Codon bias among synonymous rare variants is associated with Alzheimer's disease imaging biomarker

Alzheimer's disease (AD) is a neurodegenerative disorder with few biomarkers even though it impacts a relatively large portion of the population and is predicted to affect significantly more individuals in the future. Neuroimaging has been used in concert with genetic information to improve our understanding in relation to how AD arises and how it can be potentially diagnosed. Additionally, evidence suggests synonymous variants can have a functional impact on gene regulatory mechanisms, including those related to AD. Some synonymous codons are preferred over others leading to a codon bias. The bias can arise with respect to codons that are more or less frequently used in the genome. A bias can also result from optimal and non-optimal codons, which have stronger and weaker codon anti-codon interactions, respectively. Although association tests have been utilized before to identify genes associated with AD, it remains unclear how codon bias plays a role and if it can improve rare variant analysis. In this work, rare variants from whole-genome sequencing from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort were binned into genes using BioBin. An association analysis of the genes with AD-related neuroimaging biomarker was performed using SKAT-O. While using all synonymous variants we did not identify any genomewide significant associations, using only synonymous variants that affected codon frequency we identified several genes as significantly associated with the imaging phenotype. Additionally, significant associations were found using only rare variants that contains an optimal codon in among minor alleles and a non-optimal codon in the major allele. These results suggest that codon bias may play a role in AD and that it can be used to improve detection power in rare variant association analysis

Mikrosfere ropinirol hidroklorida za polagano oslobađanje: Utjecaj procesnih parametara

An emulsion solvent evaporation method was employed to prepare microspheres of ropinirole hydrochloride, a highly water soluble drug, by using ethylcellulose and PEG with the help of 32 full factorial design. The microspheres were made by incorporating the drug in a polar organic solvent, which was emulsified using liquid paraffin as an external oil phase. Effects of various process parameters such as viscosity of the external phase, selection of the internal phase, surfactant selection and selection of stirring speed were studied. Microspheres were evaluated for product yield, encapsulation efficiency and particle size. Various drug/ethylcellulose ratios and PEG concentrations were assayed. In vitro dissolution profiles showed that ethylcellulose microspheres were able to control release of the drug for a period of 12 h.Mikrosfere ropinirol hidroklorida, ljekovite tvari vrlo dobro topljive u vodi, pripravljene su metodom isparavanja otapala, koristeći etilcelulozu i PEG te 32 potpuno faktorijalno dizajniranje. Mikrosfere su pripravljene na sljedeći način: otopina ljekovite tvari u polarnom organskom otapalu emulgirana je s tekućim parafinom kao vanjskom uljnom fazom. Ispitivan je utjecaj različitih procesnih parametara poput viskoznosti vanjske faze, vrste interne faze i površinski aktivne tvari te brzine miješanja. Za pripravljene mikrosfere određeno je iskorištenje, učinkovitost inkapsuliranja i veličina čestica. Isprobavani su različiti odnosi ljekovite tvari i etilceluloze te koncentracija PEG-a. In vitro pokusi su pokazali da je oslobađanje ljekovite tvari kontrolirano tijekom 12 h

Early Disease Detection Through Nail Image Processing Based on Ensemble of Classifier Models

Medical science has progressed in many ways and different methods have been developed for the diagnosis of diseases in the human body and one of the ways to identify the diseases is through the close examination of nails of the human palm. The main aim of this study is to compare the performance of various classifier models that are used for the prediction of various diseases. The Performance analysis is done by applying image processing, different data mining and machine learning techniques to the extracted nail image through our proposed system which does nail analysis using a combination of 13 features (Nail Color, Shape and Texture) extracted from the nail image. In this paper we have compared different machine learning classifiers like Support Vector Machine, Multiclass SVM and K-Nearest Neighbor through ensemble of these classifiers with different features so as to classify patients with different diseases like Psoriasis, Red Lunula, Beau�s Lines, Clubbing, etc. These approaches were tested with data images from Hospitals and workplaces. The performance of the different classifiers have been measured in terms of Accuracy, Sensitivity and Specificity

Extended Hauser-Feshbach Method for Statistical Binary-Decay of Light-Mass Systems

An Extended Hauser-Feshbach Method (EHFM) is developed for light heavy-ion fusion reactions in order to provide a detailed analysis of all the possible decay channels by including explicitly the fusion-fission phase-space in the description of the cascade chain. The mass-asymmetric fission component is considered as a complex-fragment binary-decay which can be treated in the same way as the light-particle evaporation from the compound nucleus in statistical-model calculations. The method of the phase-space integrations for the binary-decay is an extension of the usual Hauser-Feshbach formalism to be applied to the mass-symmetric fission part. The EHFM calculations include ground-state binding energies and discrete levels in the low excitation-energy regions which are essential for an accurate evaluation of the phase-space integrations of the complex-fragment emission (fission). In the present calculations, EHFM is applied to the first-chance binary-decay by assuming that the second-chance fission decay is negligible. In a similar manner to the description of the fusion-evaporation process, the usual cascade calculation of light-particle emission from the highly excited complex fragments is applied. This complete calculation is then defined as EHFM+CASCADE. Calculated quantities such as charge-, mass- and kinetic-energy distributions are compared with inclusive and/or exclusive data for the $^{32}$S+$^{24}$Mg and $^{35}$Cl+$^{12}$C reactions which have been selected as typical examples. Finally, the missing charge distributions extracted from exclusive measurements are also successfully compared with the EHFM+CASCADE predictions.Comment: 34 pages, 6 Figures available upon request, Phys. Rev. C (to be published

