The Generalized Pairs Plot

Comparative analysis of jujube and sour jujube gave insight into their difference in genetic diversity and suitable habitat

Jujube (Ziziphus jujuba var. jujuba Mill.) and sour jujube (Z. jujuba var. spinosa (Bunge) Hu ex H.F.Chow.) are economically, nutritionally, and ecologically significant members of the Rhamnaceae family. Despite their importance, insufficient research on their genetics and habitats has impeded effective conservation and utilization. To address this knowledge gap, we conducted plastome sequencing, integrated distribution data from China, and assessed genetic diversity and suitable habitat. The plastomes of both species exhibited high conservation and low genetic diversity. A new-found 23 bp species-specific Indel in the petL-petG enabled us to develop a rapid Indel-based identification marker for species discrimination. Phylogenetic analysis and dating illuminated their genetic relationship, showing speciation occurred 6.9 million years ago, in a period of dramatic global temperature fluctuations. Substantial variations in suitable climatic conditions were observed, with the mean temperature of the coldest quarter as the primary factor influencing distributions (-3.16°C-12.73°C for jujube and -5.79°C to 4.11°C for sour jujube, suitability exceeding 0.6). Consequently, distinct conservation strategies are warranted due to differences in suitable habitats, with jujube having a broader distribution and sour jujube concentrated in Northern China. In conclusion, disparate habitats and climatic factors necessitate tailored conservation approaches. Comparing genetic diversity and developing rapid species-specific primers will further enhance the sustainable utilization of these valuable species.

Dysphagia at 1 Year is Associated With Mean Dose to the Inferior Section of the Brain Stem

PURPOSE

Dysphagia is a common toxicity after head and neck (HN) radiation therapy that negatively affects quality of life. We explored the relationship between radiation therapy dose to normal HN structures and dysphagia 1 year after treatment using image-based datamining (IBDM), a voxel-based analysis technique.

METHODS AND MATERIALS

We used data from 104 patients with oropharyngeal cancer treated with definitive (chemo)radiation therapy. Swallow function was assessed pretreatment and 1 year posttreatment using 3 validated measures: MD Anderson Dysphagia Inventory (MDADI), performance status scale for normalcy of diet (PSS-HN), and water swallowing test (WST). For IBDM, we spatially normalized all patients' planning dose matrices to 3 reference anatomies. Regions where the dose was associated with dysphagia measures at 1 year were found by performing voxel-wise statistics and permutation testing. Clinical factors, treatment variables, and pretreatment measures were used in multivariable analysis to predict each dysphagia measure at 1 year. Clinical baseline models were found using backward stepwise selection. Improvement in model discrimination after adding the mean dose to the identified region was quantified using the Akaike information criterion. We also compared the prediction performance of the identified region with a well-established association: mean doses to the pharyngeal constrictor muscles.

RESULTS

IBDM revealed highly significant associations between dose to distinct regions and the 3 outcomes. These regions overlapped around the inferior section of the brain stem. All clinical models were significantly improved by including mean dose to the overlap region (P ≤ .006). Including pharyngeal dosimetry significantly improved WST (P = .04) but not PSS-HN or MDADI (P ≥ .06).

CONCLUSIONS

In this hypothesis-generating study, we found that mean dose to the inferior section of the brain stem is strongly associated with dysphagia 1 year posttreatment. The identified region includes the swallowing centers in the medulla oblongata, providing a possible mechanistic explanation. Further work including validation in an independent cohort is required.

Multivariate analysis of heavy metals content of beef from Soroti, Uganda

Information about food hygiene and quality in the sub-Saharan African countries remains scarce at a time when many of their citizenry are beginning to acquire the much coveted middle income status. Confounding this are challenges linked to monitoring on a continuous basis the safety of food produced by such lucrative industries as the beef industry. The objective of the current study was to initiate a process of encouraging changes in the status quo, by showing how a first step in that direction might look like. Using heavy metal contents of representative beef samples from butcheries in Soroti, Uganda, typical of a sub-Saharan country, we demonstrate how relationships and common sources of metals in food could be identified in a multivariate space. Beef samples from 40 sites were analyzed by atomic absorption spectrometry for iron (Fe), zinc (Zn), nickel (Ni), chromium (Cr), lead (Pb), copper (Cu), cobalt (Co) and cadmium (Cd). The study showed that all beef samples contained these metals, the extent of which were in the order: Fe > Zn >> Ni, Cr > Pb > Cu, Co > Cd. By correlation analysis, the pairs Ni and Cr, Cd and Co, Ni and Fe or Cr and Fe were found to be most likely coming from similar sources. At least three distinct characteristics of beef consumed in Soroti were also found, a distinction perhaps arising from three major categories of feedlots used to raise donor cattle. The incremental risk of children or adults developing cancer over a lifetime was estimated and found to fall into three categories, two of which are separately explained by the presence of Cr or Ni. The sources of these metals remain a matter of speculation on our part. More studies are needed to determine these sources and to understand the nature of cancer risk in the three categories of beef identified here.

