Characteristics of laparoscopic and open hernia repair simulation models: a systematic review.

PURPOSE: Barriers to education in open and laparoscopic hernia repair technique include a steep learning curve and reduced theatre time for junior surgical trainees. This is particularly evident during the current COVID-19 pandemic. Simulation models may provide further opportunities for training in hernia repair outside of the traditional surgical apprenticeship model. METHODS: A systematic review was carried out following PRISMA guidelines to identify and evaluate simulation models in hernia repair. Of the 866 records screened, 27 were included in the analysis. These were assessed for face, content and construct validity, as well as their attempt to measure educational impact. RESULTS: Simulation models were identified comprising of animal tissues, synthetic materials and virtual reality (VR) technology. Models were designed for instruction in repair of inguinal, umbilical, incisional and diaphragmatic hernias. Twenty-one laparoscopic hernia repair models were described. Many models demonstrated validity across several domains, and three showed transferability of skills from simulation to the operating room. Of the six open hernia repair simulation models, none were found to have demonstrated an educational impact in addition to assessing validity. CONCLUSION: Few models individually were able to demonstrate validity and educational impact. Several novel assessment tools have been developed for assessment of progress when performing simulated and real laparoscopic inguinal hernia repair. More study is required, particularly for open hernia repair, including randomized controlled trials with large sample sizes to assess the transferability of skills.

[Linear lesions: A key dermatological feature of X-linked ectodermal dysplasia in a young girl]. / Lésions linéaires : un signe dermatologique clé de la dysplasie ectodermique liée à l'X chez la fille.

INTRODUCTION: X-linked hypo/anhidrotic ectodermal dysplasia (AED) is the most common form of AED. It is manifested in boys by involvement of the adnexa, teeth and sweat glands. In girls, signs are usually minor and may include linear lesions that are poorly known since they are reported infrequently or overlooked. Herein we report 3 cases. PATIENTS AND METHODS: There were two female patients who had been followed for several years, as well as the mother of one of the patients. Both of the younger patients had early diagnosis of DEA in childhood based on severe dental abnormalities, i.e. hypodontia and conical teeth, a typical facies, and cutaneous xerosis. The mother had milder signs and the diagnosis was made at the time of her daughter's diagnosis. All 3 had hypopigmented linear skin lesions (arms, buttocks or back), associated with a decrease in hair in one of them. Genetic analysis showed the R156H missense mutation at exon 3 of the EDA gene in all 3 patients. CONCLUSION: These hypopigmentation linear lesions, sometimes with hair loss, are well known to pediatric clinicians and dermatologists concerning early diagnosis of AED in girls, especially where the other signs are mild. Early diagnosis enables appropriate therapeutic management and genetic counseling regarding future pregnancy.

Sarcoma in neurofibromatosis 2: case report and review of the literature.

Neurofibromatosis type 2 (NF2) is associated with the development of several types of benign nervous system tumours, while malignancies are rare. We report a 22-year-old man who presented with retroperitoneal and spinal high-grade sarcomas with epithelial features. Samples showed a mixed epithelioid and spindled cell content with little associated matrix and inconclusive immunochemistry. Genetic analysis of a schwannoma and matched blood samples demonstrated a constitutional de novo substitution at the splice donor site of intron 8 of the NF2 gene and aa acquired large deletion of the entire NF2 gene as a second hit, with some loss of SMARCB1. The sarcoma also showed evidence of loss of SMARCB1 and NF2 with loss of INI1 staining. Unfortunately the mass was unresectable and the patient died 6 months after diagnosis. This malignancy was most consistent with SMARCB1-deficient epithelioid malignant peripheral nerve sheath tumour, although a significant differential was proximal-type epithelial sarcoma. Each differential has previously been reported only once with NF2. This demonstrates an extremely rare potential complication of the condition.

Understanding the relationship between cell death and tissue shrinkage via a stochastic agent-based model.

