Purification and characterization of pre-mRNA splicing factor SF2 from HeLa cells

SF2, an activity necessary for 5' splice site cleavage and lariat formation during pre-mRNA splicing in vitro, has been purified to near homogeneity from HeLa cells. The purest fraction contains only two related polypeptides of 33 kD. This fraction is sufficient to complement an S100 fraction, which contains the remaining splicing factors, to splice several pre-mRNAs. The optimal amount of SF2 required for efficient splicing depends on the pre-mRNA substrate. SF2 is distinct from the hnRNP A1 and U1 snRNP a polypeptides, which are similar in size. Endogenous hnRNA copurifies with SF2, but this activity does not appear to have an essential RNA component. SF2 appear to be necessary for the assembly or stabilization of the earliest specific prespliceosome complex, although in the absence of other components, it can bind RNA in a nonspecific manner. SF2 copurifies with an activity that promotes the annealing of complementary RNAs. Thus, SF2 may promote specific RNA-RNA interactions between snRNAs and pre-mRNA, between complementary snRNA regions, and/or involving intramolecular pre-mRNA helices. Other purified proteins with RNA annealing activity cannot substitute for SF2 in the splicing reaction

Reliability Testing of Statistical Process Control Procedures for Manufacturing with Multiple Sources of Variation

Quality inconsistencies can be caused by processes with multiple sources of variation. Therefore, the development of control charts that perform properly for both producer's and consumer's risk can be very complex. This is particularly true for real-time SPC systems that collect a great deal of data through noncontact sensing. In this paper, we demonstrate the use of a Monte Carlo simulation procedure that can be used to test SPC charts for both consumer's and producer's risk, and an experimental design procedure to analyze the results. This procedure is shown to be especially useful where design factors interact to cause high variation in a quality characteristic of a product. The approach is illustrated for a practical problem taken from the lumber manufacturing industry and demonstrates that commonly used industrial practices to control product dimensions lead to erroneous conclusions. To that end, a new mathematical approach that yields the correct results is described. The Simulation / ANOVA procedure described in this paper may have applicability in the control of many other industrial processes

SPC Methods for Detecting Simple Sawing Defects Using Real-Time Laser Range Sensor Data

Effective statistical process control (SPC) procedures can greatly enhance product value and yield in the lumber industry, ensuring accuracy and minimum waste. To this end, many mills are implementing automated real-time SPC with non-contact laser range sensors (LRS). These systems have, thus far, had only limited success because of frequent false alarms and have led to tolerances being set excessively wide and real problems being missed. Current SPC algorithms are based on manual sampling methods and, consequently, are not appropriate for the volume of data generated by real-time systems. The objective of this research was to establish a system for real-time LRS size control data for automated lumber manufacturing. An SPC system was developed that incorporated multi-sensor data, and new SPC charts were developed that went beyond traditional size control methods, simultaneously monitoring multiple surfaces and specifically targeting common sawing defects. In this paper, eleven candidate control charts were evaluated. Traditional X-bar and range charts are suggested, which were explicitly developed to take into account the components of variance in the model. Applying these methods will lead to process improvements for sawmills using automated quality control systems, so that machines producing defective material can be identified and prompt repairs made

Statistical Considerations for Real-Time Size Control Systems in Wood Products Manufacturing

Currently, sawmill machinery companies are developing real-time size lumber size control systems using non-contact laser measuring systems. These systems rely on the application of industrial statistics to large quantities of lumber thickness and width data. Because of the sampling intensity and frequent decision making in real-time systems, there is an increased chance of committing Type I or Type II errors when drawing conclusions if statistical methods are incorrectly applied. There is confusion in the industry concerning the appropriate statistical model to use for lumber size control. This survey of the current literature discusses three distinct methods for calculating and partitioning sawing variation, and thereby calculating control limits for control charts. This paper reviews the statistical foundation and current understanding of industrial statistics for implementing real-time SPC systems and makes recommendations for improvement

Human Resource Needs and Demand for Post-Secondary Education in the Canadian Secondary Wood Products Industry

Skilled labor shortages in manufacturing industries are being reported in a number of countries. The extent to which such shortages are affecting Canadian wood manufacturing industries is not known. The aim of this study was to survey the skills and educational needs of Canadian wood manufacturing industries, the status, capacity, and challenges that post-secondary education institutes face in meeting industries' human resource needs, and finally the attractiveness of the industry to high school job-seekers. The majority (83%) of wood manufacturing companies in Canada are experiencing problems in hiring skilled tradespeople, and 54.5% of the companies face difficulties in hiring and retaining professionals and supervisory personnel. Skilled staff shortages and competitive pressures were nominated by companies as the two most important factors restricting their growth. The skills needs of companies have changed over the last 10 years, and companies now place a much higher premium on leadership and communication skills from management, and attitude and advanced technical skills from tradespeople. Most companies offered some kind of in-house training to redress skills gaps, but less than half were likely to use the Internet to deliver in-house training. The majority of high school students were not interested in pursuing a career in the wood manufacturing industry because of its association with unsustainable forestry practices and manual labor, and the availability of more attractive career options. Lack of student interest in wood manufacturing is affecting the institutions offering relevant vocational and professional training, and nine of the thirteen institutes suffer from under-enrollment in their wood manufacturing programs. Comprehensive strategies are required to address the labor market imbalances currently affecting Canada's wood manufacturing industries