Evolutionary history of genus Coptis and its dynamic changes in the potential suitable distribution area

The genus Coptis belongs to the Ranunculaceae family, containing 15 recognized species highly diverse in morphology. It is a conspicuous taxon with special evolutionary position, distribution pattern and medicinal value, which makes it to be of great research and conservation significance. In order to better understand the evolutionary dynamics of Coptis and promote more practical conservation measures, we performed plastome sequencing and used the sequencing data in combination with worldwide occurrence data of Coptis to estimate genetic diversity and divergence times, rebuild biogeographic history and predict its potential suitable distribution area. The average nucleotide diversity of Coptis was 0.0067 and the hotspot regions with the highest hypermutation levels were located in the ycf1 gene. Coptis is most likely to have originated in North America and Japanese archipelago and has a typical Eastern Asian and North American disjunct distribution pattern, while the species diversity center is located in Mid-West China and Japan. The crown age of the genus is estimated at around 8.49 Mya. The most suitable climatic conditions for Coptis were as follows: precipitation of driest quarter > 25.5 mm, annual precipitation > 844.9 mm and annual mean temperature -3.1 to 19 °C. The global and China suitable area shows an upward trend in the future when emission of greenhouse gases is well controlled, but the area, especially in China, decreases significantly without greenhouse gas policy interventions. The results of this study provide a comprehensive insight into the Coptis evolutionary dynamics and will facilitate future conservation efforts.

Brain-phenotype models fail for individuals who defy sample stereotypes

Individual differences in brain functional organization track a range of traits, symptoms and behaviours1-12. So far, work modelling linear brain-phenotype relationships has assumed that a single such relationship generalizes across all individuals, but models do not work equally well in all participants13,14. A better understanding of in whom models fail and why is crucial to revealing robust, useful and unbiased brain-phenotype relationships. To this end, here we related brain activity to phenotype using predictive models-trained and tested on independent data to ensure generalizability15-and examined model failure. We applied this data-driven approach to a range of neurocognitive measures in a new, clinically and demographically heterogeneous dataset, with the results replicated in two independent, publicly available datasets16,17. Across all three datasets, we find that models reflect not unitary cognitive constructs, but rather neurocognitive scores intertwined with sociodemographic and clinical covariates; that is, models reflect stereotypical profiles, and fail when applied to individuals who defy them. Model failure is reliable, phenotype specific and generalizable across datasets. Together, these results highlight the pitfalls of a one-size-fits-all modelling approach and the effect of biased phenotypic measures18-20 on the interpretation and utility of resulting brain-phenotype models. We present a framework to address these issues so that such models may reveal the neural circuits that underlie specific phenotypes and ultimately identify individualized neural targets for clinical intervention.

Distinct Subtyping of Successful Weaning from Acute Kidney Injury Requiring Renal Replacement Therapy by Consensus Clustering in Critically Ill Patients

Background: Clinical decisions regarding the appropriate timing of weaning off renal replacement therapy (RRT) in critically ill patients are complex and multifactorial. The aim of the current study was to identify which critical patients with acute kidney injury (AKI) may be more likely to be successfully weaned off RRT using consensus cluster analysis. Methods: In this study, critically ill patients who received RRT at three multicenter referral hospitals at several timepoints from August 2016 to July 2018 were enrolled. An unsupervised consensus clustering algorithm was used to identify distinct phenotypes. The outcomes of interest were the ability to wean off RTT and 90-day mortality. Results: A total of 124 patients with AKI requiring RRT (AKI-RRT) were enrolled. The 90-day mortality rate was 30.7% (38/124), and 49.2% (61/124) of the patients were successfully weaned off RRT for over 90 days. The consensus clustering algorithm identified three clusters from a total of 45 features. The three clusters had distinct features and could be separated according to the combination of urinary neutrophil gelatinase-associated lipocalin to creatinine ratio (uNGAL/Cr), Sequential Organ Failure Assessment (SOFA) score, and estimated glomerular filtration rate at the time of weaning off RRT. uNGAL/Cr (hazard ratio [HR] 2.43, 95% confidence interval [CI]: 1.36–4.33) and clustering phenotype (cluster 1 vs. 3, HR 2.7, 95% CI: 1.11–6.57; cluster 2 vs. 3, HR 44.5, 95% CI: 11.92–166.39) could predict 90-day mortality or re-dialysis. Conclusions: Almost half of the critical patients with AKI-RRT could wean off dialysis for over 90 days. Urinary NGAL/Cr and distinct clustering phenotypes could predict 90-day mortality or re-dialysis.

Are rotational passive stiffness and translational passive stiffness correlated? A porcine in vitro study

BACKGROUND

Qualitative clinical assessments of spinal stiffness have been demonstrated to show moderate correlations with one-another. We hypothesized that these correlations would improve in an in vitro model of the functional spinal unit. If the stiffness of spinal units are different across loading regimes (e.g. flexion-extension versus shear), then it may provide one explanation as to the variability in findings from clinical assessments, since these tests tend not to discriminate rotational and translational degrees-of-freedom. Therefore, the purpose of this investigation was to quantify the relationships between rotational and translational stiffness measures in vitro.

METHODS

Forty-eight porcine cervical spine functional units were used in this investigation (20 C3-C4, 28 C5-C6). While under constant 300 N compressive load, range-of-motion tests for both flexion-extension (± 8 Nm, 0.5 deg./s) and anteroposterior shear (± 400 N, 0.2 mm/s) were conducted, to quantify moment-angle and force-deflection curves. Representative stiffness values were then obtained for flexion, extension, anterior shear, and posterior shear using segmented regression. The correlation matrix between these four measures was then used to explore their potential relationships.

FINDINGS

Of the six correlations conducted, only the relationship between posterior shear and extension stiffness was statistically significant (p = 0.014), despite featuring a low correlation coefficient (R² = 0.123).

INTERPRETATION

The poor correlations between stiffness metrics in this study supports the disparate findings of tissue stiffness in vivo. Results from this investigation suggest that clinicians should be cognizant of which degrees-of-freedom they are assessing in the spine, as their stiffness values vary independently.

