On the simulation of enzymatic digest patterns: the fragmentation of oligomeric and polymeric galacturonides by endo-polygalacturonase II

A simulation methodology for predicting the time-course of enzymatic digestions is described. The model is based solely on the enzyme's subsite architecture and concomitant binding energies. This allows subsite binding energies to be used to predict the evolution of the relative amounts of different products during the digestion of arbitrary mixtures of oligomeric or polymeric substrates. The methodology has been specifically demonstrated by studying the fragmentation of a population of oligogalacturonides of varying degrees of polymerization, when digested by endo-polygalacturonase II (endo-PG II) from Aspergillus niger.Comment: Preprint - has been accepted to Biochimica et Biophysica Act

Critical review of cultivated meat from a Nordic perspective

Background: Cultivated meat is a novel technology with the potential to partly substitute conventional meat in the future. Production of cultivated meat is based on biotechnology for tissue engineering, up-scaling of cell cultures and stem-cell differentiation, providing the basis for large-scale proliferation of the parent cell and subsequent differentiation into primitive skeletal muscle structures known from conventional meat. Development of cultivated meat is considered a socio-technological challenge including a variety of technical, sustainability, ethical, and consumer acceptance issues. Scope and approach: As the Nordic countries share common history and roots of food culture, cultivated meat will be introduced into a socio-cultural context with established food traditions. This review summarizes the current knowledge and activities on the development of cultivated meat in the Nordic countries and considers this novel food product in a specific socio-cultural context. Key findings and conclusions: The production of cultivated meat in the Nordic countries, must encompass solutions that are accepted by the typical Nordic consumer. In general, this favors solutions for cell culturing based on non-GMO cells and locally accessible raw material for cell medias and scaffolding. From the perspective of the Nordic countries, this will improve the environmental, societal, and ethical context of cultivated meat.publishedVersio

Detection of perineural invasion in prostate needle biopsies with deep neural networks

The presence of perineural invasion (PNI) by carcinoma in prostate biopsies has been shown to be associated with poor prognosis. The assessment and quantification of PNI are, however, labor intensive. To aid pathologists in this task, we developed an artificial intelligence (AI) algorithm based on deep neural networks. We collected, digitized, and pixel-wise annotated the PNI findings in each of the approximately 80,000 biopsy cores from the 7406 men who underwent biopsy in a screening trial between 2012 and 2014. In total, 485 biopsy cores showed PNI. We also digitized more than 10% (n = 8318) of the PNI negative biopsy cores. Digitized biopsies from a random selection of 80% of the men were used to build the AI algorithm, while 20% were used to evaluate its performance. For detecting PNI in prostate biopsy cores, the AI had an estimated area under the receiver operating characteristics curve of 0.98 (95% CI 0.97–0.99) based on 106 PNI positive cores and 1652 PNI negative cores in the independent test set. For a pre-specified operating point, this translates to sensitivity of 0.87 and specificity of 0.97. The corresponding positive and negative predictive values were 0.67 and 0.99, respectively. The concordance of the AI with pathologists, measured by mean pairwise Cohen’s kappa (0.74), was comparable to inter-pathologist concordance (0.68 to 0.75). The proposed algorithm detects PNI in prostate biopsies with acceptable performance. This could aid pathologists by reducing the number of biopsies that need to be assessed for PNI and by highlighting regions of diagnostic interest.publishedVersionPeer reviewe

Detection of perineural invasion in prostate needle biopsies with deep neural networks

