基于遗传算法和支持向量机的乳杆菌发酵过程建模

由于生化反应过程的复杂性和高度非线性,多数简单的数学模型不能准确描述。该文基于Matlab软件,利用改进的支持向量机(υ-SVR)对植物乳酸杆菌发酵这一典型生化过程进行研究,应用遗传算法估计模型最优参数,建立植物乳杆菌的菌体密度预测模型。同时建立传统的logistic动力学模型以进行比较。结果表明,采用结合遗传算法的υ-SVR预测模型拟合误差小,皮尔森相关系数(R)更高,可以较好地预测乳酸杆菌的发酵过程,为其优化控制及放大提供依据。     

Towards a gene expression biomarker set for human biological age

We have previously described a statistical model capable of distinguishing young (age <65 years) from old (age ≥75 years) individuals. Here we studied the performance of a modified model in three populations and determined whether individuals predicted to be biologically younger than their chronological age had biochemical and functional measures consistent with a younger biological age. Those with ‘younger’ gene expression patterns demonstrated higher muscle strength and serum albumin, and lower interleukin‐6 and blood urea concentrations relative to ‘biologically older’ individuals (odds ratios 2.09, 1.64, 0.74, 0.74; P = 2.4 × 10^?2, 3.5 × 10^?4, 1.8 × 10^?2, 1.5 × 10^?2, respectively). We conclude that our expression signature of age is robust across three populations and may have utility for estimation of biological age.     

Climate‐induced changes in the distribution of freshwater fish: observed and predicted trends

1. Climate change could be one of the main threats faced by aquatic ecosystems and freshwater biodiversity. Improved understanding, monitoring and forecasting of its effects are thus crucial for researchers, policy makers and biodiversity managers. 2. Here, we provide a review and some meta‐analyses of the literature reporting both observed and predicted climate‐induced effects on the distribution of freshwater fish. After reviewing three decades of research, we summarise how methods in assessing the effects of climate change have evolved, and whether current knowledge is geographically or taxonomically biased. We conducted multispecies qualitative and quantitative analyses to find out whether the observed responses of freshwater fish to recent changes in climate are consistent with those predicted under future climate scenarios. 3. We highlight the fact that, in recent years, freshwater fish distributions have already been affected by contemporary climate change in ways consistent with anticipated responses under future climate change scenarios: the range of most cold‐water species could be reduced or shift to higher altitude or latitude, whereas that of cool‐ and warm‐water species could expand or contract. 4. Most evidence about the effects of climate change is underpinned by the large number of studies devoted to cold‐water fish species (mainly salmonids). Our knowledge is still incomplete, however, particularly due to taxonomic and geographic biases. 5. Observed and expected responses are well correlated among families, suggesting that model predictions are supported by empirical evidence. The observed effects are of greater magnitude and show higher variability than the predicted effects, however, indicating that other drivers of changes may be interacting with climate and seriously affecting freshwater fish. 6. Finally, we suggest avenues of research required to address current gaps in what we know about the climate‐induced effects on freshwater fish distribution, including (i) the need for more long‐term data analyses, (ii) the assessment of climate‐induced effects at higher levels of organisation (e.g. assemblages), (iii) methodological improvements (e.g. accounting for uncertainty among projections and species’ dispersal abilities, combining both distributional and empirical approaches and including multiple non‐climatic stressors) and (iv) systematic confrontation of observed versus predicted effects across multi‐species assemblages and at several levels of biological organisation (i.e. populations and assemblages).     

Sterol metabolism and protein metabolism are differentially correlated with sarcopenia in Asian Chinese men and women

ObjectivesOur aim was to investigate the prevalence and predictive variables of sarcopenia.MethodsWe recruited participants from the Peking Union Medical College Hospital Multicenter Prospective Longitudinal Sarcopenia Study (PPLSS). Muscle mass was quantified using bioimpedance, and muscle function was quantified using grip strength and gait speed. Logistic regression revealed the relationships between sarcopenia and nutritional, lifestyle, disease, psychosocial and physical variables.ResultsThe prevalence of sarcopenia and sarcopenic obesity was 9.2%‐16.2% and 0.26%‐9.1%, respectively. Old age, single status, undernourishment, higher income, smoking, low physical activity, poor appetite and low protein diets were significantly associated with sarcopenia. Multiple logistic regression analysis showed that age was a risk factor for all stages of sarcopenia, and participants above 80 years were greater than fivefold more susceptible to sarcopenia, while lower physical activity was an independent risk factor. The optimal cut‐off value for age was 71 years, which departs from the commonly accepted cut‐off of 60 years. Female participants were greater than twofold less susceptible to sarcopenia than male participants. The sterol derivative 25‐hydroxyvitamin D was associated with fourfold lower odds of sarcopenia in male participants. Several protein intake variables were also correlated with sarcopenia. Based on these parameters, we defined a highly predictive index for sarcopenia.ConclusionsOur findings support a predictive index of sarcopenia, which agglomerates the complex influences that sterol metabolism and nutrition exert on male vs female participants.     