Seed Quantity or Quality?-Reproductive Responses of Females of Two Dioecious Woody Species to Long-Term Fertilisation

Although seed quality and quantity, as well as reproductive performance are important life history stages of plants, little is known about the reproductive responses of trees to environmental changes such as increased anthropogenic deposition of nitrogen (N) and phosphorus (P). Dioecious plants are good models with which to test the environmental impact on female or male reproductive responses individually. We analysed effects of different long-term nutritional availability on the reproductive performance of two dioecious species (Taxus baccata L. and Juniperus communis L.) characterised by different life histories. By using pot experiments with vegetatively propagated plants grown in different fertilisation conditions, we observed an increase in plant growth and strobili production but a decrease in seed efficiency. Seeds produced by fertilised plants had greater seed mass. Fertiliser addition did not change C or N content nor the C/N ratio of T. baccata seeds, but increased N content and the N/P ratio; however, it did lower the C/N ratio in J. communis. Fertilisation did not change the metabolite profile in T. baccata but 18 metabolites were changed in J. communis. The study revealed new links between species life history, environmental changes, and reproduction. The findings imply that future environmental conditions may alter both seed productivity, and quality, as well as plant reproductive behaviour.

Leaf Functional Traits of Two Species Affected by Nitrogen Addition Rate and Period Not Nitrogen Compound Type in a Meadow Grassland

Plasticity of plant functional traits plays an important role in plant growth and survival under changing climate. However, knowledge about how leaf functional traits respond to the multi-level N addition rates, multiple N compound and duration of N application remains lacking. This study investigated the effects of 2-year and 7-year N addition on the leaf functional traits of Leymus chinensis and Thermopsis lanceolata in a meadow grassland. The results showed that the type of N compounds had no significant effect on leaf functional traits regardless of duration of N application. N addition significantly increased the leaf total N content (LN) and specific leaf area (SLA), and decreased the leaf total P content (LP) and leaf dry matter content (LDMC) of the two species. Compared with short-term N addition, long-term N addition increased LN, LP, SLA, and plant height, but decreased the LDMC. In addition, the traits of the two species were differentially responsive to N addition, LN and LP of T. lanceolata were consistently higher than those of L. chinensis. N addition would make L. chinensis and T. lanceolata tend to "quick investment-return" strategy. Our results provide more robust and comprehensive predictions of the effects of N deposition on leaf traits.

Persistent organic pollutants and contaminants of emerging concern in spinner dolphins (Stenella longirostris) from the Western Atlantic Ocean

The presence and distribution of persistent organic pollutants (POPs) and contaminants of emerging concern (CECs) were evaluated in spinner dolphins (Stenella longirostris) from the Fernando de Noronha Archipelago (Western Atlantic Ocean). Blubber samples (n = 37) were Soxhlet extracted and analyzed using gas chromatography tandem mass spectrometry. The levels of POPs reported in this study are far below those previously reported in spinner dolphins from the Indian and Pacific Oceans. Despite relatively low levels of contaminants, the presence of chemicals represents an additional stressor to these marine mammals, which are subject to increasing anthropogenic pressures, especially regarding tourism activities, in Fernando de Noronha.

Multivariate Analysis of Sediment Toxicity in an Ocean Ecosystem: A Southern California Bight Case Study

Contaminated sediments can negatively affect aquatic organisms and beneficial uses of coastal regions. Monitoring programs typically collect many indicators of sediment toxicity, yet multivariate approaches that comprehensively evaluate data across heterogeneous spatial environments are frequently not performed. In this paper, we explore a multivariate approach to show that a list of suspected drivers of sediment toxicity to native Mytilus galloprovincialis (mussel) and Eohaustorius estuarius (a marine amphipod) population can be narrowed down without excluding samples, and that redundancies in sampling sites can be identified and isolated. Using a 153 × 28 data matrix assembled from a southern California-wide bight monitoring program, we demonstrate by this approach that Port of Los Angeles (PLA) and San Diego Bay (SDB) contained the most toxic sediments in the bight in 2008, the nature of which was unique to each locality. (Note: Little toxicity was observed here in 2013 and 2018.) In PLA sediments, mussels were more affected than amphipods, with higher survivability associated with low Hg and Sn levels. Conversely, amphipods had higher mortality than mussel embryos in SDB sediments, with higher survivability associated with low Be and Co levels. Nitrogen, organic content, and finer sediment particles were not related to the survivability of these organisms.

Combining cross-section images and modeling tools to create high-resolution root system hydraulic atlases in Zea mays

Root hydraulic properties play a central role in the global water cycle, in agricultural systems productivity, and in ecosystem survival as they impact the canopy water supply. However, the existing experimental methods to quantify root hydraulic conductivities, such as the root pressure probing, are particularly challenging, and their applicability to thin roots and small root segments is limited. Therefore, there is a gap in methods enabling easy estimations of root hydraulic conductivities in diverse root types. Here, we present a new pipeline to quickly estimate root hydraulic conductivities across different root types, at high resolution along root axes. Shortly, free-hand root cross-sections were used to extract a selected number of key anatomical traits. We used these traits to parametrize the Generator of Root Anatomy in R (GRANAR) model to simulate root anatomical networks. Finally, we used these generated anatomical networks within the Model of Explicit Cross-section Hydraulic Anatomy (MECHA) to compute an estimation of the root axial and radial hydraulic conductivities (k x and k r , respectively). Using this combination of anatomical data and computational models, we were able to create a root hydraulic conductivity atlas at the root system level, for 14-day-old pot-grown Zea mays (maize) plants of the var. B73. The altas highlights the significant functional variations along and between different root types. For instance, predicted variations of radial conductivity along the root axis were strongly dependent on the maturation stage of hydrophobic barriers. The same was also true for the maturation rates of the metaxylem vessels. Differences in anatomical traits along and across root types generated substantial variations in radial and axial conductivities estimated with our novel approach. Our methodological pipeline combines anatomical data and computational models to turn root cross-section images into a detailed hydraulic atlas. It is an inexpensive, fast, and easily applicable investigation tool for root hydraulics that complements existing complex experimental methods. It opens the way to high-throughput studies on the functional importance of root types in plant hydraulics, especially if combined with novel phenotyping techniques such as laser ablation tomography.

