Common bean under different water availability reveals classifiable stimuli-specific signatures in plant electrome.

Plant electrophysiology has unveiled the involvement of electrical signals in the physiology and behavior of plants. Spontaneously generated bioelectric activity can be altered in response to changes in environmental conditions, suggesting that a plant's electrome may possess a distinct signature associated with various stimuli. Analyzing electrical signals, particularly the electrome, in conjunction with Machine Learning (ML) techniques has emerged as a promising approach to classify characteristic electrical signals corresponding to each stimulus. This study aimed to characterize the electrome of common bean (Phaseolus vulgaris L.) cv. BRS-Expedito, subjected to different water availabilities, seeking patterns linked to these stimuli. For this purpose, bean plants in the vegetative stage were subjected to the following treatments: (I) distilled water; (II) half-strength Hoagland's nutrient solution; (III) -2 MPa PEG solution; and (IV) -2 MPa NaCl solution. Electrical signals were recorded within a Faraday's cage using the MP36 electronic system for data acquisition. Concurrently, plant water status was assessed by monitoring leaf turgor variation. Leaf temperature was additionally measured. Various analyses were conducted on the electrical time series data, including arithmetic average of voltage variation, skewness, kurtosis, Probability Density Function (PDF), autocorrelation, Power Spectral Density (PSD), Approximate Entropy (ApEn), Fast Fourier Transform (FFT), and Multiscale Approximate Entropy (ApEn(s)). Statistical analyses were performed on leaf temperature, voltage variation, skewness, kurtosis, PDF µ exponent, autocorrelation, PSD ß exponent, and approximate entropy data. Machine Learning analyses were applied to identify classifiable patterns in the electrical time series. Characterization of the electrome of BRS-Expedito beans revealed stimulus-dependent profiles, even when alterations in water availability stimuli were similar in terms of quality and intensity. Additionally, it was observed that the bean electrome exhibits high levels of complexity, which are altered by different stimuli, with more intense and aversive stimuli leading to drastic reductions in complexity levels. Notably, one of the significant findings was the 100% accuracy of Small Vector Machine in detecting salt stress using electrome data. Furthermore, the study highlighted alterations in the plant electrome under low water potential before observable leaf turgor changes. This work demonstrates the potential use of the electrome as a physiological indicator of the water status in bean plants.

Gibberellin and miRNA156-targeted SlSBP genes synergistically regulate tomato floral meristem determinacy and ovary patterning.

Many developmental processes associated with fruit development occur at the floral meristem (FM). Age-regulated microRNA156 (miR156) and gibberellins (GAs) interact to control flowering time, but their interplay in subsequent stages of reproductive development is poorly understood. Here, in tomato (Solanum lycopersicum), we show that GA and miR156-targeted SQUAMOSA PROMOTER-BINDING PROTEIN-LIKE (SPL or SBP) genes interact in the tomato FM and ovary patterning. High GA responses or overexpression of miR156 (156OE), which leads to low expression levels of miR156-silenced SBP genes, resulted in enlarged FMs, ovary indeterminacy and fruits with increased locule number. Conversely, low GA responses reduced indeterminacy and locule number, and overexpression of a S. lycopersicum (Sl)SBP15 allele that is miR156 resistant (rSBP15) reduced FM size and locule number. GA responses were partially required for the defects observed in 156OE and rSBP15 fruits. Transcriptome analysis and genetic interactions revealed shared and divergent functions of miR156-targeted SlSBP genes, PROCERA/DELLA and the classical WUSCHEL/CLAVATA pathway, which has been previously associated with meristem size and determinacy. Our findings reveal that the miR156/SlSBP/GA regulatory module is deployed differently depending on developmental stage and create novel opportunities to fine-tune aspects of fruit development that have been important for tomato domestication.

Transcriptome changes in the developing sugarcane culm associated with high yield and early-season high sugar content.

Sugarcane, with its exceptional carbon dioxide assimilation, biomass and sugar yield, has a high potential for the production of bio-energy, bio-plastics and high-value products in the food and pharmaceutical industries. A crucial challenge for long-term economic viability and environmental sustainability is also to optimize the production of biomass composition and carbon sequestration. Sugarcane varieties such as KQ228 and Q253 are highly utilized in the industry. These varieties are characterized by a high early-season sugar content associated with high yield. In order to investigate these correlations, 1,440 internodes were collected and combined to generate a set of 120 samples in triplicate across 24 sugarcane cultivars at five different development stages. Weighted gene co-expression network analysis (WGCNA) was used and revealed for the first time two sets of co-expressed genes with a distinct and opposite correlation between fibre and sugar content. Gene identification and metabolism pathways analysis was used to define these two sets of genes. Correlation analysis identified a large number of interconnected metabolic pathways linked to sugar content and fibre content. Unsupervised hierarchical clustering of gene expression revealed a stronger level of segregation associated with the genotypes than the stage of development, suggesting a dominant genetic influence on biomass composition and facilitating breeding selection. Characterization of these two groups of co-expressed key genes can help to improve breeding program for high fibre, high sugar species or plant synthetic biology.