Development of a Mobile App for Self-Care Against COVID-19 Using the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) Model: Methodological Study

Background: Mobile apps have been shown to play an important role in the management, care, and prevention of infectious diseases. Thus, skills for self-care—one of the most effective ways to prevent illness—can be improved through mobile health apps. Objective: This study aimed to design, develop, and evaluate an educational mobile-based self-care app in order to help the self-prevention of COVID-19 in underdeveloped countries. We intended the app to be easy to use, quick, and inexpensive. Methods: In 2020 and 2021, we conducted a methodological study. Using the ADDIE (analysis, design, development, implementation, and evaluation) educational model, we developed a self-care management mobile app. According to the ADDIE model, an effective training and performance support tool is built through the 5 phases that comprise its name. There were 27 participants who conducted 2 evaluations of the mobile app’s usability and impact using the mobile health app usability and self-care inventory scales. The study design included pre- and posttesting. Results: An Android app called MyShield was developed. The results of pre- and posttests showed that on a scale from 0 to 5, MyShield scored a performance average of 4.17 in the physical health dimension and an average of 3.88 in the mental well-being dimension, thereby showing positive effects on self-care skills. MyShield scored highly on the “interface and satisfaction,” “ease of use,” and “usefulness” components. Conclusions: MyShield facilitates learning self-care skills at home, even during quarantine, increasing acquisition of information. Given its low development cost and the ADDIE educational design on which it is based, the app can be helpful in underdeveloped countries. Thus, low-income countries—often lacking other tools—can use the app as an effective tool for fighting COVID-19, if it becomes a standard mobile app recommended by the government

The +4G Site in Kozak Consensus Is Not Related to the Efficiency of Translation Initiation

The optimal context for translation initiation in mammalian species is GCCRCCaugG (where R = purine and “aug” is the initiation codon), with the -3R and +4G being particularly important. The presence of +4G has been interpreted as necessary for efficient translation initiation. Accumulated experimental and bioinformatic evidence has suggested an alternative explanation based on amino acid constraint on the second codon, i.e., amino acid Ala or Gly are needed as the second amino acid in the nascent peptide for the cleavage of the initiator Met, and the consequent overuse of Ala and Gly codons (GCN and GGN) leads to the +4G consensus. I performed a critical test of these alternative hypotheses on +4G based on 34169 human protein-coding genes and published gene expression data. The result shows that the prevalence of +4G is not related to translation initiation. Among the five G-starting codons, only alanine codons (GCN), and glycine codons (GGN) to a much smaller extent, are overrepresented at the second codon, whereas the other three codons are not overrepresented. While highly expressed genes have more +4G than lowly expressed genes, the difference is caused by GCN and GGN codons at the second codon. These results are inconsistent with +4G being needed for efficient translation initiation, but consistent with the proposal of amino acid constraint hypothesis

A Possible Constraint on Regional Precipitation Intensity Changes under Global Warming

Changes in daily precipitation versus intensity under a global warming scenario in two regional climate simulations of the United States show a well-recognized feature of more intense precipitation. More important, by resolving the precipitation intensity spectrum, the changes show a relatively simple pattern for nearly all regions and seasons examined whereby nearly all high-intensity daily precipitation contributes a larger fraction of the total precipitation, and nearly all low-intensity precipitation contributes a reduced fraction. The percentile separating relative decrease from relative increase occurs around the 70th percentile of cumulative precipitation, irrespective of the governing precipitation processes or which model produced the simulation. Changes in normalized distributions display these features much more consistently than distribution changes without normalization. Further analysis suggests that this consistent response in precipitation intensity may be a consequence of the intensity spectrum’s adherence to a gamma distribution. Under the gamma distribution, when the total precipitation or number of precipitation days changes, there is a single transition between precipitation rates that contribute relatively more to the total and rates that contribute relatively less. The behavior is roughly the same as the results of the numerical models and is insensitive to characteristics of the baseline climate, such as average precipitation, frequency of rain days, and the shape parameter of the precipitation’s gamma distribution. Changes in the normalized precipitation distribution give a more consistent constraint on how precipitation intensity may change when climate changes than do changes in the nonnormalized distribution. The analysis does not apply to extreme precipitation for which the theory of statistical extremes more likely provides the appropriate description