Predicting optimal in vitro culture medium for <Emphasis Type="Italic">Pistacia vera</Emphasis> micropropagation using neural networks models

In this study, artificial intelligence techniques—specifically artificial neural networks (ANNs) in combination with fuzzy logic (neurofuzzy logic) or with genetic algorithms (ANNs–GA)—have been employed, as modeling tools, to get insight, to predict and to optimize the effect of several independent factors on four growth parameters during Pistacia vera micropropagation. Twenty-six media ingredients, including mineral ions (or salts), glycine, vitamins and plant growth regulators (PGRs) at different concentrations, were used as inputs and four growth parameters: proliferation rate, shoot length, total and healthy fresh weight as outputs on the models. The IF-THEN rules from neurofuzzy logic models have allowed discovering the positive (BAP, nicotinic-acid and pyridoxine-HCl) and negative (NO₃ ^?, Mg²⁺, Ag⁺ and gluconate^?) effects on the growth parameters and the fundamental role of BAP over all of them. Also, ANNs–GA technology has permitted to estimate the best combination of media ingredients to simultaneously maximize the four parameters of growth: 4.4 new shoots per explant; 28.7 mm length; 1.1 and 0.53 g total and healthy fresh weight, respectively, minimizing physiological disorders. In our opinion, the information obtained in this study is extremely useful to improve the massive multiplication of pistachio plant, in particular, but also demonstrate the ability of artificial intelligence technology to design plant tissue culture media with predictable and tailorable characteristics.     

A novel method based on combination of semi-in vitro and in vivo conditions in Agrobacterium rhizogenes-mediated hairy root transformation of Glycine species

Despite numerous advantages of the many tissue culture-independent hairy root transformation protocols, the process is often compromised in the initial in vitro culture stage where inability to maintain high humidity and the delivery of nourishing culture medium decrease cellular morphogenesis and organ formation efficiency. Ultimately, this influences the effective transfer of produced plantlets during transfer from in vitro to in vivo conditions, where low survival rates occur during the acclimation period. We have developed an intermediate protocol for Agrobacterium rhizogenes transformation in Glycine species by combining a two-step in vitro and in vivo process that greatly enhances the efficiency of hairy root formation and which simplifies the maintenance of the transformed roots. In this protocol, cotyledonary nodes of Glycine max and Glycine canescens seedlings were infected by A. rhizogenes K599 carrying a reporter gene construct constitutively expressing green fluorescent protein (GFP). Glass containers containing sand and nutrient solution were employed to provide a moist clean microenvironment for the generation of hairy roots from inoculated seedlings. Transgenic roots were then noninvasively identified from nontransgenic roots based on the detection of GFP. Main roots and nontransgenic roots were removed leaving transgenic hairy roots to support seedling development, all within 1 mo of beginning the experiment. Overall, this protocol increased the transformation efficiency by more than twofold over traditional methods. Approximately 88% and 100% of infected plants developed hairy roots from G. max and G. canescens, respectively. On average, each infected plant produced 10.9 transformed hairy roots in G. max and 13–20 in G. canescens. Introduction of this simple protocol is a significant advance that eliminates the long and genotype-dependent tissue culture procedure while taking advantage of its optimum in vitro qualities to enhance the micropropagation rate. This research will support the increasing use of transient transgenic hairy roots for the study of plant root biology and symbiotic interactions with Rhizobium spp.     

The Role of Stem Cells in the Treatment of Cerebral Palsy: a Review

Cerebral palsy (CP) is a neuromuscular disease due to injury in the infant’s brain. The CP disorder causes many neurologic dysfunctions in the patient. Various treatment methods have been used for the management of CP disorder. However, there has been no absolute cure for this condition. Furthermore, some of the procedures which are currently used for relief of symptoms in CP cause discomfort or side effects in the patient. Recently, stem cell therapy has attracted a huge interest as a new therapeutic method for treatment of CP. Several investigations in animal and human with CP have demonstrated positive potential of stem cell transplantation for the treatment of CP disorder. The ultimate goal of this therapeutic method is to harness the regenerative capacity of the stem cells causing a formation of new tissues to replace the damaged tissue. During the recent years, there have been many investigations on stem cell therapy. However, there are still many unclear issues regarding this method and high effort is needed to create a technology as a perfect treatment. This review will discuss the scientific background of stem cell therapy for cerebral palsy including evidences from current clinical trials.     

