Mouse Stbd1 is N-myristoylated and affects ER-mitochondria association and mitochondrial morphology

Starch binding domain-containing protein 1 (Stbd1) is a carbohydrate-binding protein that has been proposed to be a selective autophagy receptor for glycogen. Here, we show that mouse Stbd1 is a transmembrane endoplasmic reticulum (ER)-resident protein with the capacity to induce the formation of organized ER structures in HeLa cells. In addition to bulk ER, Stbd1 was found to localize to mitochondria-associated membranes (MAMs), which represent regions of close apposition between the ER and mitochondria. We demonstrate that N-myristoylation and binding of Stbd1 to glycogen act as major determinants of its subcellular targeting. Moreover, overexpression of non-myristoylated Stbd1 enhanced the association between ER and mitochondria, and further induced prominent mitochondrial fragmentation and clustering. Conversely, shRNA-mediated Stbd1 silencing resulted in an increase in the spacing between ER and mitochondria, and an altered morphology of the mitochondrial network, suggesting elevated fusion and interconnectivity of mitochondria. Our data unravel the molecular mechanism underlying Stbd1 subcellular targeting, support and expand its proposed function as a selective autophagy receptor for glycogen and uncover a new role for the protein in the physical association between ER and mitochondria

Spatial immune profiling of the colorectal tumor microenvironment predicts good outcome in stage II patients

This study was funded by Medical Research Scotland and Indica Labs, Inc., who also provided in-kind resource.Cellular subpopulations within the colorectal tumor microenvironment (TME) include CD3+ and CD8+ lymphocytes, CD68+ and CD163+ macrophages, and tumor buds (TBs), all of which have known prognostic significance in stage II colorectal cancer. However, the prognostic relevance of their spatial interactions remains unknown. Here, by applying automated image analysis and machine learning approaches, we evaluate the prognostic significance of these cellular subpopulations and their spatial interactions. Resultant data, from a training cohort retrospectively collated from Edinburgh, UK hospitals (n = 113), were used to create a combinatorial prognostic model, which identified a subpopulation of patients who exhibit 100% survival over a 5-year follow-up period. The combinatorial model integrated lymphocytic infiltration, the number of lymphocytes within 50-μm proximity to TBs, and the CD68+/CD163+ macrophage ratio. This finding was confirmed on an independent validation cohort, which included patients treated in Japan and Scotland (n = 117). This work shows that by analyzing multiple cellular subpopulations from the complex TME, it is possible to identify patients for whom surgical resection alone may be curative.Publisher PDFPeer reviewe

Intrinsic flexibility of the EMT zeolite framework under pressure

The roles of organic additives in the assembly and crystallisation of zeolites are still not fully understood. This is important when attempting to prepare novel frameworks to produce new zeolites. We consider 18-crown-6 ether (18C6) as an additive, which has previously been shown to differentiate between the zeolite EMC-2 (EMT) and faujasite (FAU) frameworks. However, it is unclear whether this distinction is dictated by influences on the metastable free-energy landscape or geometric templating. Using high-pressure synchrotron X-ray diffraction, we have observed that the presence of 18C6 does not impact the EMT framework flexibility—agreeing with our previous geometric simulations and suggesting that 18C6 does not behave as a geometric template. This was further studied by computational modelling using solid-state density-functional theory and lattice dynamics calculations. It is shown that the lattice energy of FAU is lower than EMT, but is strongly impacted by the presence of solvent/guest molecules in the framework. Furthermore, the EMT topology possesses a greater vibrational entropy and is stabilised by free energy at a finite temperature. Overall, these findings demonstrate that the role of the 18C6 additive is to influence the free energy of crystallisation to assemble the EMT framework as opposed to FAU

Hybrid Genetic Bees Algorithm applied to Single Machine Scheduling with Earliness and Tardiness Penalties

