Genetic Diversity and Differentiation of Eleven Medicago Species from Campania Region Revealed by Nuclear and Chloroplast Microsatellites Markers

The species belonging to the genus Medicago are considered a very important genetic resource at global level both for planet’s food security and for sustainable rangelands management. The checklist of the Italian flora (2021) includes a total number of 40 Medicago species for Italy, and 27 for Campania region, with a number of doubtful records or related to species no more found in the wild. In this study, 10 Medicago species native to Campania region, and one archaeophyte (M. sativa), identified by means of morphological diagnostic characters, were analyzed in a blind test to assay the efficacy of nine microsatellite markers (five cp-SSRs and four n-SSRs). A total number of 33 individuals from 6 locations were sampled and genotyped. All markers were polymorphic, 40 alleles were obtained with n-SSRs ranging from 8–12 alleles per locus with an average of 10 alleles per marker, PIC values ranged from 0.672 to 0.847, and the most polymorphic SSR was MTIC 564. The cp-SSRs markers were highly polymorphic too; PIC values ranged from 0.644 to 0.891 with an average of 0.776, the most polymorphic cp-SSR was CCMP10. 56 alleles were obtained with cp-SSRs ranging from 7 to 17 alleles per locus with an average of 11. AMOVA analysis with n-SSR markers highlighted a great level of genetic differentiation among the 11 species, with a statistically significant fixation index (FST). UPGMA clustering and Bayesian-based population structure analysis assigned these 11 species to two main clusters, but the distribution of species within clusters was not the same for the two analyses. In conclusion, our results demonstrated that the combination of the used SSRs well distinguished the 11 Medicago species. Moreover, our results demonstrated that the use of a limited number of SSRs might be considered for further genetic studies on other Medicago species.

Simultaneous Selection of Sweet-Waxy Corn Ideotypes Appealing to Hybrid Seed Producers, Growers, and Consumers in Thailand

Multi-trait selection helps breeders identify genotypes that appeal to divergent groups of preferences. In this study, we performed simultaneous selection of sweet-waxy corn hybrids on several traits covering the perspectives of consumers (taller kernel depth, better eating quality), growers (early maturity, shorter plant stature, and high ear yield), and seed producers (high flowering synchrony, acceptable seed yield, and good plant architecture). Three supersweet corn lines and 8 waxy corn lines were intercrossed to generate 48 F1 hybrids according to North Carolina Design II, and these genotypes were laid out in a randomized complete block design with 3 replications across 2 seasons between 2017 and 2018. A sensory blind test on sweetness, stickiness, tenderness, and overall liking was conducted to assess the eating quality of steamed corn samples. Two methods of simultaneous selection, namely unweighted selection index and overall rank-sum index (ORSI), were applied to rank crosses, following all targeted groups of preferences. Genetic parameters and genetic gain were estimated to evaluate the effectiveness of those selection methods. Both approaches had similar patterns of preferable realized gain on each given trait and could identify similar top five crosses with only slight order changes, implying that these methods were effective to rank genotypes according to given selection criteria. One of the tested crosses, 101L/TSC-10 × KV/mon, consistently had the highest unweighted selection index in the dry (7.84) and the rainy (7.15) seasons and the lowest ORSI (310), becoming a promising candidate as synergistic sweet-waxy corn hybrid appealing to consumers, growers, and seed producers. The expected ideotypes of sweet-waxy corn hybrid are discussed.

