidence: statistical, philosophical and empirical considerations. The University of Chicago Press, Chicago, pp 191–216, 2004a ), evidential statistics emerged as a seriously contending paradigm. Drawing on and refining elements from error statistics, likelihoodism, Bayesian statistics, information criteria, and robust methods, evidential statistics is a statistical modern synthesis that smoothly incorporates model identification, model uncertainty, model comparison, parameter estimation, parameter uncertainty, pre-data control of error, and post-data strength of evidence into a single coherent framework. We argue that evidential statistics is currently the most effective statistical paradigm to support 21st century science. Despite the power of the evidential paradigm, we think that there is no substitute for learning how to clarify scientific arguments with statistical arguments. In this paper we sketch and relate the conceptual bases of error statistics, Bayesian statistics and evidential statistics. We also discuss a number of misconceptions about the paradigms that have hindered practitioners, as well as some real problems with the error and Bayesian statistical paradigms solved by evidential statistics.     

Acoustic sequences in non‐human animals: a tutorial review and prospectus

Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well‐known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise – let alone understand – the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near‐future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, ‘Analysing vocal sequences in animals’. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial‐style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality.     

Precocious flowering of juvenile citrus induced by a viral vector based on Citrus leaf blotch virus: a new tool for genetics and breeding

The long juvenile period of citrus trees (often more than 6 years) has hindered genetic improvement by traditional breeding methods and genetic studies. In this work, we have developed a biotechnology tool to promote transition from the vegetative to the reproductive phase in juvenile citrus plants by expression of the Arabidopsis thaliana or citrus FLOWERING LOCUS T (FT) genes using a Citrus leaf blotch virus‐based vector (clbvINpr‐AtFT and clbvINpr‐CiFT, respectively). Citrus plants of different genotypes graft inoculated with either of these vectors started flowering within 4–6 months, with no alteration of the plant architecture, leaf, flower or fruit morphology in comparison with noninoculated adult plants. The vector did not integrate in or recombine with the plant genome nor was it pollen or vector transmissible, albeit seed transmission at low rate was detected. The clbvINpr‐AtFT is very stable, and flowering was observed over a period of at least 5 years. Precocious flowering of juvenile citrus plants after vector infection provides a helpful and safe tool to dramatically speed up genetic studies and breeding programmes.     

Tousled‐like kinase 2 regulates recovery from a DNA damage‐induced G2 arrest

In order to maintain a stable genome, cells need to detect and repair DNA damage before they complete the division cycle. To this end, cell cycle checkpoints prevent entry into the next cell cycle phase until the damage is fully repaired. Proper reentry into the cell cycle, known as checkpoint recovery, requires that a cell retains its original cell cycle state during the arrest. Here, we have identified Tousled‐like kinase 2 (Tlk2) as an important regulator of recovery after DNA damage in G2. We show that Tlk2 regulates the Asf1A histone chaperone in response to DNA damage and that depletion of Asf1A also produces a recovery defect. Both Tlk2 and Asf1A are required to restore histone H3 incorporation into damaged chromatin. Failure to do so affects expression of pro‐mitotic genes and compromises the cellular competence to recover from damage‐induced cell cycle arrests. Our results demonstrate that Tlk2 promotes Asf1A function during the DNA damage response in G2 to allow for proper restoration of chromatin structure at the break site and subsequent recovery from the arrest.     

Attenuation of pattern recognition receptor signaling is mediated by a MAP kinase kinase kinase

Pattern recognition receptors (PRRs) play a key role in plant and animal innate immunity. PRR binding of their cognate ligand triggers a signaling network and activates an immune response. Activation of PRR signaling must be controlled prior to ligand binding to prevent spurious signaling and immune activation. Flagellin perception in Arabidopsis through FLAGELLIN‐SENSITIVE 2 (FLS2) induces the activation of mitogen‐activated protein kinases (MAPKs) and immunity. However, the precise molecular mechanism that connects activated FLS2 to downstream MAPK cascades remains unknown. Here, we report the identification of a differentially phosphorylated MAP kinase kinase kinase that also interacts with FLS2. Using targeted proteomics and functional analysis, we show that MKKK7 negatively regulates flagellin‐triggered signaling and basal immunity and this requires phosphorylation of MKKK7 on specific serine residues. MKKK7 attenuates MPK6 activity and defense gene expression. Moreover, MKKK7 suppresses the reactive oxygen species burst downstream of FLS2, suggesting that MKKK7‐mediated attenuation of FLS2 signaling occurs through direct modulation of the FLS2 complex.     