Genomic prediction with allele dosage information in highly polyploid species.

KEY MESSAGE: Including allele, dosage can improve genomic selection in highly polyploid species under higher frequency of different heterozygous genotypic classes and high dominance degree levels. Several studies have shown how to leverage allele dosage information to improve the accuracy of genomic selection models in autotetraploid. In this study, we expanded the methodology used for genomic selection in autotetraploid to higher (and mixed) ploidy levels. We adapted the models to build covariance matrices of both additive and digenic dominance effects that are subsequently used in genomic selection models. We applied these models using estimates of ploidy and allele dosage to sugarcane and sweet potato datasets and validated our results by also applying the models in simulated data. For the simulated datasets, including allele dosage information led up to 140% higher mean predictive abilities in comparison to using diploidized markers. Including dominance effects were highly advantageous when using diploidized markers, leading to mean predictive abilities which were up to 115% higher in comparison to only including additive effects. When the frequency of heterozygous genotypes in the population was low, such as in the sugarcane and sweet potato datasets, there was little advantage in including allele dosage information in the models. Overall, we show that including allele dosage can improve genomic selection in highly polyploid species under higher frequency of different heterozygous genotypic classes and high dominance degree levels.

Long-term comparison between index selection and optimal independent culling in plant breeding programs with genomic prediction.

In the context of genomic selection, we evaluated and compared breeding programs using either index selection or independent culling for recurrent selection of parents. We simulated a clonally propagated crop breeding program for 20 cycles using either independent culling or an economic index with two unfavourably correlated traits under selection. Cycle time from crossing to selection of parents was kept the same for both strategies. Both methods led to increasingly unfavourable genetic correlations between traits and, compared to independent culling, index selection led to larger changes in the genetic correlation between the two traits. When linkage disequilibrium was not considered, the two methods had similar losses of genetic diversity. Two independent culling approaches were evaluated, one using optimal culling levels and one using the same selection intensity for both traits. Optimal culling levels outperformed the same selection intensity even when traits had the same economic importance. Therefore, accurately estimating optimal culling levels is essential for maximizing gains when independent culling is performed. Once optimal culling levels are achieved, independent culling and index selection lead to comparable genetic gains.

Using machine learning to construct nomograms for patients with metastatic colon cancer.

AIM: Patients with synchronous colon cancer metastases have highly variable overall survival (OS), making accurate predictive models challenging to build. We aim to use machine learning to more accurately predict OS in these patients and to present this predictive model in the form of nomograms for patients and clinicians. METHODS: Using the National Cancer Database (2010-2014), we identified right colon (RC) and left colon (LC) cancer patients with synchronous metastases. Each primary site was split into training and testing datasets. Nomograms predicting 3- year OS were created for each site using Cox proportional hazard regression with lasso regression. Each model was evaluated by both calibration (comparison of predicted vs observed OS) and validation (degree of concordance as measured by the c-index) methodologies. RESULTS: A total of 11 018 RC and 8346 LC patients were used to construct and validate the nomograms. After stratifying each model into five risk groups, the predicted OS was within the 95% CI of the observed OS in four out of five risk groups for both the RC and LC models. Externally validated c-indexes at 3 years for the RC and LC models were 0.794 and 0.761, respectively. CONCLUSIONS: Utilization of machine learning can result in more accurate predictive models for patients with metastatic colon cancer. Nomograms built from these models can assist clinicians and patients in the shared decision-making process of their cancer care.

Genomic resources for energy cane breeding in the post genomics era.

Sugarcane is one of the most sustainable energy crops among cultivated crops presenting the highest tonnage of cultivated plants. Its high productivity of sugar, bioethanol and bioelectricity make it a promising green alternative to petroleum. Furthermore, the myriad of products that can be derived from sugarcane biomass has been driving breeding programs towards varieties with a higher yield of fiber and a more vigorous and sustainable performance: the energy cane. Here we provide an overview of the energy cane including plant description, breeding efforts, types, and end-uses. In addition, we describe recently published genomic resources for the development of this crop, discuss current knowledge of cell wall metabolism, bioinformatic tools and databases available for the community.