Effects of Moderate Nitrate and Low Sulphate Depositions on the Status of Soil Base Cation Pools and Recent Mineral Soil Acidification at Forest Conversion Sites with European Beech (“Green Eyes”) Embedded in Norway Spruce and Scots Pine Stands

High N depositions of past decades brought changes to European forests including impacts on forest soil nutrition status. However, the ecosystem responses to declining atmospheric N inputs or moderate N depositions attracted only less attention so far. Our study investigated macronutrient (N, S, Ca2+, Mg2+, K+) pools and fluxes at forest conversion sites over 80 years old in Central Germany with European beech (so-called “Green Eyes” (GE)). The GE are embedded in large spruce and pine stands (coniferous stands: CS) and all investigated forest stands were exposed to moderate N deposition rates (6.8 ± 0.9 kg ha−1 yr−1) and acidic soil conditions (pHH2O < 4.7). Since the understanding of forest soil chemical and macronutrient status is essential for the evaluation of forest conversion approaches, we linked patterns in water-bound nutrient fluxes (2001–2018) and in predicted macronutrient storage in the herbaceous and tree layer to patterns in litter fall (2016–2017) and in forest floor and mineral soil macronutrient stocks at GE and CS assessed in 2018. Our results exhibited 43% (Nt) and 21% (S) higher annual throughfall fluxes at CS than at GE. Seepage water at 100 cm mineral soil depth (2001–2018) of CS is characterized by up to fivefold higher NO3− (GE: 2 ± 0.7 µmolc L−1; CS: 9 ± 1.4 µmolc L−1) and sevenfold higher SO42− (GE: 492 ± 220 µmolc L−1; CS: 3672 ± 2613 µmolc L−1) concentrations. High base cation (∑ Ca2+, Mg2+, K+) concentrations in CS mineral soil seepage water (100 cm depth: 2224 ± 1297 µmolc L−1) show significant positive correlations with SO42−. Tree uptake of base cations at GE is associated especially with a Ca2+ depletion from deeper mineral soil. Foliar litter fall turns out to be the main pathway for litter base cation return to the topsoil at GE (>59%) and CS (>66%). The litter fall base cation return at GE (59 ± 6 kg ha−1 yr−1) is almost twice as large as the base cation deposition (30 ± 5 kg ha−1 yr−1) via throughfall and stemflow. At CS, base cation inputs to the topsoil via litter fall and depositions are at the same magnitude (24 ± 4 kg ha−1 yr−1). Macronutrient turnover is higher at GE and decomposition processes are hampered at CS maybe through higher N inputs. Due to its little biomass and only small coverage, the herbaceous layer at GE and CS do not exert a strong influence on macronutrient storage. Changes in soil base cation pools are tree species-, depth- and might be time-dependent, with recently growing forest floor stocks. An ongoing mineral soil acidification seems to be related to decreasing mineral soil base cation stocks (through NO3− and especially SO42− leaching as well as through tree uptake).

Multivariate Analysis of Morpho-Physiological Traits Reveals Differential Drought Tolerance Potential of Bread Wheat Genotypes at the Seedling Stage

Drought is one of the foremost environmental stresses that can severely limit crop growth and productivity by disrupting various physiological processes. In this study, the drought tolerance potential of 127 diverse bread wheat genotypes was evaluated by imposing polyethylene glycol (PEG)-induced drought followed by multivariate analysis of several growth-related attributes. Results showed significant variations in the mean values of different morpho-physiological traits due to PEG-induced drought effects. Correlation analysis revealed that most of the studied traits were significantly correlated among them. The robust hierarchical co-clustering indicated that all the genotypes were clustered into four major groups, with cluster 4 (26 genotypes) being, in general, drought-tolerant followed by cluster 1 (19 genotypes) whereas, cluster 2 (55 genotypes) and 3 (27 genotypes) being drought-sensitive. Linear discriminant analysis (LDA) confirmed that around 90% of the genotypes were correctly assigned to clusters. Squared distance (D2) analysis indicated that the clusters differed significantly from each other. Principal component analysis (PCA) and genotype by trait biplot analysis showed that the first three components accounted for 71.6% of the total variation, with principal component (PC) 1 accounting for 35.4%, PC2 for 24.6% and PC3 for 11.6% of the total variation. Both PCA and LDA revealed that dry weights, tissue water content, cell membrane stability, leaf relative water content, root-shoot weight ratio and seedling vigor index played the most important discriminatory roles in explaining drought tolerance variations among 127 wheat genotypes. Our results conclude that the drought-tolerant and -sensitive wheat genotypes identified in this study would offer valuable genetic tools for further improvement of wheat productivity in arid and semi-arid regions during this time of unpredictable climate change.

Robust variable selection in the framework of classification with label noise and outliers: Applications to spectroscopic data in agri-food

Classification of high-dimensional spectroscopic data is a common task in analytical chemistry. Well-established procedures like support vector machines (SVMs) and partial least squares discriminant analysis (PLS-DA) are the most common methods for tackling this supervised learning problem. Nonetheless, interpretation of these models remains sometimes difficult, and solutions based on feature selection are often adopted as they lead to the automatic identification of the most informative wavelengths. Unfortunately, for some delicate applications like food authenticity, mislabeled and adulterated spectra occur both in the calibration and/or validation sets, with dramatic effects on the model development, its prediction accuracy and robustness. Motivated by these issues, the present paper proposes a robust model-based method that simultaneously performs variable selection, outliers and label noise detection. We demonstrate the effectiveness of our proposal in dealing with three agri-food spectroscopic studies, where several forms of perturbations are considered. Our approach succeeds in diminishing problem complexity, identifying anomalous spectra and attaining competitive predictive accuracy considering a very low number of selected wavelengths.