Predominant culturable crude oil-degrading bacteria in the coast of Kuwait

Total of 272 crude oil-degrading bacteria were isolated from seven locations along the coast of Kuwait. The analysis of the 16S rDNA sequences of isolated bacteria revealed the predominance of six bacterial genera: Pseudomonas, Bacillus, Staphylococcus, Acinetobacter, Kocuria and Micrococcus. Investigation of the factors associated with bacterial predominance revealed that, dominant culturable crude oil-degrading bacteria were better crude oil utilizers than the less frequently occurring isolates. Bacterial predominance was also influenced by the ability of bacteria to adapt to the level of organic content available. Predominant culturable bacteria constituted 89.7–54.2% of the total crude oil-degrading bacterial communities. Using 16S-RFLP analyses to assess the diversity of the dominant crude oil-degrading bacterial genera, four phylotypes of Pseudomonas sp. and seven phylotypes of Bacillus sp. were determined. This suggested high degree of diversity of crude oil-degrading bacterial population at the strain level, but low diversity at the genus level.     

Unmet need for hypercholesterolemia care in 35 low- and middle-income countries: A cross-sectional study of nationally representative surveys

BackgroundAs the prevalence of hypercholesterolemia is increasing in low- and middle-income countries (LMICs), detailed evidence is urgently needed to guide the response of health systems to this epidemic. This study sought to quantify unmet need for hypercholesterolemia care among adults in 35 LMICs.Methods and findingsWe pooled individual-level data from 129,040 respondents aged 15 years and older from 35 nationally representative surveys conducted between 2009 and 2018. Hypercholesterolemia care was quantified using cascade of care analyses in the pooled sample and by region, country income group, and country. Hypercholesterolemia was defined as (i) total cholesterol (TC) ≥240 mg/dL or self-reported lipid-lowering medication use and, alternatively, as (ii) low-density lipoprotein cholesterol (LDL-C) ≥160 mg/dL or self-reported lipid-lowering medication use. Stages of the care cascade for hypercholesterolemia were defined as follows: screened (prior to the survey), aware of diagnosis, treated (lifestyle advice and/or medication), and controlled (TC <200 mg/dL or LDL-C <130 mg/dL). We further estimated how age, sex, education, body mass index (BMI), current smoking, having diabetes, and having hypertension are associated with cascade progression using modified Poisson regression models with survey fixed effects.High TC prevalence was 7.1% (95% CI: 6.8% to 7.4%), and high LDL-C prevalence was 7.5% (95% CI: 7.1% to 7.9%). The cascade analysis showed that 43% (95% CI: 40% to 45%) of study participants with high TC and 47% (95% CI: 44% to 50%) with high LDL-C ever had their cholesterol measured prior to the survey. About 31% (95% CI: 29% to 33%) and 36% (95% CI: 33% to 38%) were aware of their diagnosis; 29% (95% CI: 28% to 31%) and 33% (95% CI: 31% to 36%) were treated; 7% (95% CI: 6% to 9%) and 19% (95% CI: 18% to 21%) were controlled. We found substantial heterogeneity in cascade performance across countries and higher performances in upper-middle-income countries and the Eastern Mediterranean, Europe, and Americas. Lipid screening was significantly associated with older age, female sex, higher education, higher BMI, comorbid diagnosis of diabetes, and comorbid diagnosis of hypertension. Awareness of diagnosis was significantly associated with older age, higher BMI, comorbid diagnosis of diabetes, and comorbid diagnosis of hypertension. Lastly, treatment of hypercholesterolemia was significantly associated with comorbid hypertension and diabetes, and control of lipid measures with comorbid diabetes. The main limitations of this study are a potential recall bias in self-reported information on received health services as well as diminished comparability due to varying survey years and varying lipid guideline application across country and clinical settings.ConclusionsCascade performance was poor across all stages, indicating large unmet need for hypercholesterolemia care in this sample of LMICs—calling for greater policy and research attention toward this cardiovascular disease (CVD) risk factor and highlighting opportunities for improved prevention of CVD.

Maja Marcus and colleagues use nationally-representative surveys conducted between 2009 and 2018 to investigate the unmet need for hypercholesterolemia care in 35 low- and middle-income countries.     