Improved Prediction of Body Fat by Measuring Skinfold Thickness,Circumferences, and Bone Breadths

Objective: To develop improved predictive regression equations for body fat content derived from common anthropometric measurements. Research Methods and Procedures: 117 healthy German subjects, 46 men and 71 women, 26 to 67 years of age, from two different studies were assigned to a validation and a cross‐validation group. Common anthropometric measurements and body composition by DXA were obtained. Equations using anthropometric measurements predicting body fat mass (BFM) with DXA as a reference method were developed using regression models. Results: The final best predictive sex‐specific equations combining skinfold thicknesses (SF), circumferences, and bone breadth measurements were as follows: BFM_New (kg) for men = ?40.750 + [(0.397 × waist circumference) + [6.568 × (log triceps SF + log subscapular SF + log abdominal SF)]] and BFM_New (kg) for women = ?75.231 + [(0.512 × hip circumference) + [8.889 × (log chin SF + log triceps SF + log subscapular SF)] + (1.905 × knee breadth)]. The estimates of BFM from both validation and cross‐validation had an excellent correlation, showed excellent correspondence to the DXA estimates, and showed a negligible tendency to underestimate percent body fat in subjects with higher BFM compared with equations using a two‐compartment (Durnin and Womersley) or a four‐compartment (Peterson) model as the reference method. Discussion: Combining skinfold thicknesses with circumference and/or bone breadth measures provide a more precise prediction of percent body fat in comparison with established SF equations. Our equations are recommended for use in clinical or epidemiological settings in populations with similar ethnic background.     

Of mast and mean: differential‐temperature cue makes mast seeding insensitive to climate change

Mast‐seeding plants often produce high seed crops the year after a warm spring or summer, but the warm‐temperature model has inconsistent predictive ability. Here, we show for 26 long‐term data sets from five plant families that the temperature difference between the two previous summers (ΔT) better predicts seed crops. This discovery explains how masting species tailor their flowering patterns to sites across altitudinal temperature gradients; predicts that masting will be unaffected by increasing mean temperatures under climate change; improves prediction of impacts on seed consumers; demonstrates that strongly masting species are hypersensitive to climate; explains the rarity of consecutive high‐seed years without invoking resource constraints; and generates hypotheses about physiological mechanisms in plants and insect seed predators. For plants, ΔT has many attributes of an ideal cue. This temperature‐difference model clarifies our understanding of mast seeding under environmental change, and could also be applied to other cues, such as rainfall.     

The body beyond the body: expectation of a sensory event is enough to induce ownership over a fake hand

More than 100 papers have been published on the rubber hand illusion since its discovery 14 years ago. The illusion has been proposed as a demonstration that the body is distinguished from other objects by its participation in specific forms of intermodal perceptual correlation. Here, we radically challenge this view by claiming that perceptual correlation is not necessary to produce the experience of this body as mine. Each of 15 participants was seated with his/her right arm resting upon a table just below another smaller table. Thus, the real hand was hidden from the participant''s view and a life-sized rubber model of a right hand was placed on the small table in front of the participant. The participant observed the experimenter''s hand while approaching—without touching—the rubber hand. Phenomenology of the illusion was measured by means of skin conductance response and questionnaire. Both measures indicated that participants experienced the illusion that the experimenter''s hand was about to touch their hidden hand rather than the rubber hand, as if the latter replaced their own hand. This did not occur when the rubber hand was rotated by 180° or replaced by a piece of wood. This illusion indicates that our brain does not build a sense of self in a merely reactive way, via perceptual correlations; rather it generates predictions on what may or may not belong to itself.     

inSPIRE: An Open-Source Tool for Increased Mass Spectrometry Identification Rates Using Prosit Spectral Prediction

Rescoring of mass spectrometry (MS) search results using spectral predictors can strongly increase peptide spectrum match (PSM) identification rates. This approach is particularly effective when aiming to search MS data against large databases, for example, when dealing with nonspecific cleavage in immunopeptidomics or inflation of the reference database for noncanonical peptide identification. Here, we present inSPIRE (in silico Spectral Predictor Informed REscoring), a flexible and performant open-source rescoring pipeline built on Prosit MS spectral prediction, which is compatible with common database search engines. inSPIRE allows large-scale rescoring with data from multiple MS search files, increases sensitivity to minor differences in amino acid residue position, and can be applied to various MS sample types, including tryptic proteome digestions and immunopeptidomes. inSPIRE boosts PSM identification rates in immunopeptidomics, leading to better performance than the original Prosit rescoring pipeline, as confirmed by benchmarking of inSPIRE performance on ground truth datasets. The integration of various features in the inSPIRE backbone further boosts the PSM identification in immunopeptidomics, with a potential benefit for the identification of noncanonical peptides.