Cell death, a process which can occur both naturally and in response to insult, is both a complex and diverse phenomenon. Under some circumstances, dying cells actively contract and cause their neighbors to rearrange and maintain tissue integrity. Under other circumstances, dying cells leave behind gaps, which results in tissue separation. A better understanding of how the cellular scale features of cell death manifest on the population scale has implications ranging from morphogenesis to tumor response to treatment. However, the mechanistic relationship between cell death and population scale shrinkage is not well understood, and computational methods for studying these relationships are not well established. Here we propose a mechanically robust agent-based cell model designed to capture the implications of cell death on the population scale. In our agent-based model, algorithmic rules applied on the cellular level emerge on the population scale where their effects are quantified. To better quantify model uncertainty and parameter interactions, we implement a recently developed technique for conducting a variance-based sensitivity analysis on the stochastic model. From this analysis and subsequent investigation, we find that cellular scale shrinkage has the largest influence of all model parameters tested, and that by adjusting cellular scale shrinkage population shrinkage varies widely even across simulations which contain the same fraction of dying cells. We anticipate that the methods and results presented here are a starting point for significant future investigation toward quantifying the implications of different mechanisms of cell death on population and tissue scale behavior.

Treatment efficiency and economic feasibility of biological oxidation, membrane filtration and separation processes, and advanced oxidation for the purification and valorization of olive mill wastewater.

Olive mill wastewater (OMW) is a major waste stream resulting from numerous operations that occur during the production stages of olive oil. The resulting effluent contains various organic and inorganic contaminants and its environmental impact can be notable. The present work aims at investigating the efficiency of (i) jet-loop reactor with ultrafiltration (UF) membrane system (Jacto.MBR), (ii) solar photo-Fenton oxidation after coagulation/flocculation pre-treatment and (iii) integrated membrane filtration processes (i.e. UF/nanofiltration (NF)) used for the treatment of OMW. According to the results, the efficiency of the biological treatment was high, equal to 90% COD and 80% total phenolic compounds (TPh) removal. A COD removal higher than 94% was achieved by applying the solar photo-Fenton oxidation process as post-treatment of coagulation/flocculation of OMW, while the phenolic fraction was completely eliminated. The combined UF/NF process resulted in very high conductivity and COD removal, up to 90% and 95%, respectively, while TPh were concentrated in the NF concentrate stream (i.e. 93% concentration). Quite important is the fact that the NF concentrate, a valuable and polyphenol rich stream, can be further valorized in various industries (e.g. food, pharmaceutical, etc.). The above treatment processes were found also to be able to reduce the initial OMW phytotoxicity at greenhouse experiments; with the effluent stream of solar photo-Fenton process to be the least phytotoxic compared to the other treated effluents. A SWOT (Strength, Weakness, Opportunities, Threats) analysis was performed, in order to determine both the strengths of each technology, as well as the possible obstacles that need to overcome for achieving the desired levels of treatment. Finally, an economic evaluation of the tested technologies was performed in an effort to measure the applicability and viability of these systems at real scale; highlighting that the cost cannot be regarded as a 'cut off criterion', since the most cost-effective option in not always the optimum one.

Longitudinal changes in cognition in early Parkinson's disease patients with REM sleep behavior disorder.

INTRODUCTION: Cognitive decline is common in Parkinson's disease (PD), and identifying patients at highest risk for it is essential. We aimed to examine the effect of possible REM sleep behavior disorder (pRBD) on rate of cognitive decline in early PD, for both global cognition and in specific cognitive domains. METHODS: Parkinson's Progression Markers Initiative (PPMI) is a multi-site, international study of PD patients untreated at enrollment. pRBD was assessed with the REM sleep behavior disorder questionnaire (RBDSQ). Global cognition was assessed at baseline and annually using the Montreal Cognitive Assessment (MoCA) and a cognitive battery. Linear mixed effects models were used to examine the relationship between pRBD (RBDSQ≥6) and rate of change in cognitive variables. Age, sex, years of education, and baseline motor and cognitive scores were included as covariates. RESULTS: The baseline sample consisted of 423 individuals with PD, mean age 61.7 years and 65.5% male. Data was available on 389, 366, and 196 participants at 1-year, 2-year, and 3-year follow-up respectively. Possible RBD occurred in 108 (25.5%) at baseline. In multivariate analyses, baseline RBD was associated with greater annual rate of decline in MoCA score (ß = -0.34, 95%CI -0.54, -0.13, p < 0.001), Symbol Digit Modalities Test (ß = -0.69, 95%CI -1.3, -0.09, p = 0.024), and Hopkins Verbal Learning Test-Revised, delayed free recall (ß = -0.21, 95%CI -0.41, -0.013, p = 0.037). CONCLUSIONS: Possible RBD is common in early PD and predicts future cognitive decline, particularly in attention and memory domains.