Histological and Quantitative Appraisal of the Intradermal and Subcutaneous Distribution of the Hyaluronic Acid Injected into the Nasolabial Fold

BACKGROUND

Histological analysis of hyaluronic acid (HA) applied in the nasolabial fold (NLF) studied gel distribution into the dermis and subcutaneous fat, correlating density of NLF tissues, with cohesivity, concentration and degradation of HA.

METHOD

Ten patients received two injection points on each NLF. They were intradermal near the nasal ala and subcutaneous near the oral commissure. Injection points received 0.1 ml of 24 mg/ml HA cross-linked by BDDE 2.0 ppm through a bolus technique injection without retrograde backflow. Biopsies were taken 72 h and 9 months after application to histological analysis.

RESULTS

Dermis density fragmented the gel into small nodules, spreading it into the reticular dermis. Seventy-two hours after application, average diameter of the small nodules was 0.30 mm and at month nine 0.05 mm. Softness of the subcutaneous fat and high concentration of HA created a single and compact nodule. Seventy-two hours after application, average of nodule diameters was 1.05 mm and at month nine 0.49 mm. HA biodegradation occurred on the external surface of the gel. The single nodule offered small contact surface to enzymes, slowing gel degradation. The sum average of the diameters of the small nodules offered a large contact surface to enzymes, accelerating gel degradation.

CONCLUSION

Permanence of the HA into the tissues depended on the relationship between the gel distribution and its degradation. Due to the small contact surface of the single nodule to enzymes, permanence of the HA into the subcutaneous fat was more extended than into the dermis.

LEVEL OF EVIDENCE IV

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Predator community and resource use jointly modulate the inducible defense response in body height of crucian carp

Phenotypic plasticity can be expressed as changes in body shape in response to environmental variability. Crucian carp (Carassius carassius), a widespread cyprinid, displays remarkable plasticity in body morphology and increases body depth when exposed to cues from predators, suggesting the triggering of an antipredator defense mechanism. However, these morphological changes could also be related to resource use and foraging behavior, as an indirect effect of predator presence. In order to determine whether phenotypic plasticity in crucian carp is driven by a direct or indirect response to predation threat, we compared twelve fish communities inhabiting small lakes in southeast Norway grouped by four categories of predation regimes: no predator fish, or brown trout (Salmo trutta), perch (Perca fluviatilis), or pike (Esox lucius) as main piscivores. We predicted the body shape of crucian carp to be associated with the species composition of predator communities and that the presence of efficient piscivores would result in a deeper body shape. We use stable isotope analyses to test whether this variation in body shape was related to a shift in individual resource use-that is, littoral rather than pelagic resource use would favor the development of a specific body shape-or other environmental characteristics. The results showed that increasingly efficient predator communities induced progressively deeper body shape, larger body size, and lower population densities. Predator maximum gape size and individual trophic position were the best variables explaining crucian carp variation in body depth among predation categories, while littoral resource use did not have a clear effect. The gradient in predation pressure also corresponded to a shift in lake productivity. These results indicate that crucian carp have a fine-tuned morphological defense mechanism against predation risk, triggered by the combined effect of predator presence and resource availability.

Histological and Clinical Appraisal of Distribution and Long Acting New Hyaluronic Acid into the Subcutaneous Fat of the Forehead to Improve Horizontal Lines

BACKGROUND

A new hyaluronic acid (HA) was appraised to improve forehead horizontal lines (FHL). Histological analysis correlated the gel distribution with clinical findings and also with wrinkle depth, 48 h and 12 months after HA application.

METHODS

The new filler composed by 24 mg/ml of HA cross-linked with BDDE 2.0 ppm was injected into the subcutaneous fat, just beneath the dermis, through a retrograde backflow injection technique applied in sequence. Biopsies were taken with a 3.0-mm-diameter skin punch before HA application, 48 h and 12 months after HA application for histological evaluation.

RESULTS

Subcutaneous application created a compact cylindrical filament as pattern of gel distribution, which acted as strut raising the FHL to the level of the surrounding tissues. Diameter average of the filament 48 h after HA application was 1.18 mm and at month twelve 0.34 mm. The residual amount of the gel at month twelve ensured the long acting of the HA into the subcutaneous fat. FHL depth of 251.83 µm before HA application and 190.20 µm after 12 months indicated that the residual amount of gel at month twelve still projected FHL.

CONCLUSION

High cohesivity of HA and low density of forehead subcutaneous fat caused the gel to take the form of a compact cylindrical filament. The small amount of gel still presenting into the subcutaneous fat 12 months after application validated the long acting of the HA. Evidence-based analysis showed that this new filler might be considered a safe alternative for improvement in the FHL.

LEVEL OF EVIDENCE IV

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Prebiotic Organic Chemistry of Formamide and the Origin of Life in Planetary Conditions: What We Know and What Is the Future

The goal of prebiotic chemistry is the depiction of molecular evolution events preceding the emergence of life on Earth or elsewhere in the cosmos. Plausible experimental models require geochemical scenarios and robust chemistry. Today we know that the chemical and physical conditions for life to flourish on Earth were at work much earlier than thought, i.e., earlier than 4.4 billion years ago. In recent years, a geochemical model for the first five hundred million years of the history of our planet has been devised that would work as a cradle for life. Serpentinization processes in the Hadean eon affording self-assembled structures and vesicles provides the link between the catalytic properties of the inorganic environment and the impressive chemical potential of formamide to produce complete panels of organic molecules relevant in pre-genetic and pre-metabolic processes. Based on an interdisciplinary approach, we propose basic transformations connecting geochemistry to the chemistry of formamide, and we hint at the possible extension of this perspective to other worlds.