Hydrothermal time analysis of watermelon (<Emphasis Type="Italic">Citrullus vulgaris</Emphasis> cv. ‘Crimson sweet’) seed germination

This study evaluated the ability of a hydrothermal time model (HTT) to describe the kinetics of watermelon (Citrullus vulgaris cv. ‘Crimson sweet’) seed germination under different temperatures (T) and water potentials (ψ) and also to determine the cardinal temperatures of watermelon. Results indicated that ψ influenced germination rate and germination percentage. For this seed lot, cardinal temperatures were 10 °C for T _b, 28.34 °C for T _o and 40.8 °C for T _c in the control (0 MPa) treatment. There was a decrease in hydrotime constant (θ _H) when T was increased to T _o and then remained constant at supra-optimal temperatures (30 MPah^?1). Also, at temperatures above T _o, ψ _b(50) values increased linearly with T. The k _T value (the slope of the relationship between ψ _b(50) and T exceeds T _o) of this seed lot was calculated as 0.076 MPa°Ch^?1. Results this study show that when the HTT model is applied, it can accurately describe ψ _b(g) and the course of germination around Ts (R ² = 0.82). Moreover, the ψ _b(50) was estimated to be ?0.96 MPa based on this model. Consequently, the germination response of watermelon for all Ts and ψs can be adequately described by the HTT model and enabling it to be used as a predictive tool in watermelon seed germination simulation models.     

Streptomyces strains alleviate water stress and increase peppermint (Mentha piperita) yield and essential oils

Plant and Soil - Drought is the most significant factor limiting plant production in a majority of agricultural fields worldwide. PGPRs (plant growth promoting rhizobacteria) are beneficial soil...     

Anti-Inflammatory Effects of Lactobacillus Rahmnosus and Bifidobacterium Breve on Cigarette Smoke Activated Human Macrophages

Background

Chronic obstructive pulmonary disease (COPD) is a major global health problem with cigarette smoke (CS) as the main risk factor for its development. Airway inflammation in COPD involves the increased expression of inflammatory mediators such as CXCL-8 and IL-1β which are important mediators for neutrophil recruitment. Macrophages are an important source of these mediators in COPD. Lactobacillus rhamnosus (L. rhamnosus) and Befidobacterium breve (B. breve) attenuate the development of ‘allergic asthma’ in animals but their effects in COPD are unknown.

Objective

To determine the anti-inflammatory effects of L. rhamnosus and B. breve on CS and Toll-like receptor (TLR) activation.

Design

We stimulated the human macrophage cell line THP-1 with CS extract in the presence and absence of L. rhamnosus and B. breve and measured the expression and release of inflammatory mediators by RT-qPCR and ELISA respectively. An activity assay and Western blotting were used to examine NF-κB activation.

Results

Both L. rhamnosus and B. breve were efficiently phagocytized by human macrophages. L. rhamnosus and B. breve significantly suppressed the ability of CS to induce the expression of IL-1β, IL-6, IL-10, IL-23, TNFα, CXCL-8 and HMGB1 release (all p<0.05) in human THP-1 macrophages. Similar suppression of TLR4- and TLR9-induced CXCL8 expression was also observed (p<0.05). The effect of L. rhamnosus and B. breve on inflammatory mediator release was associated with the suppression of CS-induced NF-κB activation (p<0.05).

Conclusions

This data indicate that these probiotics may be useful anti-inflammatory agents in CS-associated disease such as COPD.     

Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations

Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biology. However, these methods have been less frequently used with empirical population genetics data. In this study, we developed a new combined approach of data analysis using microsatellite marker data from our previous studies of olive populations using machine learning algorithms. Herein, 267 olive accessions of various origins including 21 reference cultivars, 132 local ecotypes, and 37 wild olive specimens from the Iranian plateau, together with 77 of the most represented Mediterranean varieties were investigated using a finely selected panel of 11 microsatellite markers. We organized data in two ‘4-targeted’ and ‘16-targeted’ experiments. A strategy of assaying different machine based analyses (i.e. data cleaning, feature selection, and machine learning classification) was devised to identify the most informative loci and the most diagnostic alleles to represent the population and the geography of each olive accession. These analyses revealed microsatellite markers with the highest differentiating capacity and proved efficiency for our method of clustering olive accessions to reflect upon their regions of origin. A distinguished highlight of this study was the discovery of the best combination of markers for better differentiating of populations via machine learning models, which can be exploited to distinguish among other biological populations.