Absence of Tau triggers age‐dependent sciatic nerve morphofunctional deficits and motor impairment

Dementia is the cardinal feature of Alzheimer's disease (AD), yet the clinical symptoms of this disorder also include a marked loss of motor function. Tau abnormal hyperphosphorylation and malfunction are well‐established key events in AD neuropathology but the impact of the loss of normal Tau function in neuronal degeneration and subsequent behavioral deficits is still debated. While Tau reduction has been increasingly suggested as therapeutic strategy against neurodegeneration, particularly in AD, there is controversial evidence about whether loss of Tau progressively impacts on motor function arguing about damage of CNS motor components. Using a variety of motor‐related tests, we herein provide evidence of an age‐dependent motor impairment in Tau?/? animals that is accompanied by ultrastructural and functional impairments of the efferent fibers that convey motor‐related information. Specifically, we show that the sciatic nerve of old (17–22‐months) Tau?/? mice displays increased degenerating myelinated fibers and diminished conduction properties, as compared to age‐matched wild‐type (Tau+/+) littermates and younger (4–6 months) Tau?/? and Tau+/+ mice. In addition, the sciatic nerves of Tau?/? mice exhibit a progressive hypomyelination (assessed by g‐ratio) specifically affecting large‐diameter, motor‐related axons in old animals. These findings suggest that loss of Tau protein may progressively impact on peripheral motor system.     

Unintended irradiation of internal mammary chain – Is that enough?

Aim

To evaluate the unintentional coverage of the internal mammary chain (IMC) with tangential fields irradiation to the breast, and its relation with the type of surgery employed.

Background

The dose distribution in regions adjacent to the treatment targets (mammary gland or chest wall), with incidental irradiation of the IMC, could translate into clinical benefit, due to the proximity of these regions.

Materials and methods

One hundred and twelve consecutive conformal radiotherapy plans were correlating the average dose to the IMC with the type of surgery employed, the extent of disease and the irradiation techniques.

Results

The mean doses to IMC after modified radical mastectomy (MRM), modified radical mastectomy with immediate reconstruction (MRM + R), and breast conservative surgery (BCS) were 30.34 Gy, 30.26 Gy, and 18.67 Gy, respectively. Significant differences were identified between patients who underwent MRM or MRM + R over BCS (p = 0.01 and 0.003, respectively), but not between MRM and MRM + R (p = 0.88). Mean doses to IMC were greater in patients with T3–T4 tumors when compared with more initial stages (≤T2) (p = 0.0096). The lymph node involvement also correlated with higher average doses to IMC (node positive: 26.1 Gy × node negative: 17.8 Gy, p = 0.0017).

Conclusions

The moderate dose level to the IMC in the unintentional irradiation scenario seems to be insufficient to treat the subclinical disease, although it could have an impact in patients undergoing mastectomy.     

Protein-Based Classifier to Predict Conversion from Clinically Isolated Syndrome to Multiple Sclerosis