Genome-Wide Association Study in Arabidopsis thaliana of Natural Variation in Seed Oil Melting Point: A Widespread Adaptive Trait in Plants.

Seed oil melting point is an adaptive, quantitative trait determined by the relative proportions of the fatty acids that compose the oil. Micro- and macro-evolutionary evidence suggests selection has changed the melting point of seed oils to covary with germination temperatures because of a trade-off between total energy stores and the rate of energy acquisition during germination under competition. The seed oil compositions of 391 natural accessions of Arabidopsis thaliana, grown under common-garden conditions, were used to assess whether seed oil melting point within a species varied with germination temperature. In support of the adaptive explanation, long-term monthly spring and fall field temperatures of the accession collection sites significantly predicted their seed oil melting points. In addition, a genome-wide association study (GWAS) was performed to determine which genes were most likely responsible for the natural variation in seed oil melting point. The GWAS found a single highly significant association within the coding region of FAD2, which encodes a fatty acid desaturase central to the oil biosynthesis pathway. In a separate analysis of 15 a priori oil synthesis candidate genes, 2 (FAD2 and FATB) were located near significant SNPs associated with seed oil melting point. These results comport with others' molecular work showing that lines with alterations in these genes affect seed oil melting point as expected. Our results suggest natural selection has acted on a small number of loci to alter a quantitative trait in response to local environmental conditions.

Genome-Wide Association Study of Arabidopsis thaliana Identifies Determinants of Natural Variation in Seed Oil Composition.

The renewable source of highly reduced carbon provided by plant triacylglycerols (TAGs) fills an ever increasing demand for food, biodiesel, and industrial chemicals. Each of these uses requires different compositions of fatty acid proportions in seed oils. Identifying the genes responsible for variation in seed oil composition in nature provides targets for bioengineering fatty acid proportions optimized for various industrial and nutrition goals. Here, we characterized the seed oil composition of 391 world-wide, wild accessions of Arabidopsis thaliana, and performed a genome-wide association study (GWAS) of the 9 major fatty acids in the seed oil and 4 composite measures of the fatty acids. Four to 19 regions of interest were associated with the seed oil composition traits. Thirty-four of the genes in these regions are involved in lipid metabolism or transport, with 14 specific to fatty acid synthesis or breakdown. Eight of the genes encode transcription factors. We have identified genes significantly associated with variation in fatty acid proportions that can be used as a resource across the Brassicaceae. Two-thirds of the regions identified contain candidate genes that have never been implicated in lipid metabolism and represent potential new targets for bioengineering.

Emergence timing and fitness consequences of variation in seed oil composition in Arabidopsis thaliana.

Early seedling emergence can increase plant fitness under competition. Seed oil composition (the types and relative amounts of fatty acids in the oils) may play an important role in determining emergence timing and early growth rate in oilseeds. Saturated fatty acids provide more energy per carbon atom than unsaturated fatty acids but have substantially higher melting points (when chain length is held constant). This characteristic forms the basis of an adaptive hypothesis that lower melting point seeds (lower proportion of saturated fatty acids) should be favored under colder germination temperatures due to earlier germination and faster growth before photosynthesis, while at warmer germination temperatures, seeds with a higher amount of energy (higher proportion of saturated fatty acids) should be favored. To assess the effects of seed oil melting point on timing of seedling emergence and fitness, high- and low-melting point lines from a recombinant inbred cross of Arabidopsis thaliana were competed in a fully factorial experiment at warm and cold temperatures with two different density treatments. Emergence timing between these lines was not significantly different at either temperature, which aligned with warm temperature predictions, but not cold temperature predictions. Under all conditions, plants competing against high-melting point lines had lower fitness relative to those against low-melting point lines, which matched expectations for undifferentiated emergence times.

Intramuscular distribution of botulinum toxin--visualized by MRI.