A Hybrid Bacterial Swarming Methodology for Job Shop Scheduling Environment

Optimized utilization of resources is the need of the hour in any manufacturing system. A properly planned schedule is often required to facilitate optimization. This makes scheduling a significant phase in any manufacturing scenario. The Job Shop Scheduling Problem is an operation sequencing problem on multiple machines with some operation and machine precedence constraints, aimed to find the best sequence of operations on each machine in order to optimize a set of objectives. Bacterial Foraging algorithm is a relatively new biologically inspired optimization technique proposed based on the foraging behaviour of E.coli bacteria. Harmony Search is a phenomenon mimicking algorithm devised by the improvisation process of musicians. In this research paper, Harmony Search is hybridized with bacterial foraging to improve its scheduling strategies. A proposed Harmony Bacterial Swarming Algorithm is developed and tested with benchmark Job Shop instances. Computational results have clearly shown the competence of our method in obtaining the best schedule

Opening the black box of energy modelling: Strategies and lessons learned

The global energy system is undergoing a major transition, and in energy planning and decision-making across governments, industry and academia, models play a crucial role. Because of their policy relevance and contested nature, the transparency and open availability of energy models and data are of particular importance. Here we provide a practical how-to guide based on the collective experience of members of the Open Energy Modelling Initiative (Openmod). We discuss key steps to consider when opening code and data, including determining intellectual property ownership, choosing a licence and appropriate modelling languages, distributing code and data, and providing support and building communities. After illustrating these decisions with examples and lessons learned from the community, we conclude that even though individual researchers' choices are important, institutional changes are still also necessary for more openness and transparency in energy research

Fuzzy Knowledge Based System for Suitability of Soils in Airfield Applications

Proper design of roads and airfield pavements requires an in-depth soil properties evaluation to determine suitability of soil. Soft computing is used to model soil classification system's dynamic behaviour and its properties. Soft computing is based on methods of machine learning, fuzzy logic and artificial neural networks, expert systems, genetic algorithms. Fuzzy system is a strong method for mimicking human thought and solves question of confusion. This paper proposes a new decision-making approach for soil suitability in airfield applications without a need to perform any manual works like use of tables or chart. A fuzzy knowledge - based approach is built to rate soil suitability in qualitative terms for airfield application. The proposed model describes a new technique by defining fuzzy descriptors using triangular functions considering the index properties of soils as input parameters and fuzzy rules are generated using fuzzy operators to classify soil and rate its suitability for airfield applications. The data obtained from the results of the laboratory test are validated with the results of the fuzzy knowledge-based system indicating the applicability of the Fuzzy model created. The approach developed in this work is more skilled to other prevailing optimization models. Due to its system’s flexibility, it can be suitably customized and applied to laboratory test data available, thus delivering a wide range for any geotechnical engineer. Doi: 10.28991/cej-2021-03091643 Full Text: PD

Nail lacquer films’ surface energies and in vitro water-resistance and adhesion do not predict their in vivo residence

The in vivo residence of nail lacquers (which are ideal topical drug carriers for the treatment of nail diseases) determines their frequency of application, and is thereby expected to influence patient adherence and success of treatment. Thus in vitro measurements to indicate lacquers’ in vivo residence are routinely conducted during formulation development. However the literature on in vitro-in vivo correlations is severely limited. Thus, the aim of the work discussed in this paper was to investigate correlations between in vivo residence and in vitro film resistance to water, in vitro film adhesion and surface energy of lacquer films. In vivo measurements were conducted on fingernails in six volunteers. Seven commercially available nail lacquers were tested in commonly-used measurements. Correlations between in vivo residence and in vitro water resistance and adhesion were found to be extremely poor. The surface energies of the lacquer films (which were between 33 and 39 mJ/m2) were also not predictive of in vivo residence. High density polyethylene (HDPE) sheet – whose surface energy was determined to be similar to that of the human nailplate – was found to be a suitable model for the nailplate (when investigating surface energy) and was used in a number of experiments

A study on patients treated with interlock nailing in the forearm fracture bones

Background: Fractures involving the bones of the forearm present unique problems not encountered with fractures of other long bones and may significantly affect the function of the upper limb. The purpose of the present study was to evaluate the functional outcome of patients treated with interlock nailing in the fracture forearm bones.Methods: Thirty two patients included after their consent. With the patient supine on a radiolucent table, and under general or regional anesthesia the extremity was prepared and the surgery was performed using a standard procedure. If secure rigid fixation is achieved forearm POP splint is applied and kept in place for 2 weeks, thereafter a removable sugar-tong orthosis is worn until bridging callus is present, and the orthosis is removed frequently for exercise.Results: The average age of the patients was 38.90 years. The major mode of injury was RTA (59.09%) followed by assault (36.36%). 41% of patients were operated within week of injury, only three patients were operated after a week and one patient after 3 weeks. More than half of patients had closed fractures and rest was open fractures, of which Gustilo Anderson type II were in majority. In 3/5 of patients locking at nondriving end was not done cause of stable fixation. There was statistically significant difference in the surgical time (P <0.05) and duration of postoperative immobilization differed statistically significantly (P <0.001) between the group of patients in whom locking was done and not done. Conclusions: Advantages of Interlocking nail are high rate of bony consolidation along with minimized surgical approaches, cosmetically better suited and little risk of refracture after removal of the implant