Xylem Phenology and Growth Response of European Beech, Silver Fir and Scots Pine along an Elevational Gradient during the Extreme Drought Year 2018

Highlights: European beech (Fagus sylvatica L.) and silver fir (Abies alba Mill.) displayed parabolic elevational trends of the cessation of xylem cell differentiation phases. Xylem phenology and growth rates of Scots pine (Pinus sylvestris L.) appeared to be less influenced by the 2018 drought, whereas beech reduced growth on the lowest elevation and fir seemed negatively affected in general. Background: The year 2018 was characterized by multiple drought periods and heat waves during the growing season. Our aim was to understand species-specific responses of xylem phenology and growth to drought and how this effect was modified along an elevational gradient. Materials and Methods: We sampled microcores and increment cores along an elevational gradient in the southwestern Black Forest (SW Germany) region and analyzed xylem phenology and growth response to drought. Results: Termination of cell enlargement and lignification occurred earliest in beech and latest in pine. Beech had the highest growth rates but shortest growth durations, fir achieved moderate rates and medium durations and pine had lowest growth rates despite long growth durations. In contrast to pine, onsets of cell differentiation phases of fir and beech did not show clear linear relationships with elevation. Cessation of cell production and lignification of beech and fir followed a parabolic elevational trend and occurred earliest on low elevations, whereas pine showed no changes with elevation. Tree-ring width, generally, depended 3–4 times more on the growth rate than on growth duration. Conclusions: The possibly drought-induced early cessation of cell differentiation and considerable growth reduction of beech appeared to be most severe on the lowest elevation. In comparison, growth reductions of fir were larger and seemed independent from elevation. We found evidence, that productivity might be severely affected at lower elevations, whereas at high elevations wood production might not equally benefit during global warming.

“Small things matter most”: The spillover effects in the cryptocurrency market and gold as a silver bullet

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Cryptos with small market capitalization are more likely to be sources of shocks than their larger counterparts.

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Bitcoins can be considered as a better hedge due to its relative independence.

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USDT strong anchoring with US$ makes it very volatile.

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The idiosyncrasy of Gold enables it to weather adverse crypto market’s movements.

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Having gold in the portfolio with cryptocurrency helps fruitful diversification.

The cryptocurrencies with small market capitalization are often overlooked despite they can potentially be the source of shocks to other cryptocurrencies in the market. To address this caveat, this paper attempts to investigate the spillover effects among 14 cryptocurrencies by employing transfer entropy. Our results suggest that among different types of cryptos, Bitcoin is still the most appropriate instrument for hedging, while Tether (USDT) which have a strong anchor with the US dollar is significantly volatile. Interestingly, we document that the small coins are more likely to be shock creators in the cryptocurrency market. Using the same approach, we further explored the link between gold prices and cryptocurrency prices. The results show that gold could be a good hedging instrument for cryptocurrencies due to its independence. In light of empirical results, it is advisable to carefully consider the coins with small capitalization. Further, investors should conduct portfolio rebalancing by including gold to hedge against the unexpected movement in the cryptocurrency market. Our paper not only contributes in terms of the application of advanced empirical methodology but also provides evidence on idiosyncratic features of the cryptocurrency market.

Soil pH is the primary factor driving the distribution and function of microorganisms in farmland soils in northeastern China

Purpose

To understand which environmental factors influence the distribution and ecological functions of bacteria in agricultural soil.

Method

A broad range of farmland soils was sampled from 206 locations in Jilin province, China. We used 16S rRNA gene-based Illumina HiSeq sequencing to estimated soil bacterial community structure and functions.

Result

The dominant taxa in terms of abundance were found to be, Actinobacteria, Acidobacteria, Gemmatimonadetes, Chloroflexi, and Proteobacteria. Bacterial communities were dominantly affected by soil pH, whereas soil organic carbon did not have a significant influence on bacterial communities. Soil pH was significantly positively correlated with bacterial operational taxonomic unit abundance and soil bacterial α-diversity (P<0.05) spatially rather than with soil nutrients. Bacterial functions were estimated using FAPROTAX, and the relative abundance of anaerobic and aerobic chemoheterotrophs, and nitrifying bacteria was 27.66%, 26.14%, and 6.87%, respectively, of the total bacterial community. Generally, the results indicate that soil pH is more important than nutrients in shaping bacterial communities in agricultural soils, including their ecological functions and biogeographic distribution.

High- and Extra-High-Profile Round Implants in Breast Augmentation: Guidelines to Prevent Rippling and Implant Edge Visibility

BACKGROUND

Rippling and implant edge visibility after breast augmentation depends on several factors. Among the most relevant are breast soft tissue thickness, particularly the retroareolar mammary parenchyma, and implant profile. They were correlates to prevent these occurrences.

METHODS

Thirty patients underwent breast augmentation through subfascial dissection involving the pectoralis, serratus, external oblique, and rectus abdominis fascias. The thickness of the retroareolar mammary parenchyma distributed patients into two groups. Group I: patients with thickness equal to or greater than 4.0 cm received high-profile 85% fill round implants. Group II: patients with thickness up to 3.9 cm received extra-high-profile 100% fill round implants. MRI was performed preoperatively and 5 years after augmentation to evaluate breast tissue changes and implant contouring.