OBJECTIVE: A precise knowledge of the spread of botulinum toxin (BoNT) in muscle tissue is required to efficiently access endplate zones and increase BoNT's therapeutic efficacy. Here, we aimed to understand the spatiotemporal dynamics of BoNT distribution in skeletal muscle and its modulating factors, such as injected volume and exercise after injection. METHODS: To visualize distribution in muscle tissue, sagittal, dynamic, balanced fast field echo (BFFE) MRI imaging was performed during injection of 1 ml BoNT/NaCl bolus in spastic biceps brachii muscles (SBB, n=4), and 1 ml NaCl in the right and 2 ml NaCl in the left healthy biceps brachii (HBB, n=6), with or without successive muscle exercise. The pattern of extracellular fluid distribution was evaluated by T2-weighted and diffusion tensor imaging (DTI) sequences. RESULTS: BFFE indicated an immediate increase in hyperintensity, parallel to the muscle fibers, in the shape of a long (5.3±1.7 cm) and thin (0.52±1.3 cm) layer in HBB. The layer in SBB was shorter (3.25±0.6 cm, p=0.01) and tended to be thicker (0.74±2.9 cm, p=0.27). In HBB, an increase in volume (2 ml) resulted in an increase in thickness (0.95±0.2 cm, p=0.015), but a consistent length (5.67±1.3 cm, p=0.54). DTI visualized a change of diffusion, which exceeded the bolus region by approximately 0.5 cm. Redistribution occurred 10 min after injection and was more prominent in HBB, compared to SBB. Additional muscle activity did not alter the diffusion pattern or bolus distribution. CONCLUSION: Injecting BoNT at different depths perpendicular to the direction of the muscle fiber might optimize the efficacy of BoNT treatment. Additional sites along muscle fibers should be considered in SBB.

Association mapping of germination traits in Arabidopsis thaliana under light and nutrient treatments: searching for G×E effects.

In the natural world, genotype expression is influenced by an organism's environment. Identifying and understanding the genes underlying phenotypes in different environments is important for making advances in fields ranging from evolution to medicine to agriculture. With the availability of genome-wide genetic-marker datasets, it is possible to look for genes that interact with the environment. Using the model organism, Arabidopsis thaliana, we looked for genes underlying phenotypes as well as genotype-by-environment interactions in four germination traits under two light and two nutrient conditions. We then performed genome-wide association tests to identify candidate genes underlying the observed phenotypes and genotype-by-environment interactions. Of the four germination traits examined, only two showed significant genotype-by-environment interactions. While genome-wide association analyses did not identify any markers or genes explicitly linked to genotype-by-environment interactions, we did identify a total of 55 markers and 71 genes associated with germination differences. Of the 71 genes, four--ZIGA4, PS1, TOR, and TT12--appear to be strong candidates for further study of germination variation under different environments.

Toward a consensus in protein structure nomenclature.

In a recent article, published in Intrinsically Disordered Proteins, a valuable consensus view regarding the nomenclature for disordered proteins was presented.1 In this work the authors present a thoughtful and systemic review of terms that have been used in the literature to describe proteins that sample a heterogeneous set of structures during their biological lifetime. We agree that the term "intrinsically disordered proteins" (IDPs) is an appropriate single descriptor to refer to this particular class of proteins, although it does not fully capture much of the nuanced complexities that are inherent to this class. In what follows we suggest a refinement to this nomenclature based on an analysis of the underlying ensemble that describes the thermally accessible states of a given IDP.

New point mutation in Golga3 causes multiple defects in spermatogenesis.

