Developmental and heat stress-regulated expression of HsfA2 and small heat shock proteins in tomato anthers

The high sensitivity of male reproductive cells to high temperatures may be due to an inadequate heat stress response. The results of a comprehensive expression analysis of HsfA2 and Hsp17-CII, two important members of the heat stress system, in the developing anthers of a heat-tolerant tomato genotype are reported here. A transcriptional analysis at different developmental anther/pollen stages was performed using semi-quantitative and real-time PCR. The messengers were localized using in situ RNA hybridization, and protein accumulation was monitored using immunoblot analysis. Based on the analysis of the gene and protein expression profiles, HsfA2 and Hsp17-CII are finely regulated during anther development and are further induced under both short and prolonged heat stress conditions. These data suggest that HsfA2 may be directly involved in the activation of protection mechanisms in the tomato anther during heat stress and, thereby, may contribute to tomato fruit set under adverse temperatures

Mitochondrial Variability as a Source of Extrinsic Cellular Noise

We present a study investigating the role of mitochondrial variability in generating noise in eukaryotic cells. Noise in cellular physiology plays an important role in many fundamental cellular processes, including transcription, translation, stem cell differentiation and response to medication, but the specific random influences that affect these processes have yet to be clearly elucidated. Here we present a mechanism by which variability in mitochondrial volume and functionality, along with cell cycle dynamics, is linked to variability in transcription rate and hence has a profound effect on downstream cellular processes. Our model mechanism is supported by an appreciable volume of recent experimental evidence, and we present the results of several new experiments with which our model is also consistent. We find that noise due to mitochondrial variability can sometimes dominate over other extrinsic noise sources (such as cell cycle asynchronicity) and can significantly affect large-scale observable properties such as cell cycle length and gene expression levels. We also explore two recent regulatory network-based models for stem cell differentiation, and find that extrinsic noise in transcription rate causes appreciable variability in the behaviour of these model systems. These results suggest that mitochondrial and transcriptional variability may be an important mechanism influencing a large variety of cellular processes and properties

Deformation Analysis with Feature Voting

[EN] Deformation analysis of GNSS network is usually computed using precise coordinates of the monitoring network points. Coordinates change over time construct a velocity field, which is used to estimate fault model parameters. Estimation process of coordinates is affected by several factors such as measurement errors, datum definition and the measurements datum defect. Points defining the monitoring datum have position accuracies which can increase inaccuracies in velocity estimations and the datum defect could cause biases and instability in computing the velocity field. This research proposes an algorithm of estimating geometric fault parameters using feature voting – addressing changes over time in GNSS vectors. The algorithm selects best solution for specific data-sets using minimal squared-disclosure between data and a tested value set of the fault model parameters. We concentrate on geometric fault models which rely solely on geometry between fault-line and monitoring network points. Geometric fault models are ill-conditioned, combined with low-frequency nature data - numerical instability rises. Vectors were computed with scientific processing software (Bernese), with consistent processing parameters at all epochs. Additionally, several numerical processes were adopted to transform the low-frequency data into usable datasets. Test cases were based upon 8 northern sites in the Israel’s continuous operating permanent stations. Simulative data was created from a true solved epoch; then variety of epoch data-sets were introduced to the algorithm to compute pre-defined geometric fault model parameters. Test cases show that simulative data, without and with noises, introduced to the algorithm is suited for estimating model parameters properly.Bar, O.; Even-Tzur, G. (2023). Deformation Analysis with Feature Voting. Editorial Universitat Politècnica de València. 533-536. http://hdl.handle.net/10251/19231653353

Body Mass Index and Caries: Machine Learning and Statistical Analytics of the Dental, Oral, Medical Epidemiological (DOME) Nationwide Big Data Study