Effect of homeopathic treatment used in commercial boar semen diluent on sperm viability

Background: It has been speculated that the homeopathic treatment of sperm cells in order to improve semen quality could be promising. However, few data is available and its use in spermatozoa requires investigation. It is well established that mitochondrial membrane potential is an important viability parameter of spermatozoa and it is intimately related to reproductive efficiency. In this manner, new technologies in order to improve the activity of sperm cells and, finally, the fecundity of swine herds are of extremely importance. Due to the lack of knowledge of homeopathic treatment effect on spermatozoa, the aim of the present study was to verify the effect of three different homeopathic treatments on viability of boar sperm cells. Methods: semen samples were obtained from two sexually mature boars (18 mo of age). The boars were cross bred, with similar genetics of Pietrain versus Duroc, BP 450 progeny from a supplier company of similar reproductive performance animals. The animals were maintained in individual stalls, study conducted in Sao Paulo - Brazil. Three homeopathic treatments: Pulsatilla 6CH, Avena 6 CH or both, compared to placebo treatment (sucrose), the homeopathic medicaments or the control were administrated as globules manipulated according Brazilian Homeopathic Pharmacology. Each globule weighted 30 mg and contained sucrose as vehicle. One dose of two globules was added per 100 mL of diluted boar semen, which were chilled for 24 or 48 hours. All samples were labeled in codes in order to allow all laboratory analysis and evaluations being performed as a blind test. Data were tested for normality of residues and homogeneity of variances using the Guided Data Analysis software. Variables and interactions were analyzed by the PROC MIXED of the SAS package (SAS Institute Ins. Cary, NC). Adjusted least squares means (LSMEANS) of treatments were compared using the Tukey Test. Results: The different treatments contributed to maintain acrossome integrity for prolonged periods of cooling over 48 hours. The use of Pulsatilla was effective in maintaining high sperm mitochondria activity up to 24 hours from harvesting. Conclusion: Homeopathic medications can be used in artificial insemination in order to improve the quality of cooled and stored pig semen [1]. Keywords: homeopathy, swine semen, sperm viability. Reference [1] Soto, F. R. M.; Vuaden, E. R.; Coelho, C. P.; Bonamin, L. V.; Azevedo, S. S. A.; Benites, N. R.; Barros, F. R. O.; Goissis, M. D.; Assumpção, M. E. O. D.; Visintin, J. A.; Marques, M. G. Effects of the utilization of homeopathic elements in commercial diluent on swine sperm viability. In Vitro Cell.Dev.Biol.—Animal. 47:205–209, 2011.

Geostatistics assisted by machine learning for reservoir property modeling: A case study in presalt carbonates of Buzios Field, Brazil

An embedded model estimator (EMBER) petrophysical modeling algorithm has been applied to obtain effective porosity and permeability within the presalt carbonate reservoirs of the Barra Velha Formation in Buzios Field, Santos Basin. This advanced methodology was used due to the heterogeneity and complexity of the reservoirs, which makes modeling by conventional geostatistical methodologies difficult. For effective porosity modeling, we chose one facies model, one stratigraphic seismic attribute (acoustic impedance), and one structural seismic attribute (local flatness) as secondary variables. Permeability was modeled by using the best effective porosity simulation result as a secondary variable. Our results demonstrate that average effective porosity and permeability were 0.10 v/v and 440 md, respectively, indicating good reservoir quality throughout the studied area. A vertical trend of high effective porosities and permeabilities for the basal and uppermost reservoir sections was identified in our results, as well as a trend with lower values for these reservoir properties for the intermediate reservoir section. The lower section of the formation presented more continuity, and we infer it to be the best reservoir interval. We observed two horizontal trends for these reservoir properties at the formation top: one of higher values aligned to the north–south direction at the structural highs and another of lower reservoir properties related to isolated structural lows within structural highs. Correlation between modeled results and the blind test ANP-1 well upscaled properties was high, and upscaled well-log property distributions were preserved in the EMBER simulations, proving the predictive capacity of the algorithm. Finally, conditional distributions analysis indicated that the basal section of the Barra Velha Formation presents higher uncertainty for the estimation of effective porosity. Even though this interval is considered to have the best reservoir characteristics, decision making should be done with caution for this section.