Evidence for Strong Kinship Influence on the Extent of Linkage Disequilibrium in Cultivated Common Beans.

Phaseolus vulgaris is an important grain legume for human consumption. Recently, association mapping studies have been performed for the species aiming to identify loci underlying quantitative variation of traits. It is now imperative to know whether the linkage disequilibrium (LD) reflects the true association between a marker and causative loci. The aim of this study was to estimate and analyze LD on a diversity panel of common beans using ordinary r² and r2 extensions which correct bias due to population structure (rS²), kinship (rV²), and both (rVS²). A total of 10,362 single nucleotide polymorphisms (SNPs) were identified by genotyping by sequencing (GBS), and polymorphisms were found to be widely distributed along the 11 chromosomes. In terms of r2, high values of LD (over 0.8) were identified between SNPs located at opposite chromosomal ends. Estimates for rV² were lower than those for rS². Results for rV² and rVS² were similar, suggesting that kinship may also include information on population structure. Over genetic distance, LD decayed to 0.1 at a distance of 1 Mb for rVS². Inter-chromosomal LD was also evidenced. This study showed that LD estimates decay dramatically according to the population structure, and especially the degree of kinship. Importantly, the LD estimates reported herein may influence our ability to perform association mapping studies on P. vulgaris.

A fully automated pipeline for quantitative genotype calling from next generation sequencing data in autopolyploids.

BACKGROUND: Genotyping-by-sequencing (GBS) has been used broadly in genetic studies for several species, especially those with agricultural importance. However, its use is still limited in autopolyploid species because genotype calling software generally fails to properly distinguish heterozygous classes based on allele dosage. RESULTS: VCF2SM is a Python script that integrates sequencing depth information of polymorphisms in variant call format (VCF) files and SUPERMASSA software for quantitative genotype calling. VCFs can be obtained from any variant discovery software that outputs exact allele sequencing depth, such as a modified version of the TASSEL-GBS pipeline provided here. VCF2SM was successfully applied in analyzing GBS data from diverse panels (alfalfa and potato) and full-sib mapping populations (alfalfa and switchgrass) of polyploid species. CONCLUSIONS: We demonstrate that our approach can help plant geneticists working with autopolyploid species to advance their studies by distinguishing allele dosage from GBS data.

Linkage Disequilibrium and Population Structure in Wild and Cultivated Populations of Rubber Tree (Hevea brasiliensis).

Among rubber tree species, which belong to the Hevea genus of the Euphorbiaceae family, Hevea brasiliensis (Willd. ex Adr.de Juss.) Muell. Arg. is the main commercial source of natural rubber production worldwide. Knowledge of the population structure and linkage disequilibrium (LD) of this species is essential for the efficient organization and exploitation of genetic resources. Here, we obtained single-nucleotide polymorphisms (SNPs) using a genotyping-by-sequencing (GBS) approach and then employed the SNPs for the following objectives: (i) to identify the positions of SNPs on a genetic map of a segregating mapping population, (ii) to evaluate the population structure of a germplasm collection, and (iii) to detect patterns of LD decay among chromosomes for future genetic association studies in rubber tree. A total of 626 genotypes, including both germplasm accessions (368) and individuals from a genetic mapping population (254), were genotyped. A total of 77,660 and 21,283 SNPs were detected by GBS in the germplasm and mapping populations, respectively. The mapping population, which was previously mapped, was constructed with 1,062 markers, among which only 576 SNPs came from GBS, reducing the average interval between two adjacent markers to 4.4 cM. SNPs from GBS genotyping were used for the analysis of genetic structure and LD estimation in the germplasm accessions. Two groups, which largely corresponded to the cultivated and wild populations, were detected using STRUCTURE and via principal coordinate analysis. LD analysis, also using the mapped SNPs, revealed that non-random associations varied along chromosomes, with regions of high LD interspersed with regions of low LD. Considering the length of the genetic map (4,693 cM) and the mean LD (0.49 for cultivated and 0.02 for wild populations), a large number of evenly spaced SNPs would be needed to perform genome-wide association studies in rubber tree, and the wilder the genotypes used, the more difficult the mapping saturation.

A retrospective analysis of factors associated with anesthetic case duration for cesarean deliveries.

