Generation of Haploid Spermatids on Silk Fibroin-Alginate-Laminin-Based Porous 3D Scaffolds

In vitro production of sperm is a desirable idea for fertility preservation in azoospermic men and prepubertal boys suffering from cancer. In this study, a biocompatible porous scaffold based on a triad mixture of silk fibroin (SF), alginate (Alg), and laminin (LM) is developed to facilitate the differentiation of mouse spermatogonia stem cells (SSCs). Following SF extraction, the content is analyzed by SDS-PAGE and stable porous 3D scaffolds are successfully prepared by merely Alg, SF, and a combination of Alg-SF, or Alg-SF-LM through freeze-drying. Then, the biomimetic scaffolds are characterized regarding the structural and biological properties, water absorption capacity, biocompatibility, biodegradability, and mechanical behavior. Neonatal mice testicular cells are seeded on three-dimensional scaffolds and their differentiation efficiency is evaluated using real-time PCR, flow cytometry, immunohistochemistry. Blend matrices showed uniform porous microstructures with interconnected networks, which maintained long-term stability and mechanical properties better than homogenous structures. Molecular analysis of the cells after 21 days of culture showed that the expression of differentiation-related proteins in cells that are developed in composite scaffolds is significantly higher than in other groups. The application of a composite system can lead to the differentiation of SSCs, paving the way for a novel infertility treatment landscape in the future.

Performance of a machine-learning algorithm for fully automatic LGE scar quantification in the large multi-national derivate registry

Funding Acknowledgements

Type of funding sources: Other. Main funding source(s): J. Schwitter receives research support by “ Bayer Schweiz AG “. C.N.C. received grant by Siemens. Gianluca Pontone received institutional fees by General Electric, Bracco, Heartflow, Medtronic, and Bayer. U.J.S received grand by Astellas, Bayer, General Electric. This work was supported by Italian Ministry of Health, Rome, Italy (RC 2017 R659/17-CCM698). This work was supported by Gyrotools, Zurich, Switzerland.

Background

 Late Gadolinium enhancement (LGE) scar quantification is generally recognized as an accurate and reproducible technique, but it is observer-dependent and time consuming. Machine learning (ML) potentially offers to solve this problem. 

Purpose

 to develop and validate a ML-algorithm to allow for scar quantification thereby fully avoiding observer variability, and to apply this algorithm to the prospective international multicentre Derivate cohort.

Method

 The Derivate Registry collected heart failure patients with LV ejection fraction <50% in 20 European and US centres. In the post-myocardial infarction patients (n = 689) quality of the LGE short-axis breath-hold images was determined (good, acceptable, sufficient, borderline, poor, excluded) and ground truth (GT) was produced (endo-epicardial contours, 2 remote reference regions, artefact elimination) to determine mass of non-infarcted myocardium and of dense (≥5SD above mean-remote) and non-dense scar (>2SD to <5SD above mean-remote). Data were divided into the learning (total n = 573; training: n = 289; testing: n = 284) and validation set (n = 116). A Ternaus-network (loss function = average of dice and binary-cross-entropy) produced 4 outputs (initial prediction, test time augmentation (TTA), threshold-based prediction (TB), and TTA + TB) representing normal myocardium, non-dense, and dense scar (Figure 1).Outputs were evaluated by dice metrics, Bland-Altman, and correlations. 

Results

 In the validation and test data sets, both not used for training, the dense scar GT was 20.8 ± 9.6% and 21.9 ± 13.3% of LV mass, respectively. The TTA-network yielded the best results with small biases vs GT (-2.2 ± 6.1%, p < 0.02; -1.7 ± 6.0%, p < 0.003, respectively) and 95%CI vs GT in the range of inter-human comparisons, i.e. TTA yielded SD of the differences vs GT in the validation and test data of 6.1 and 6.0 percentage points (%p), respectively (Fig 2), which was comparable to the 7.7%p for the inter-observer comparison (n = 40). For non-dense scar, TTA performance was similar with small biases (-1.9 ± 8.6%, p < 0.0005, -1.4 ± 8.2%, p < 0.0001, in the validation and test sets, respectively, GT 39.2 ± 13.8% and 42.1 ± 14.2%) and acceptable 95%CI with SD of the differences of 8.6 and 8.2%p for TTA vs GT, respectively, and 9.3%p for inter-observer. 

Conclusions

 In the large Derivate cohort from 20 centres, performance of the presented ML-algorithm to quantify dense and non-dense scar fully automatically is comparable to that of experienced humans with small bias and acceptable 95%-CI. Such a tool could facilitate scar quantification in clinical routine as it eliminates human observer variability and can handle large data sets.

Phase-field modeling of constrained interactive fungal networks

Fungi develop structures that interact with their surroundings and evolve adaptively in the presence of geometrical constraints, finding optimal solutions for complex combinatorial problems. The pathogenic fungus Ophiocordyceps constitutes a perfect model for the study of constrained interactive networks. Modeling these networks is challenging due to the highly coupled physics involved and their interaction with moving boundaries. In this work, we develop a computational phase-field model to elucidate the mechanics of the emerging properties observed in fungal networks. We use a variational approach to derive the equations governing the evolution in time of the mycelium biomass and the nutrients in the medium. We present an extensive testing of our model, reproduce growing and decaying phenomena, and capture spatial and temporal scales. We explore the variables interplay mechanism that leads to different colony morphologies, and explain abrupt changes of patterns observed in the laboratory. We apply our model to simulate analogous processes to the evolution of Ophiocordyceps as it grows through confined geometry and depletes available resources, demonstrating the suitability of the formulation to study this class of biological networks.