Multiple sclerosis is an inflammatory, demyelinating, and neurodegenerative disease of the central nervous system. In most patients, the disease initiates with an episode of neurological disturbance referred to as clinically isolated syndrome, but not all patients with this syndrome develop multiple sclerosis over time, and currently, there is no clinical test that can conclusively establish whether a patient with a clinically isolated syndrome will eventually develop clinically defined multiple sclerosis. Here, we took advantage of the capabilities of targeted mass spectrometry to establish a diagnostic molecular classifier with high sensitivity and specificity able to differentiate between clinically isolated syndrome patients with a high and a low risk of developing multiple sclerosis. Based on the combination of abundances of proteins chitinase 3-like 1 and ala-β-his-dipeptidase in cerebrospinal fluid, we built a statistical model able to assign to each patient a precise probability of conversion to clinically defined multiple sclerosis. Our results are of special relevance for patients affected by multiple sclerosis as early treatment can prevent brain damage and slow down the disease progression.Multiple sclerosis is an inflammatory, demyelinating, and neurodegenerative disease of the central nervous system, and although the etiology of the disease is not fully understood, it is probably caused by the interaction of a complex genetic architecture and environmental factors. Multiple sclerosis affects over 2 million people worldwide, and it is typically diagnosed between ages 20 and 40, thus making a significant impact on public health and its economy (1).In most patients, the disease initiates with an episode of neurological disturbance referred to as clinically isolated syndrome. However, not all patients with this syndrome develop multiple sclerosis over time (2), and currently, the magnetic resonance imaging (MRI) abnormalities and the presence of IgG oligoclonal bands in cerebrospinal fluid (CSF) are used as predictors for later conversion to clinically definite multiple sclerosis (CDMS)¹ (3–5). Although such abnormalities are considered important factors that influence the likelihood of developing CDMS, there is currently no clinical test that can conclusively establish whether a patient with a clinically isolated syndrome will eventually develop CDMS.The lack of diagnostic and prognostic biomarkers is a common problem for many diseases lacking a complete etiology, which is the case for most neurological disorders related to the central nervous system such as Parkinson''s and Alzheimer''s diseases, schizophrenia, and multiple sclerosis. In the particular case of multiple sclerosis, early treatment of patients with a clinically isolated syndrome can prevent brain damage and slow down the disease progression (6). Therefore, the availability of a diagnostic test in the initial stages of the disease is not only desirable but also of extreme relevance to attenuate the degenerative effects of the disease.Biomarker validation has traditionally been dominated by enzyme linked immuno-sorbent assays (ELISA), but recent advances in proteomics techniques have enabled the measurement of a subset of selected proteins over a large dynamic concentration range in multiple samples. Targeted mass spectrometry has thus become the method of choice when quantifying simultaneously a panel of proteins across many different biological samples (7–9). In particular, selected reaction monitoring (SRM) is the gold standard targeted mass spectrometry method for protein quantification due to its high precision, reliability, and throughput (10–13). This targeted mass spectrometry method is performed on triple quadrupole instruments, in which a predefined peptide precursor ion is first isolated, and then selected fragment ions arising from its collisional dissociation are measured over time. Each pair of precursor and fragment ion is called a transition, and multiple transitions can be coordinately measured and used to conclusively identify and quantify a peptide in a clinical complex sample.In a previous study, we used a screening mass spectrometric approach to discover potential markers for multiple sclerosis conversion in patients that initially presented a clinical isolated syndrome (14). In that discovery phase, quantitative mass spectrometry with iTRAQ labeling was used to measure protein abundances in pooled CSF samples from patients presenting a clinical isolated syndrome that either remained normal (CIS) or had eventually converted to clinically definite multiple sclerosis (CDMS) (n = 60). In the initial screening, several proteins exhibited significant differences in abundance when comparing these two groups of patients. The abundance change in one of the altered proteins, chitinase 3-like 1 (CH3L1), was confirmed by ELISA in CSF of individual patients, whereas for others, such as semaphorin 7A (SEM7A) and ala-β-his-dipeptidase (CNDP1), their abundance changes were confirmed by targeted mass spectrometry in follow-up studies with independent cohorts (15). Moreover, the levels of CH3L1 were associated with brain MRI abnormalities and disability progression during the follow-up period, as well as with shorter time to conversion to clinically definite multiple sclerosis (14).We now set out to establish a diagnostic protein classifier with high sensitivity and specificity able to differentiate between patients with a clinically isolated syndrome that have either a high or a low risk of developing clinically definite multiple sclerosis over time. For this purpose, CSF samples from an independent patient cohort from the one used in the discovery study were collected, and a set of preselected protein biomarker candidates were systematically quantified by targeted mass spectrometry (SRM) and evaluated for their classification power. Out of this study, we established a protein classifier based on the combination of abundances of proteins chitinase 3-like 1 and ala-β-his-dipeptidase, which is able to differentiate with high sensitivity and specificity between patients with a clinically isolated syndrome that have either a high or low risk of developing clinically definite multiple sclerosis. Moreover, the statistical model built around this protein classifier enables clinicians to easily assign to each patient a precise probability of conversion to clinically definite multiple sclerosis (Fig. 1).Open in a separate windowFig. 1.General workflow used in the present study. Initially, protein candidates identified in our previous discovery studies—together with several proteins described by other groups—were selected and quantified by targeted mass spectrometry (SRM) in a relatively large cohort individual patients. Protein quantities were then evaluated by their capability of classifying patients with clinical isolated syndrome, and thus, the best prognostic protein combination was identified.