The objectives of the research were to analyze the association between Body Mass Index (BMI) and dental caries using novel approaches of both statistical and machine learning (ML) models while adjusting for cardiovascular risk factors and metabolic syndrome (MetS) components, consequences, and related conditions. This research is a data-driven analysis of the Dental, Oral, Medical Epidemiological (DOME) big data repository, that integrates comprehensive socio-demographic, medical, and dental databases of a nationwide sample of dental attendees to military dental clinics for 1 year aged 18–50 years. Obesity categories were defined according to the World Health Organization (WHO): under-weight: BMI 2, normal weight: BMI 18.5 to 24.9 kg/m2, overweight: BMI 25 to 29.9 kg/m2, and obesity: BMI ≥ 30 kg/m2. General linear models were used with the mean number of decayed teeth as the dependent variable across BMI categories, adjusted for (1) socio-demographics, (2) health-related habits, and (3) each of the diseases comprising the MetS definition MetS and long-term sequelae as well as associated illnesses, such as hypertension, diabetes, hyperlipidemia, cardiovascular disease, obstructive sleep apnea (OSA) and non-alcoholic fatty liver disease (NAFLD). After the statistical analysis, we run the XGBoost machine learning algorithm on the same set of clinical features to explore the features’ importance according to the dichotomous target variable of decayed teeth as well as the obesity category. The study included 66,790 subjects with a mean age of 22.8 ± 7.1. The mean BMI score was 24.2 ± 4.3 kg/m2. The distribution of BMI categories: underweight (3113 subjects, 4.7%), normal weight (38,924 subjects, 59.2%), overweight (16,966, 25.8%), and obesity (6736, 10.2%). Compared to normal weight (2.02 ± 2.79), the number of decayed teeth was statistically significantly higher in subjects with obesity [2.40 ± 3.00; OR = 1.46 (1.35–1.57)], underweight [2.36 ± 3.04; OR = 1.40 (1.26–1.56)] and overweight [2.08 ± 2.76, OR = 1.05 (1.01–1.11)]. Following adjustment, the associations persisted for obesity [OR = 1.56 (1.39–1.76)] and underweight [OR = 1.29 (1.16–1.45)], but not for overweight [OR = 1.11 (1.05–1.17)]. Features important according to the XGBoost model were socioeconomic status, teeth brushing, birth country, and sweetened beverage consumption, which are well-known risk factors of caries. Among those variables was also our main theory independent variable: BMI categories. We also performed clinical features importance based on XGBoost with obesity set as the target variable and received an AUC of 0.702, and accuracy of 0.896, which are considered excellent discrimination, and the major features that are increasing the risk of obesity there were: hypertension, NAFLD, SES, smoking, teeth brushing, age as well as our main theory dependent variable: caries as a dichotomized variable (Yes/no). The study demonstrates a positive association between underweight and obesity BMI categories and caries, independent of the socio-demographic, health-related practices, and other systemic conditions related to MetS that were studied. Better allocation of resources is recommended, focusing on populations underweight and obese in need of dental care

Ribosomal protein L24 mediates mammalian microRNA processing in an evolutionarily conserved manner

To investigate the mechanism(s) underlying the expression of primate-specific microRNAs (miRs), we sought DNA regulatory elements and proteins mediating expression of the primate-specific hsa-miR-608 (miR-608), which is located in the SEMA4G gene and facilitates the cholinergic blockade of inflammation by targeting acetylcholinesterase mRNA. 'Humanized' mice carrying pre-miR-608 flanked by 250 bases of endogenous sequences inserted into the murine Sema4g gene successfully expressed miR-608. Moreover, by flanking miR-608 by shortened fragments of its human genome region we identified an active independent promoter within the 150 nucleotides 5' to pre-miR-608, which elevated mature miR-608 levels by 100-fold in transfected mouse- and human-originated cells. This highlighted a regulatory role of the 5' flank as enabling miR-608 expression. Moreover, pull-down of the 150-base 5' sequence revealed its interaction with ribosomal protein L24 (RPL24), implicating an additional mechanism controlling miR-608 levels. Furthermore, RPL24 knockdown altered the expression of multiple miRs, and RPL24 immunoprecipitation indicated that up- or down-regulation of the mature miRs depended on whether their precursors bind RPL24 directly. Finally, further tests showed that RPL24 interacts directly with DDX5, a component of the large microprocessor complex, to inhibit miR processing. Our findings reveal that RPL24, which has previously been shown to play a role in miR processing in Arabidopsis thaliana, has a similar evolutionarily conserved function in miR biogenesis in mammals. We thus characterize a novel extra-ribosomal role of RPL24 in primate miR regulation

Associations of Exposure to Nitrogen Oxides with Prevalent Asthma and Other Atopic Diseases in Israel

Childhood exposure to nitrogen oxides (NOx) is considered a risk factor for the onset of asthma. However, associations of this exposure with other atopic diseases and factors that modify this association are less clear. We aimed to study associations between exposure to NOx and the prevalence of atopic diseases in Israeli adolescents using a cross-sectional design. The study population comprised all Israeli-born adolescents whose medical status was evaluated for mandatory military recruitment during 1967–2017 (n = 2,523,745), of whom 5.9% had prevalent asthma. We based the exposure assessments on a land-use regression model and estimated associations using multivariable logistic regression models. Across all periods, mean exposure to NOx from birth to adolescence was associated with prevalent asthma at the examination in a dose-response manner, with an odds ratio for the upper quintile of 1.61 (95% CI: 1.56–1.67), in comparison to the lowest quintile. Associations were stronger in males and in lower socioeconomic strata. We found the strongest associations for asthma with comorbid rhinitis, with an almost twofold increase in the odds of upper versus lower quintile of exposure (odds ratio = 1.96, 95% CI: 1.82–2.11). Rhino-conjunctivitis and allergic atopic dermatitis suggested a possible threshold level with NOx. Capsule Summary: Research indicates that half of the global population will suffer from an allergic condition at some point in life. Childhood exposure to nitrogen oxides is a risk factor for the onset of asthma. The association between exposure and allergic diseases other than asthma is unclear. We demonstrate a strong, dose-response relationship between exposure and a group of allergic outcomes, using data comprising 2.5 million subjects over 50 years. The large health benefits from clean air should motivate governments to prioritize mitigation measures