RESULTS

Seventeen patients with high-profile implants and thirteen patients with extra-high-profile implants had noticeable improvement of the breasts without the occurrence of rippling or implant edge visibility. A natural appearance of the breast, increased mammary cone, balanced upper and lower pole contouring was maintained at 5 years postoperatively. MRI performed 5 years after breast augmentation validated patient clinical outcomes not evidencing implant deformities, or soft tissue thinning, parenchymal atrophy or chest wall deformities.

CONCLUSIONS

The adequate correlation between retroareolar mammary parenchyma thickness with high-profile 85% fill and extra-high-profile 100% fill textured round implants was of utmost importance in preventing rippling and implant edge visibility. The wide fascial support, width of the implant smaller than the breast diameter, and soft cohesive gel-filled implants were co-adjuvant factors in preventing rippling and implant edge visibility.

LEVEL OF EVIDENCE IV

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Conceptual and Methodological Issues in Evaluating Multidimensional Visualizations for Decision Support

We explore how to rigorously evaluate multidimensional visualizations for their ability to support decision making. We first define multi-attribute choice tasks, a type of decision task commonly performed with such visualizations. We then identify which of the existing multidimensional visualizations are compatible with such tasks, and set out to evaluate three elementary visualizations: parallel coordinates, scatterplot matrices and tabular visualizations. Our method consists in first giving participants low-level analytic tasks, in order to ensure that they properly understood the visualizations and their interactions. Participants are then given multi-attribute choice tasks consisting of choosing holiday packages. We assess decision support through multiple objective and subjective metrics, including a decision accuracy metric based on the consistency between the choice made and self-reported preferences for attributes. We found the three visualizations to be comparable on most metrics, with a slight advantage for tabular visualizations. In particular, tabular visualizations allow participants to reach decisions faster. Thus, although decision time is typically not central in assessing decision support, it can be used as a tie-breaker when visualizations achieve similar decision accuracy. Our results also suggest that indirect methods for assessing choice confidence may allow to better distinguish between visualizations than direct ones. We finally discuss the limitations of our methods and directions for future work, such as the need for more sensitive metrics of decision support.

Selection of internal references for qRT-PCR assays of human hepatocellular carcinoma cell lines

Selecting internal references is important for normalizing the loading quantity of samples in quantitative reverse-transcription PCR (qRT-PCR). In the present study, a systematic evaluation of reference genes among nine hepatocellular carcinoma (HCC) cell lines was conducted. After screening the microarray assay data of ten HCC cell lines, 19 candidate reference genes were preselected and then evaluated by qRT-PCR, together with ACTB, GAPDH, HPRT1 and TUBB The expression evenness of these candidate genes was evaluated using RefFinder. The stabilities of the reference genes were further evaluated under different experimental perturbations in Huh-7 and MHCC-97L, and the applicability of the reference genes was assessed by measuring the mRNA expression of CCND1, CCND3, CDK4 and CDK6 under sorafenib treatment in Huh-7. Results showed that TFG and SFRS4 are among the most reliable reference genes, and ACTB ranks third and acts quite well as a classical choice, whereas GAPDH, HPRT1 and TUBB are not proper reference genes in qRT-PCR assays among the HCC cell lines. SFRS4, YWHAB, SFRS4 and CNPY3 are the most stable reference genes of the MHCC-97L under the perturbations of chemotherapy, oxidative stress, starvation and hypoxia respectively, whereas YWHAB is the most stable one of Huh-7 under all perturbations. GAPDH is recommended as a reference gene under chemotherapy perturbations. YWHAB and UBE2B, TMED2 and TSFM, and GAPDH and TSFM are the two best reference genes under oxidative stress, starvation and hypoxia perturbations respectively. TSFM is stable in both cell lines across all the perturbations.

Investigating Epistemic Stances in Game Play with Data Mining

In this paper, techniques of statistical computing were applied to data logs to investigate the patterns in students' play of The Fuzzy Chronicles, and how these patterns relate to learning outcomes with regards to Newtonian kinematics. This paper has two goals. The first goal is to investigate the basic claims of the proposed Two-System Framework for Game-Based Learning (or 2SM) (Martinez-Garza & Clark, 2016) that may serve as part of a general-use explanatory framework for educational gaming. The second goal is to explore and demonstrate the use of automatically collected log files of student play as evidence through educational data mining techniques. These techniques could also find general use, and this paper offers a demonstration of plausible methods and processes that are suited for game play data. These goals were pursued via two research questions. The first research question examines whether students playing The Fuzzy Chronicles showed evidence of dichotomous fast/slow modes of solution. The 2SM theorizes that slow modes of solution will correlate to higher learning gains. Congruent with the 2SM, students who use mainly fast iterative solution strategies achieved lower learning gains than students who preferred slow, elaborate solutions, or a more balanced mix of the two. A second research question investigates the connection between conceptual understanding and student performance in conceptually-laden challenges. The finding was that students generally improve their performance in these challenges as gameplay progresses, but that this improvement is strongly moderated by their prior knowledge of physics. Implications of these findings in terms of educational game design, analysis of gameplay logs, and further refinement of the 2SM are discussed.

3D Regression Heat Map Analysis of Population Study Data

Epidemiological studies comprise heterogeneous data about a subject group to define disease-specific risk factors. These data contain information (features) about a subject's lifestyle, medical status as well as medical image data. Statistical regression analysis is used to evaluate these features and to identify feature combinations indicating a disease (the target feature). We propose an analysis approach of epidemiological data sets by incorporating all features in an exhaustive regression-based analysis. This approach combines all independent features w.r.t. a target feature. It provides a visualization that reveals insights into the data by highlighting relationships. The 3D Regression Heat Map, a novel 3D visual encoding, acts as an overview of the whole data set. It shows all combinations of two to three independent features with a specific target disease. Slicing through the 3D Regression Heat Map allows for the detailed analysis of the underlying relationships. Expert knowledge about disease-specific hypotheses can be included into the analysis by adjusting the regression model formulas. Furthermore, the influences of features can be assessed using a difference view comparing different calculation results. We applied our 3D Regression Heat Map method to a hepatic steatosis data set to reproduce results from a data mining-driven analysis. A qualitative analysis was conducted on a breast density data set. We were able to derive new hypotheses about relations between breast density and breast lesions with breast cancer. With the 3D Regression Heat Map, we present a visual overview of epidemiological data that allows for the first time an interactive regression-based analysis of large feature sets with respect to a disease.