Molecular and MALDI-TOF MS identification of swallow bugs Cimex hirundinis (Heteroptera: Cimicidae) and endosymbionts in France

Background The Cimicidae are obligatory blood-feeding ectoparasites of medical and veterinary importance. We aim in the current study to assess the ability of MALDI-TOF MS to identify Cimex hirundinis swallow bugs collected in house martin nests. Methods Swallow bugs were picked out from abandoned nests of house martin swallows and identified morphologically to the species level. The bugs were randomly selected, dissected and then subjected to MALDI-TOF MS and molecular analyses. Results A total of 65 adults and 50 nymphs were used in the attempt to determine whether this tool could identify the bug species and discriminate their developmental stages. Five adults and four nymphs of C. hirundinis specimens were molecularly identified to update our MS homemade arthropod database. BLAST analysis of COI gene sequences from these C. hirundinis revealed 98.66–99.12% identity with the corresponding sequences of C. hirundinis of the GenBank. The blind test against the database supplemented with MS reference spectra showed 100% (57/57) C. hirundinis adults and 100% (46/46) C. hirundinis nymphs were reliably identified and in agreement with morphological identification with logarithmic score values between 1.922 and 2.665. Ninety-nine percent of C. hirundinis specimens tested were positive for Wolbachia spp. The sequencing results revealed that they were identical to Wolbachia massiliensis, belonging to the new T-supergroup strain and previously isolated from C. hemipterus. Conclusions We report for the first time to our knowledge a case of human infestation by swallow bugs (C. hirundinis) in France. We also show the usefulness of MALDI-TOF MS in the rapid identification of C. hirundinis specimens and nymphs with minimal sample requirements. We phylogenetically characterized the novel Wolbachia strain (W. massiliensis) infecting C. hirundinis and compared it to other recognized Wolbachia clades. Graphical Abstract

Machine Learning Guided 3D Image Recognition for Carbonate Pore and Mineral Volumes Determination

<p>Automated image processing algorithms can improve the quality, efficiency, and consistency of classifying the morphology of heterogeneous carbonate rock and can deal with a massive amount of data and images seamlessly. Geoscientists and petroleum engineers face difficulties in setting the direction of the optimum method for determining petrophysical properties from core plug images of optical thin-sections, Micro-Computed Tomography (μCT), or Magnetic Resonance Imaging (MRI). Most of the successful work is from the homogeneous and clastic rocks focusing on 2D images with less focus on 3D and requiring numerical simulation. Currently, image analysis methods converge to three approaches: image processing, artificial intelligence, and combined image processing with artificial intelligence. In this work, we propose two methods to determine the porosity from 3D μCT and MRI images: an image processing method with Image Resolution Optimized Gaussian Algorithm (IROGA); advanced image recognition method enabled by Machine Learning Difference of Gaussian Random Forest (MLDGRF).</p><p>Meanwhile, we have built reference 3D micro models and collected images for calibration of the IROGA and MLDGRF methods. To evaluate the predictive capability of these calibrated approaches, we ran them on 3D μCT and MRI images of natural heterogeneous carbonate rock. We also measured the porosity and lithology of the carbonate rock using three and two industry-standard ways, respectively, as reference values. Notably, IROGA and MLDGRF have produced porosity results with an accuracy of 96.2% and 97.1% on the training set and 91.7% and 94.4% on blind test validation, respectively, in comparison with the three experimental measurements. We measured limestone and pyrite reference values using two methods, X-ray powder diffraction, and grain density measurements. MLDGRF has produced lithology (limestone and pyrite) volume fractions with an accuracy of 97.7% in comparison to reference measurements.</p>

Machine Learning Guided 3D Image Recognition for Carbonate Pore and Mineral Volumes Determination