The presence of perineural invasion (PNI) by carcinoma in prostate biopsies has been shown to be associated with poor prognosis. The assessment and quantification of PNI are, however, labor intensive. To aid pathologists in this task, we developed an artificial intelligence (AI) algorithm based on deep neural networks. We collected, digitized, and pixel-wise annotated the PNI findings in each of the approximately 80,000 biopsy cores from the 7406 men who underwent biopsy in a screening trial between 2012 and 2014. In total, 485 biopsy cores showed PNI. We also digitized more than 10% (n = 8318) of the PNI negative biopsy cores. Digitized biopsies from a random selection of 80% of the men were used to build the AI algorithm, while 20% were used to evaluate its performance. For detecting PNI in prostate biopsy cores, the AI had an estimated area under the receiver operating characteristics curve of 0.98 (95% CI 0.97-0.99) based on 106 PNI positive cores and 1652 PNI negative cores in the independent test set. For a pre-specified operating point, this translates to sensitivity of 0.87 and specificity of 0.97. The corresponding positive and negative predictive values were 0.67 and 0.99, respectively. The concordance of the AI with pathologists, measured by mean pairwise Cohen's kappa (0.74), was comparable to inter-pathologist concordance (0.68 to 0.75). The proposed algorithm detects PNI in prostate biopsies with acceptable performance. This could aid pathologists by reducing the number of biopsies that need to be assessed for PNI and by highlighting regions of diagnostic interest.</p

Derivation of 30 human embryonic stem cell lines—improving the quality

We have derived 30 human embryonic stem cell lines from supernumerary blastocysts in our laboratory. During the derivation process, we have studied new and safe method to establish good quality lines. All our human embryonic stem cell lines have been derived using human foreskin fibroblasts as feeder cells. The 26 more recent lines were derived in a medium containing serum replacement instead of fetal calf serum. Mechanical isolation of the inner cell mass using flexible metal needles was used in deriving the 10 latest lines. The lines are karyotypically normal, but culture adaptation in two lines has been observed. Our human embryonic stem cell lines are banked, and they are available for researchers

Interobserver reproducibility of perineural invasion of prostatic adenocarcinoma in needle biopsies

Numerous studies have shown a correlation between perineural invasion (PNI) in prostate biopsies and outcome. The reporting of PNI varies widely in the literature. While the interobserver variability of prostate cancer grading has been studied extensively, less is known regarding the reproducibility of PNI. A total of 212 biopsy cores from a population-based screening trial were included in this study (106 with and 106 without PNI according to the original pathology reports). The glass slides were scanned and circulated among four pathologists with a special interest in urological pathology for assessment of PNI. Discordant cases were stained by immunohistochemistry for S-100 protein. PNI was diagnosed by all four observers in 34.0% of cases, while 41.5% were considered to be negative for PNI. In 24.5% of cases, there was a disagreement between the observers. The kappa for interobserver variability was 0.67-0.75 (mean 0.73). The observations from one participant were compared with data from the original reports, and a kappa for intraobserver variability of 0.87 was achieved. Based on immunohistochemical findings among discordant cases, 88.6% had PNI while 11.4% did not. The most common diagnostic pitfall was the presence of bundles of stroma or smooth muscle. It was noted in a few cases that collagenous micronodules could be mistaken for a nerve. The distance between cancer and nerve was another cause of disagreement. Although the results suggest that the reproducibility of PNI may be greater than that of prostate cancer grading, there is still a need for improvement and standardization

N-1-methylnicotinamide is a signalling molecule produced in skeletal muscle coordinating energy metabolism

Obesity is a major health problem, and although caloric restriction and exercise are successful strategies to lose adipose tissue in obese individuals, a simultaneous decrease in skeletal muscle mass, negatively effects metabolism and muscle function. To deeper understand molecular events occurring in muscle during weight-loss, we measured the expressional change in human skeletal muscle following a combination of severe caloric restriction and exercise over 4 days in 15 Swedish men. Key metabolic genes were regulated after the intervention, indicating a shift from carbohydrate to fat metabolism. Nicotinamide N-methyltransferase (NNMT) was the most consistently upregulated gene following the energy-deficit exercise. Circulating levels of N-1-methylnicotinamide (MNA), the product of NNMT activity, were doubled after the intervention. The fasting-fed state was an important determinant of plasma MNA levels, peaking at similar to 18 h of fasting and being lowest similar to 3 h after a meal. In culture, MNA was secreted by isolated human myotubes and stimulated lipolysis directly, with no effect on glucagon or insulin secretion. We propose that MNA is a novel myokine that enhances the utilization of energy stores in response to low muscle energy availability. Future research should focus on applying MNA as a biomarker to identify individuals with metabolic disturbances at an early stage.Peer reviewe