This paper presents a hybrid Genetic-Bees Algorithm based optimised solution for the single machine scheduling problem. The enhancement of the Bees Algorithm (BA) is conducted using the Genetic Algorithm's (GA's) operators during the global search stage. The proposed enhancement aims to increase the global search capability of the BA gradually with new additions. Although the BA has very successful implementations on various type of optimisation problems, it has found that the algorithm suffers from weak global search ability which increases the computational complexities on NP-hard type optimisation problems e.g. combinatorial/permutational type optimisation problems. This weakness occurs due to using a simple global random search operation during the search process. To reinforce the global search process in the BA, the proposed enhancement is utilised to increase exploration capability by expanding the number of fittest solutions through the genetical variations of promising solutions. The hybridisation process is realised by including two strategies into the basic BA, named as â\u80\u9creinforced global searchâ\u80\u9d and â\u80\u9cjumping functionâ\u80\u9d strategies. The reinforced global search strategy is the first stage of the hybridisation process and contains the mutation operator of the GA. The second strategy, jumping function strategy, consists of four GA operators as single point crossover, multipoint crossover, mutation and randomisation. To demonstrate the strength of the proposed solution, several experiments were carried out on 280 well-known single machine benchmark instances, and the results are presented by comparing to other well-known heuristic algorithms. According to the experiments, the proposed enhancements provides better capability to basic BA to jump from local minima, and GBA performed better compared to BA in terms of convergence and the quality of results. The convergence time reduced about 60% with about 30% better results for highly constrained jobs

A review on assembly sequence planning and assembly line balancing optimisation using soft computing approaches

Assembly optimisation activities occur across development and production stages of manufacturing goods. Assembly Sequence Planning (ASP) and Assembly Line Balancing (ALB) problems are among the assembly optimisation. Both of these activities are classified as NP-hard. Several soft computing approaches using different techniques have been developed to solve ASP and ALB. Although these approaches do not guarantee the optimum solution, they have been successfully applied in many ASP and ALB optimisation works. This paper reported the survey on research in ASP and ALB that use soft computing approaches for the past 10years. To be more specific, only Simple Assembly Line Balancing Problem (SALBP) is considered for ALB. The survey shows that three soft computing algorithms that frequently used to solve ASP and ALB are Genetic Algorithm, Ant Colony Optimisation and Particle Swarm Optimisation. Meanwhile, the research in ASP and ALB is also progressing to the next level by integration of assembly optimisation activities across product development stages

A short, 8-week course of imiquimod 5% cream versus podophyllotoxin in the treatment of anogenital warts: A retrospective comparative cohort study

Background: Studies comparing head-to-head treatment modalities for anogenital warts are lacking. Aim: We sought to compare a short, 8-week course of imiquimod 5% cream to versus the standard 4 week course of podophyllotoxin in the treatment of anogenital warts and to assess factors that may affect response to treatment. Methods: This was a retrospective cohort study. We reviewed medical files of otherwise healthy patients with a first episode of anogenital warts who were treated with either a short, 8-week course of imiquimod or the standard 4-week course of podophyllotoxin. Inverse probability of treatment weighted (IPTW). Logistic regression was employed to evaluate factors that may affect response to therapy. Results: The study included 347 patients. In patients with lesions on dry, keratinized anatomical sites, the complete clearance rates were 7.6% for imiquimod and 27.9% for podophyllotoxin (P < 0.001). In patients with lesions on moist, partially keratinized sites, no difference between the treatments was revealed. Significant predictors of > 50% reduction in wart area were location of lesions [odds ratio (OR) (95% confidence interval (CI)): 3.6 (1.84-7.08), P = 0.0002] for “partially keratinized” versus “keratinized” sites and treatment used [OR (95% CI): 1.79 (1.08-2.97), P = 0.024] for podophyllotoxin versus imiquimod. Limitations: The retrospective design of the study was a limitation that we mitigated against with the use of IPTW logistic regression. Conclusion: A standard 4 week course of Podophyllotoxin was more effective than an 8-week course of imiquimod only for lesions on keratinized sites. Treatment with podophyllotoxin and location of lesions on partially keratinized sites were independent predictors of >50% reduction in wart area