Antibiotic resistance profiles of Salmonella serotypes isolated from animals in Iran: a meta-analysis

BACKGROUND

Salmonella infection (salmonellosis) is a zoonotic bacterial disease. Widespread use of antibiotics in livestock and poultry production for different purposes such as treatment and growth promotion has led to the emergence of antibiotic-resistant Salmonella, causing treatment of Salmonella infections more difficult with each passing year.

AIMS

To determine the antibiotic resistance prevalence of Salmonella serotypes isolated from animals in different provinces of Iran.

METHODS

To find eligible articles, we searched the international and national electronic databases using appropriate keywords in English and Persian.

RESULTS

After applying predefined criteria, 54 articles reporting antibiotic resistance profiles of Salmonella serotypes were included. Salmonella isolates were mostly resistant against nalidixic acid (67%), tetracycline (66.9%), and streptomycin (49.6%), followed by trimethoprim/sulfamethoxazole (41.6%) and kanamycin (23.6%). The highest sensitivity was observed against imipenem, meropenem, and cefepime with 1.7%, 1.4%, and 1.9% of all isolates being resistant, respectively.

CONCLUSION

Results revealed that the prevalence of resistant isolates to nalidixic acid, tetracycline and streptomycin is high and their use must be restricted. In addition, resistance to other antibiotics such as chloramphenicol, ampicillin, cephalothin, cefixime, and enrofloxacin is at an alarming level that calls for attention in the future infection control and antibiotic stewardship programs.

Human health risk assessment of organophosphorus pesticide in rice crop from selected districts of Anzali International Wetland basin, Iran

Low fertility in rice caused by Chilo suppressalis has led to the use of diazinon to control this pest. Residue of pesticide could penetrate products and also food which can affect public health. The aim of this research was to determine health risk assessment of organophosphorus (OP) pesticide in rice, a strategic crop in Iran. Ninety rice samples were collected from 30 points during harvesting seasons from Rasht Area, Guilan Province, Iran from which 30 samples were prepared. The concentration of diazinon, the most common pesticide used in the study area, was determined by high-performance liquid chromatography. The result indicated that the total average of diazinon in rice samples (31.91 mg/kg) is by far higher than the maximum residue limit recommended by the European Union. According to the results, EDAI was 0.051 mg/kg day, while health risk index in rice was 10.2. Results showed that there is a health risk associated with the lifetime consumption of rice polluted by OP pesticide in the study area.

Unexpectedly high occurrence of Escherichia coli and Staphylococcus aureus isolates from raw milk in Ilam, Western Iran

Raw milk contains diverse nutritional components that provide a suitable medium for spoilage and the growth of potentially pathogenic microorganisms. Unpasteurized milk consumption by a large number of people can threaten health and increase public concerns. In this study, sixty-two raw cow’s milk samples were collected from the dairy farms of Ilam, Western Iran. All samples were collected in sterilized containers and were transferred via ice boxes to the laboratory. Isolates were then identified by standard methods. Totally, 88.7% (n=55) of samples were contaminated. Our study also showed that Escherichia coli had a high prevalence among isolates (43: 69.4%), while Klebsiella pneumoniae and Klebsiella planticola showed the lowest prevalence (1: 1.6%). Staphylococcus aureus was also detected in 17.7% (n=11) of samples. The raw milk microbial contamination is complex. Some of the microorganisms threaten public health via different traits, therefore it is recommended that raw milk consumption should be avoided.

A Critical Evaluation of the Experimental Design of Studies of Mechanism Based Enzyme Inhibition, with Implications for In Vitro-In Vivo Extrapolation

The published literature on mechanism based inhibition (MBI) of CYPs was evaluated with respect to experimental design, methodology and data analysis. Significant variation was apparent in the dilution factor, ratio of preincubation to incubation times and probe substrate concentrations used, and there were some anomalies in the estimation of associated kinetic parameters (k(inact), K(I), r). The impact of the application of inaccurate values of k(inact) and K(I) when extrapolating to the extent of inhibition in vivo is likely to be greatest for those compounds of intermediate inhibitory potency, but this also depends on the fraction of the net clearance of substrate subject to MBI and the pre-systemic and systemic exposure to the inhibitor. For potent inhibitors, the experimental procedure is unlikely to have a material influence on the maximum inhibition. Nevertheless, the bias in the values of the kinetic parameters may influence the time for recovery of enzyme activity following re-synthesis of the enzyme. Careful attention to the design of in vitro experiments to obtain accurate kinetic parameters is necessary for a reliable prediction of different aspects of the in vivo consequences of MBI. The review calls for experimental studies to quantify the impact of study design in studies of MBI, with a view to better harmonisation of protocols.