INTRODUCTION: Accurately predicting cesarean delivery case duration is an integral component of designing appropriate workflow protocols and ensuring adequate provider availability. Our primary objective was to describe the variability of case duration, based on factors that we hypothesized would be influential, such as hospital facility type, United States region, time of day, case volume, and patient and provider characteristics. METHODS: We analyzed hospital-, patient-, and provider-level variables from the National Anesthesia Clinical Outcomes Registry, a voluntary registry created to share anesthesia-related data and outcomes. Multivariable linear regression was performed to assess the association of these variables to case duration. RESULTS: A total of 205332 cases were included in the final analysis. The majority of these cases came from medium-sized community hospitals (50.8%). Mean and median case duration were 115 and 79 minutes, respectively. Mean duration was longest for cases performed at university hospitals (143 min, standard deviation 136 min). Case duration varied in clinically meaningful ways based on hospital facility type, United States region, presence of a Certified Registered Nurse Anesthetist, and anesthesia type. Differences were not clinically significant with respect to other variables studied. CONCLUSION: This study analyzed national cesarean delivery data and determined factors associated with cesarean delivery duration. We showed that case durations varied in meaningful ways according to facility type, United States region, presence of a Certified Registered Nurse Anesthetist, and anesthesia type. Our work contributes to a small but growing body of research on optimal staffing models for anesthesia practices.

Fasting Upregulates npy, agrp, and ghsr Without Increasing Ghrelin Levels in Zebrafish (Danio rerio) Larvae.

Food intake in fish and mammals is orchestrated by hypothalamic crosstalk between orexigenic (food intake stimulation) and anorexigenic (food intake inhibition) signals. Some of these signals are released by peripheral tissues that are associated with energy homeostasis or nutrient availability. During the fish larva stage, orexigenic stimulation plays a critical role in individual viability. The goal of this study was to assess the mRNA levels of the main neuropeptides involved in food intake regulation (npy, agrp, carppt, and pomc), in concert with the mRNA levels and peptide levels of ghrelin, under a fasting intervention at the larval stage in zebrafish (Danio rerio). Prior to the fasting intervention, the zebrafish larva cohort was reared for 20 days post fertilization (dpf) and then randomly divided into two groups of 20 individuals. One group was subjected to a fasting intervention for 5 days (fasted group), and the other group was fed normally (fed group); this experimental protocol was performed twice independently. At the end of the fasting period, individuals from each experimental group were divided into different analysis groups, for evaluations such as relative gene expression, immunohistochemistry, and liquid chromatography coupled to nano high-resolution mass spectrometry (nLC-HRMS) analyses. The relative expression levels of the following genes were assessed: neuropeptide Y (npy), agouti-related peptide (agrp), proopiomelanocortin (pomc), cocaine and amphetamine-regulated transcript (cartpt), ghrelin (ghrl), ghrelin O-acyltransferase (mboat4), growth hormone secretagogue receptor (ghsr), and glucokinase (gck). In the fasted group, significant upregulation of orexigenic peptides (npy - agrp) and ghsr was observed, which was associated with significant downregulation of gck. The anorexigenic peptides (pomc and cartpt) did not show any significant modulation between the groups, similar to mboat4. Contrary to what was expected, the relative mRNA upregulation of the orexigenic peptides observed in the fasted experimental group could not be associated with significant ghrelin modulation as assessed by three different approaches: qPCR (relative gene expression of ghrelin), nLC-HRMS (des-acyl-ghrelin levels), and immunohistochemistry (integrated optical density of prepropeptides in intestinal and hepatopancreas tissues). Our results demonstrate that zebrafish larvae at 25 dpf exhibit suitable modulation of the relative mRNA levels of orexigenic peptides (npy and agrp) in response to fasting intervention; nevertheless, ghrelin was not coregulated by fasting. Therefore, it can be suggested that ghrelin is not an essential peptide for an increase in appetite in the zebrafish larva stage. These results give rise to new questions about food intake regulation factors in the early stages of fish.

Plant "electrome" can be pushed toward a self-organized critical state by external cues: Evidences from a study with soybean seedlings subject to different environmental conditions.

In the present study, we have investigated how the low-voltage electrical signals of soybean seedlings change their temporal dynamic under different environmental conditions (cold, low light, and low osmotic potential). We have used electrophytografic technique (EPG) with sub-dermal electrodes inserted in 15-days-old seedlings located between root and shoot, accounting for a significant part of the individual seedlings. Herein, to work on a specific framework to settle this type of the study, we are adopting the term "electrome" as a reference to the totality of electrical activity measured. Taking into account the non-linear dynamic of the plants electrophysiology, we have hypothesized that the stimuli, as applied in a constant way, could push the system to a critical state, exhibiting spikes without a characteristic size, indicating self-organized criticality (SOC). The results from the power spectral density analysis (PSD), showed that the interval of the large majority of the ß exponents were between 1.5 and 3, indicating that the time series, regardless environmental conditions, showed long-range temporal correlation (long memory for ß≠0 and ß≠2). The analyses from the histograms of the runs showed different patterns of distributions concerning the experimental conditions. However, the runs exhibiting typical spikes, mostly under low light and osmotic stress, showed power law distribution with exponent µ ≅ 2, which is an indicative for SOC. Overall, our results have confirmed that the temporal dynamic of the electrical signaling shows a complex non-linear behavior with long-range persistence. Moreover, the hypothesis that plant electrome can exhibit a self-organized critical state evoked by environmental cues, dissipating energy by bursts of electrical spikes without a characteristic size, was reinforced. Finally, new perspectives for research and additional hypothesis were presented.