Mice with repro27 exhibit fully penetrant male-specific infertility associated with a nonsense mutation in the golgin subfamily A member 3 gene (Golga3). GOLGA3 is a Golgi complex-associated protein implicated in protein trafficking, apoptosis, positioning of the Golgi and spermatogenesis. In repro27 mutant mice, a point mutation in exon 18 of the Golga3 gene that inserts a pre-mature termination codon leads to an absence of GOLGA3 protein expression. GOLGA3 protein was undetectable in the brain, heart and liver in both mutant and control mice. Although spermatogenesis in Golga3(repro27) mutant mice appears to initiate normally, development is disrupted in late meiosis during the first wave of spermatogenesis, leading to significant germ cell loss between 15 and 18 days post-partum (dpp). Terminal Deoxynucleotidyl Transferase dUTP-mediated Nick End Labeling analysis showed elevated DNA fragmentation in meiotic germ cells by 12 dpp, suggesting apoptosis as a mechanism of germ cell loss. The few surviving post-meiotic round spermatids exhibited abnormal spermiogenesis with defects in acrosome formation, head and tail development and extensive vacuolization in the seminiferous epithelium. Analysis of epididymal spermatozoa showed significantly low sperm concentration and motility and in vitro fertilization with mutant spermatozoa was unsuccessful. Golga3(repro27) mice lack GOLGA3 protein and thus provide an in vivo tool to aid in deciphering the role of GOLGA3 in Golgi complex positioning, cargo trafficking and apoptosis signalling in male germ cells.

Fusion of bolaamphiphile micelles: a method to prepare stable supported biomimetic membranes.

Supported biomimetic membranes (SBMs) on solid substrates have been commonly prepared from vesicle-forming double-tail lipids, such as zwitterionic phospholipids, using the method of vesicle fusion. Here we report on the preparation of SBMs on silica surfaces via a similar process of "micelle fusion" from a cationic single-tail bolaamphiphile GLH-20 that forms spherical and elongated thread-like micelles in solution. We demonstrate that, in contrast to zwitterionic phospholipids, GLH-20 self-assembles into a stable contiguous SBM at both low and high ionic strengths. The cationic charge of GLH-20 promotes the formation of a stable SBM through enhanced double-layer interactions with the negatively charged silica surface. It is also shown that spinach aquaporin PM-28 was successfully incorporated within bolaamphiphile SBM in a manner similar to SBMs prepared by vesicle/proteoliposome fusion; thereby the inherent curvature of the micelle surface does not inhibit protein reconstitution. The results suggest that SBMs based on charged bolaamphiphiles might be an attractive platform for applications such as water purification and biosensors, where the stability and low defect rate of SBMs in diverse conditions are crucial for achieving desired performance.

DACTAL: divide-and-conquer trees (almost) without alignments.

MOTIVATION: While phylogenetic analyses of datasets containing 1000-5000 sequences are challenging for existing methods, the estimation of substantially larger phylogenies poses a problem of much greater complexity and scale. METHODS: We present DACTAL, a method for phylogeny estimation that produces trees from unaligned sequence datasets without ever needing to estimate an alignment on the entire dataset. DACTAL combines iteration with a novel divide-and-conquer approach, so that each iteration begins with a tree produced in the prior iteration, decomposes the taxon set into overlapping subsets, estimates trees on each subset, and then combines the smaller trees into a tree on the full taxon set using a new supertree method. We prove that DACTAL is guaranteed to produce the true tree under certain conditions. We compare DACTAL to SATé and maximum likelihood trees on estimated alignments using simulated and real datasets with 1000-27 643 taxa. RESULTS: Our studies show that on average DACTAL yields more accurate trees than the two-phase methods we studied on very large datasets that are difficult to align, and has approximately the same accuracy on the easier datasets. The comparison to SATé shows that both have the same accuracy, but that DACTAL achieves this accuracy in a fraction of the time. Furthermore, DACTAL can analyze larger datasets than SATé, including a dataset with almost 28 000 sequences. AVAILABILITY: DACTAL source code and results of dataset analyses are available at www.cs.utexas.edu/users/phylo/software/dactal.

SuperFine: fast and accurate supertree estimation.

Many research groups are estimating trees containing anywhere from a few thousands to hundreds of thousands of species, toward the eventual goal of the estimation of a Tree of Life, containing perhaps as many as several million leaves. These phylogenetic estimations present enormous computational challenges, and current computational methods are likely to fail to run even on data sets in the low end of this range. One approach to estimate a large species tree is to use phylogenetic estimation methods (such as maximum likelihood) on a supermatrix produced by concatenating multiple sequence alignments for a collection of markers; however, the most accurate of these phylogenetic estimation methods are extremely computationally intensive for data sets with more than a few thousand sequences. Supertree methods, which assemble phylogenetic trees from a collection of trees on subsets of the taxa, are important tools for phylogeny estimation where phylogenetic analyses based upon maximum likelihood (ML) are infeasible. In this paper, we introduce SuperFine, a meta-method that utilizes a novel two-step procedure in order to improve the accuracy and scalability of supertree methods. Our study, using both simulated and empirical data, shows that SuperFine-boosted supertree methods produce more accurate trees than standard supertree methods, and run quickly on very large data sets with thousands of sequences. Furthermore, SuperFine-boosted matrix representation with parsimony (MRP, the most well-known supertree method) approaches the accuracy of ML methods on supermatrix data sets under realistic conditions.