<p>Automated image processing algorithms can improve the quality, efficiency, and consistency of classifying the morphology of heterogeneous carbonate rock and can deal with a massive amount of data and images seamlessly. Geoscientists and petroleum engineers face difficulties in setting the direction of the optimum method for determining petrophysical properties from core plug images of optical thin-sections, Micro-Computed Tomography (μCT), or Magnetic Resonance Imaging (MRI). Most of the successful work is from the homogeneous and clastic rocks focusing on 2D images with less focus on 3D and requiring numerical simulation. Currently, image analysis methods converge to three approaches: image processing, artificial intelligence, and combined image processing with artificial intelligence. In this work, we propose two methods to determine the porosity from 3D μCT and MRI images: an image processing method with Image Resolution Optimized Gaussian Algorithm (IROGA); advanced image recognition method enabled by Machine Learning Difference of Gaussian Random Forest (MLDGRF).</p><p>Meanwhile, we have built reference 3D micro models and collected images for calibration of the IROGA and MLDGRF methods. To evaluate the predictive capability of these calibrated approaches, we ran them on 3D μCT and MRI images of natural heterogeneous carbonate rock. We also measured the porosity and lithology of the carbonate rock using three and two industry-standard ways, respectively, as reference values. Notably, IROGA and MLDGRF have produced porosity results with an accuracy of 96.2% and 97.1% on the training set and 91.7% and 94.4% on blind test validation, respectively, in comparison with the three experimental measurements. We measured limestone and pyrite reference values using two methods, X-ray powder diffraction, and grain density measurements. MLDGRF has produced lithology (limestone and pyrite) volume fractions with an accuracy of 97.7% in comparison to reference measurements.</p>

Research on Chinese Consumers’ Preferences and Characteristics Regarding Scalp Care Shampoo Products

This study aims to explore consumers’ preferences on different types of shampoo products among women aged 20s and 30s from Beijing and Shanghai. 100 women who have scalp troubles were selected as respondents. By conducting HUT blind test, we compared the consumers’ feedbacks on 3 scalp care shampoo products but with 3 different formulations, i.e., 2 products with silicone-free formula and 1 product containing silicone oil. We adopted quantitative methodology through the whole analysis, and evaluation results of different groups were obtained by PCA analysis. The results of the study are recapped as follows: (1) Although there is no obvious difference in consumers’ preference among different ages, there are obvious differences in different regions. (2) Beijing consumers are satisfied with the sensory efficacy of the 3 products while Shanghai consumers are less satisfied with any of them. It is speculated that Shanghai consumers have a higher expectation for scalp care products; (3) Products containing silicone oil shows higher usage satisfaction when compared with silicone- free formula. It is better to emphasize long-term efficacy for silicone-free formula when planning GTM strategy, so that it could guide consumers to achieve their post-purchase rationalization. (4) Although the tested products all have scalp care function, consumers are more concerned about the effects on the health status of the hair than the scalp care effects.

Multiattribute probabilistic neural network for near-surface field engineering application

Unconfined compressive strength (UCS) is an important rock parameter required in the engineering design of structures built on top or within the interior of rock formations. In a site investigation project, UCS is typically obtained discretely (through point-to-point measurement) and interpolated. This method is less than optimal to resolve meter-scale UCS variations of heterogenous rock such as carbonate formations in which property changes occur within data spacing. We investigate the geotechnical application of multiattribute analysis based on near-surface reflection seismic data to probe rock formations for their strength attributes at meter-scale variability. Two Late Jurassic outcrops located in central Saudi Arabia serve as testing sites: the Hanifa Formation in Wadi Birk and the Jubaila Formation in Wadi Laban. The study uses core and 2D seismic profiles acquired in both sites, from which we constrain UCS, acoustic velocity, density, and gamma-ray values. A positive linear correlation between UCS and acoustic impedance along the core indicates that seismic attributes can be utilized as a method to laterally extrapolate the UCS away from the core location. Seismic colored inversion serves as input for neural network multiattribute analysis and is validated with a blind test. Results from data at both outcrop sites indicate a high degree of consistency with an absolute UCS error of approximately 5%. We also demonstrate the applicability of predicted UCS profiles to interpret mechanical stratigraphy and map lateral UCS heterogeneities. These findings provide a less expensive alternative to constrain UCS from limited core data on a field-scale site engineering project.