ConPADE: genome assembly ploidy estimation from next-generation sequencing data.

As a result of improvements in genome assembly algorithms and the ever decreasing costs of high-throughput sequencing technologies, new high quality draft genome sequences are published at a striking pace. With well-established methodologies, larger and more complex genomes are being tackled, including polyploid plant genomes. Given the similarity between multiple copies of a basic genome in polyploid individuals, assembly of such data usually results in collapsed contigs that represent a variable number of homoeologous genomic regions. Unfortunately, such collapse is often not ideal, as keeping contigs separate can lead both to improved assembly and also insights about how haplotypes influence phenotype. Here, we describe a first step in avoiding inappropriate collapse during assembly. In particular, we describe ConPADE (Contig Ploidy and Allele Dosage Estimation), a probabilistic method that estimates the ploidy of any given contig/scaffold based on its allele proportions. In the process, we report findings regarding errors in sequencing. The method can be used for whole genome shotgun (WGS) sequencing data. We also show applicability of the method for variant calling and allele dosage estimation. Results for simulated and real datasets are discussed and provide evidence that ConPADE performs well as long as enough sequencing coverage is available, or the true contig ploidy is low. We show that ConPADE may also be used for related applications, such as the identification of duplicated genes in fragmented assemblies, although refinements are needed.

Gunshot wounds to the thigh. Evaluation of vascular and subclinical vascular injuries.

A retrospective review of 173 patient charts, angiograms, surgical reports, and plain radiographs were performed for all patients admitted with gunshot wounds to the thigh from May 1988 to January 1991 at Martin Luther King, Jr. Hospital. A zonal classification of gunshot wounds to the thigh was created and defined to determine if a zonal classification was predictive of a positive angiogram. Associations and relationships of patients with vascular injury are presented.

Gunshot wounds to the foot.

One hundred and one patients who sustained gunshot wounds to their feet were retrospectively reviewed. All patients were treated at King/Drew Medical Center between 1982 and 1994. From the authors' experience, they believe that patients with low-velocity gunshot wounds to the foot should be hospitalized and treated with at least a 3-day course of intravenous antibiotics of a first generation cephalosporin. Low-energy shotgun injuries should be treated the same as low-velocity injuries. Patients with high-velocity and high-energy shotgun wounds should be hospitalized and receive broad-spectrum intravenous antibiotics with multiple irrigation and debridements.

The safety of the Esmarch tourniquet.

The use of an Esmarch bandage as a tourniquet in surgery has been criticized. Many authors claim that the pressures under the Esmarch are inconsistent and may be extremely high. We have seen few, if any, problems from the use of an Esmarch in surgery of the foot and ankle. The purpose of this study was to evaluate the pressures generated under the Esmarch tourniquet in a situation that mimics its clinical application, and to determine whether pressures of appropriate magnitude and consistency are obtained in order to recommend its continued use in surgery. Ten volunteers performed numerous applications of the Esmarch. The number of wraps and the width of the Esmarch bandage used were varied. The Esmarch was applied as it would be for a surgical case. Pressures directly beneath the Esmarch were recorded 8 cm proximal to the distal tip of the medial malleolus. Considering all volunteers and all pressures generated, a 3-in Esmarch applied with three wraps gave a mean pressure (+/- SD) of 225 +/- 46 mm Hg. A 3-in Esmarch applied with four wraps gave a mean pressure of 291 +/- 53 mm Hg. A 4-in Esmarch applied with three wraps gave a mean pressure of 233 +/- 35 mm Hg, and a 4-in Esmarch with four wraps gave a mean pressure of 284 +/- 42 mm Hg. The maximum pressures generated by any individual were as follows: 3-in three wraps, 321 mm Hg; 3-in four wraps, 413 mm Hg; 4-in three wraps, 328 mm Hg; and 4-in four wraps, 380 mm Hg.(ABSTRACT TRUNCATED AT 250 WORDS)