Quantitative trait loci involved in regulating seed oil composition in Arabidopsis thaliana and their evolutionary implications.

Fatty acid composition is an important determinant of seed oil quality. Overall, 72 QTL for 12 fatty acid traits that control seed oil composition were identified in four recombinant inbred line (RIL) populations (Ler-0 × Sha, Ler-0 × Col-4, Ler-2 × Cvi, Ler-0 × No-0) of Arabidopsis thaliana. The identified QTL explained 3.2-79.8% of the phenotypic variance; 33 of the 59 QTL identified in the Ler-0 × Sha and the Ler-0 × Col RIL populations co-located with several a priori candidate genes for seed oil composition. QTL for fatty acids 18:1, 18:2, 22:1, and fatty acids synthesized in plastids was identified in both Ler-0 × Sha and Ler-0 × Col-4 RIL populations, and QTL for 16:0 was identified in the Ler-0 × Sha and Ler-0 × No-0 RIL populations providing strong support for the importance of these QTL in determining seed oil composition. We identified melting point QTL in three RIL populations, and fatty acid QTL collocated with two of them, suggesting that the loci could be under selection for altering the melting point of seed oils to enhance adaptation and could be useful for breeding purposes. Nuclear-cytoplasmic interactions and epistasis were rare. Analysis of the genetic correlations between these loci and other fatty acids indicated that these correlations would tend to strongly enhance selection for desirable fatty acids.

SATe-II: very fast and accurate simultaneous estimation of multiple sequence alignments and phylogenetic trees.

Highly accurate estimation of phylogenetic trees for large data sets is difficult, in part because multiple sequence alignments must be accurate for phylogeny estimation methods to be accurate. Coestimation of alignments and trees has been attempted but currently only SATé estimates reasonably accurate trees and alignments for large data sets in practical time frames (Liu K., Raghavan S., Nelesen S., Linder C.R., Warnow T. 2009b. Rapid and accurate large-scale coestimation of sequence alignments and phylogenetic trees. Science. 324:1561-1564). Here, we present a modification to the original SATé algorithm that improves upon SATé (which we now call SATé-I) in terms of speed and of phylogenetic and alignment accuracy. SATé-II uses a different divide-and-conquer strategy than SATé-I and so produces smaller more closely related subsets than SATé-I; as a result, SATé-II produces more accurate alignments and trees, can analyze larger data sets, and runs more efficiently than SATé-I. Generally, SATé is a metamethod that takes an existing multiple sequence alignment method as an input parameter and boosts the quality of that alignment method. SATé-II-boosted alignment methods are significantly more accurate than their unboosted versions, and trees based upon these improved alignments are more accurate than trees based upon the original alignments. Because SATé-I used maximum likelihood (ML) methods that treat gaps as missing data to estimate trees and because we found a correlation between the quality of tree/alignment pairs and ML scores, we explored the degree to which SATé's performance depends on using ML with gaps treated as missing data to determine the best tree/alignment pair. We present two lines of evidence that using ML with gaps treated as missing data to optimize the alignment and tree produces very poor results. First, we show that the optimization problem where a set of unaligned DNA sequences is given and the output is the tree and alignment of those sequences that maximize likelihood under the Jukes-Cantor model is uninformative in the worst possible sense. For all inputs, all trees optimize the likelihood score. Second, we show that a greedy heuristic that uses GTR+Gamma ML to optimize the alignment and the tree can produce very poor alignments and trees. Therefore, the excellent performance of SATé-II and SATé-I is not because ML is used as an optimization criterion for choosing the best tree/alignment pair but rather due to the particular divide-and-conquer realignment techniques employed.