Statistical methods for handling unwanted variation in metabolomics data

Metabolomics experiments are inevitably subject to a component of unwanted variation, due to factors such as batch effects, long runs of samples, and confounding biological variation. Although the removal of this unwanted variation is a vital step in the analysis of metabolomics data, it is considered a gray area in which there is a recognized need to develop a better understanding of the procedures and statistical methods required to achieve statistically relevant optimal biological outcomes. In this paper, we discuss the causes of unwanted variation in metabolomics experiments, review commonly used metabolomics approaches for handling this unwanted variation, and present a statistical approach for the removal of unwanted variation to obtain normalized metabolomics data. The advantages and performance of the approach relative to several widely used metabolomics normalization approaches are illustrated through two metabolomics studies, and recommendations are provided for choosing and assessing the most suitable normalization method for a given metabolomics experiment. Software for the approach is made freely available.

Interactive Visual Analysis of Image-Centric Cohort Study Data

Epidemiological population studies impose information about a set of subjects (a cohort) to characterize disease-specific risk factors. Cohort studies comprise heterogenous variables describing the medical condition as well as demographic and lifestyle factors and, more recently, medical image data. We propose an Interactive Visual Analysis (IVA) approach that enables epidemiologists to rapidly investigate the entire data pool for hypothesis validation and generation. We incorporate image data, which involves shape-based object detection and the derivation of attributes describing the object shape. The concurrent investigation of image-based and non-image data is realized in a web-based multiple coordinated view system, comprising standard views from information visualization and epidemiological data representations such as pivot tables. The views are equipped with brushing facilities and augmented by 3D shape renderings of the segmented objects, e.g., each bar in a histogram is overlaid with a mean shape of the associated subgroup of the cohort. We integrate an overview visualization, clustering of variables and object shape for data-driven subgroup definition and statistical key figures for measuring the association between variables. We demonstrate the IVA approach by validating and generating hypotheses related to lower back pain as part of a qualitative evaluation.

Reading the leaves: A comparison of leaf rank and automated areole measurement for quantifying aspects of leaf venation

The reticulate venation that is characteristic of a dicot leaf has excited interest from systematists for more than a century, and from physiological and developmental botanists for decades. The tools of digital image acquisition and computer image analysis, however, are only now approaching the sophistication needed to quantify aspects of the venation network found in real leaves quickly, easily, accurately, and reliably enough to produce biologically meaningful data. In this paper, we examine 120 leaves distributed across vascular plants (representing 118 genera and 80 families) using two approaches: a semiquantitative scoring system called "leaf ranking," devised by the late Leo Hickey, and an automated image-analysis protocol. In the process of comparing these approaches, we review some methodological issues that arise in trying to quantify a vein network, and discuss the strengths and weaknesses of automatic data collection and human pattern recognition. We conclude that subjective leaf rank provides a relatively consistent, semiquantitative measure of areole size among other variables; that modal areole size is generally consistent across large sections of a leaf lamina; and that both approaches-semiquantitative, subjective scoring; and fully quantitative, automated measurement-have appropriate places in the study of leaf venation.

Data Visualization in Sociology

Visualizing data is central to social scientific work. Despite a promising early beginning, sociology has lagged in the use of visual tools. We review the history and current state of visualization in sociology. Using examples throughout, we discuss recent developments in ways of seeing raw data and presenting the results of statistical modeling. We make a general distinction between those methods and tools designed to help explore datasets, and those designed to help present results to others. We argue that recent advances should be seen as part of a broader shift towards easier sharing of the code and data both between researchers and with wider publics, and encourage practitioners and publishers to work toward a higher and more consistent standard for the graphical display of sociological insights.

GPLOM: the generalized plot matrix for visualizing multidimensional multivariate data

Scatterplot matrices (SPLOMs), parallel coordinates, and glyphs can all be used to visualize the multiple continuous variables (i.e., dependent variables or measures) in multidimensional multivariate data. However, these techniques are not well suited to visualizing many categorical variables (i.e., independent variables or dimensions). To visualize multiple categorical variables, 'hierarchical axes' that 'stack dimensions' have been used in systems like Polaris and Tableau. However, this approach does not scale well beyond a small number of categorical variables. Emerson et al. [8] extend the matrix paradigm of the SPLOM to simultaneously visualize several categorical and continuous variables, displaying many kinds of charts in the matrix depending on the kinds of variables involved. We propose a variant of their technique, called the Generalized Plot Matrix (GPLOM). The GPLOM restricts Emerson et al.'s technique to only three kinds of charts (scatterplots for pairs of continuous variables, heatmaps for pairs of categorical variables, and barcharts for pairings of categorical and continuous variable), in an effort to make it easier to understand. At the same time, the GPLOM extends Emerson et al.'s work by demonstrating interactive techniques suited to the matrix of charts. We discuss the visual design and interactive features of our GPLOM prototype, including a textual search feature allowing users to quickly locate values or variables by name. We also present a user study that compared performance with Tableau and our GPLOM prototype, that found that GPLOM is significantly faster in certain cases, and not significantly slower in other cases.