Recent progress in engineering highly promising biocatalysts has increasingly involved machine learning methods. These methods leverage existing experimental and simulation data to aid in the discovery and annotation of promising enzymes, as well as in suggesting beneficial mutations for improving known targets. The field of machine learning for protein engineering is gathering steam, driven by recent success stories and notable progress in other areas. It already encompasses ambitious tasks such as understanding and predicting protein structure and function, catalytic efficiency, enantioselectivity, protein dynamics, stability, solubility, aggregation, and more. Nonetheless, the field is still evolving, with many challenges to overcome and questions to address. In this Perspective, we provide an overview of ongoing trends in this domain, highlight recent case studies, and examine the current limitations of machine learning-based methods. We emphasize the crucial importance of thorough experimental validation of emerging models before their use for rational protein design. We present our opinions on the fundamental problems and outline the potential directions for future research.

• Publication type
• Journal Article MeSH
• Review MeSH

PURPOSE OF THE STUDY To compare the functional and radiological results of the total arthroscopic treatment (TAT) performed due to the rotator cuff (RC) tear problem with the results of the arthroscopically assisted mini-open surgery (AAMOS). MATERIAL AND METHODS This study conducted over a two-year period included all had TAT or AAMOS. Patients were included in the study if they had undergone arthroscopic or mini-open rotator cuff repair, with a minimum of 2 years' follow-up. Patients were divided into two groups in terms of the surgical technique performed. Patients who had TAT was included into the group 1 and, AAMOS group 2. Exclusion criteria included other significant intra-articular pathology such as SLAP lesions or glenohumeral arthrosis, previous rotator cuff surgery, massive rotator cuff tears (>5 cm), and neurologic disorders such as brachial plexopathy or suprascapular neuropathy. Every patient underwent magnetic resonance imaging evaluation before surgery and at last follow-up after surgery. Acromion typed of patients were recorded. Patients were questioned for ASES and Constant score. RESULTS Fifty-eight shoulders were included in the study. Twenty-eight patients were female and 30 were male. The mean age was 55.63 ± 8.06 years. Both groups had 29 patients per each. Mean follow-up period was 26.26 ± 11.46 months. There was no statistically significant difference between the mean age and gender distribution of the groups (p > 0.05). No statistically significant difference in the follow-up period between two groups (p > 0.05). No statistically significant difference was found between the postoperative ASES measurements between the two groups (p > 0.05). There was no statistically significant difference in postoperative Constant measurements between the two groups (p > 0.05). There was no statistically significant difference between the Acromion types between the two groups (p > 0.05). No statistically significant difference was found between the both groups in terms of accompanying shoulder pathology and AC joint degeneration (p > 0.05). In the postoperative MRIs of the patients, 7 patients in the Group 2 and 6 patients in the Group 1 were found to have recurrent tears. No statistically significant difference was found (p > 0.05). DISCUSSION When compared their patients who underwent RC repair by AAMOS intervention with those treated with TAT intervention and stated that the results were satisfactory for both groups and close to each other during their 2-year follow-up regardless of the tear diameter. Rotator cuff repairing with TAT is becoming a popular method of shoulder surgery. Initial reports of outcomes with this technique have indicated similar results when compared with open techniques, with less perioperative morbidity. Patients with RC tears treated by TAR, the shoulder range of motion was achieved in a shorter time and the rate of development of fibrous ankylosis was found to be lower. We performed the same configuration for the repair technique that may avoid to differ the results. Additionlay, all patients in study had the same rehabilitation protocol not to differ the results. Our study demonstrated similar results, with no differences noted in clinical outcomes between the TAT and the AAMOS for all scoring scales evaluated. Our experience with TAT notes a steep learning curve for proper technique. Certainly, surgeons may attempt a TAT, knowing that the patient's long-term outcome will not differ if the AAMOS is needed. CONCLUSIONS It must be kept in mind that both surgical methods may provide satisfactory results; the decision regarding which method should be used must be based on the skills, experience and technical oppurtunities of the orthopedic surgeon. However, any of the surgical technique is chosen, smilar excellent clinical results can be achieved. Key words: rotator cuff, mini-open surgery, total arthroscopic repair, cuff tear, Constant score, ASES score.

• MeSH
• Acromion MeSH
• Arthroscopy MeSH
• Middle Aged MeSH
• Humans MeSH
• Rotator Cuff Injuries * diagnostic imaging   surgery   MeSH
• Shoulder Joint * MeSH
• Rotator Cuff diagnostic imaging   surgery   MeSH
• Range of Motion, Articular MeSH
• Treatment Outcome MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

The physiological disciplines are being taught from the 1st year of medical study up to the end of the 4th year, it means 8 semesters altogether. It is necessary to explain the curriculum of the 3rd Faculty of Medicine, Charles University in Prague. This Faculty has had a new curriculum since 1997, so the first students, who had been taught as to this system, already finished their study. The duration of medical study is 6 years, i.e. 12 semesters. This composed of three cycles: I Basic biomedical sciences. The first two years represent the first cycle, which is based on the integrative principle. II. Principles of clinical medicine. The second cycle is concerned on the problem-based learning. III. Clinical preparation. The third cycle represents clinical application. In the first two years the integrative study is composed of different modules. The first module I A--Structure and functions of human body is the greatest module in the first two years, which is composed of anatomy, histology and embryology, biochemistry and physiology. The module I B--Cell biology and genetics is composed of genetics and cell biology and this module is finished by the examination after two semesters at the end of the first year.

• MeSH
• Physiology education   MeSH
• Curriculum * MeSH
• Humans MeSH
• Problem-Based Learning MeSH
• Education, Medical methods   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Czech Republic MeSH

A method for type analysis of learning curves, based on the statistical mixture decomposition, is described. Some critical points in current data-analytic techniques are discussed. The mathematical rationale of the new method is outlined in a brief sketch. The possibilities of the method are documented by two examples. In the first study, done on simulated lata of a known structure (N = 200, 2 classes), it was possible to distinguish, with an average performance of 82%, between two types, and to reproduce their original curves. In the second study data from experiments in classical eye-lid conditioning in man were analysed (N = 80). The decomposition procedure resulted into the classification into four groups, with pronounced inter-class differences in the course of respective learning curves. The variety of class curves ranges from a group with only few CRs (C1, N = 26), through a group with an initial increase and final decrease in CR frequency (C2, N = 16), a group with an apparently biphasic course of CR frequency (C3, N = 20), to a group with a rapid increase of CR and then stable course of CR frequency (C4, N = 18). The results are consistent with earlier findings concerning the existence of distinct types of learning curves. The problem of interpretation is briefly discussed. The method can be applied principally to any problems, where different types of time development trends of an alternative response are to be distinguished.

• MeSH
• Conditioning, Classical MeSH
• Humans MeSH
• Reinforcement Schedule MeSH
• Models, Psychological * MeSH
• Statistics as Topic MeSH
• Learning * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

The Hennovation project, an EU H2020 funded thematic network, aimed to explore the potential value of practice-led multi-actor innovation networks within the laying hen industry. The project proposed that husbandry solutions can be practice-led and effectively supported to achieve durable gains in sustainability and animal welfare. It encouraged a move away from the traditional model of science providing solutions for practice, towards a collaborative approach where expertise from science and practice were equally valued. During the 32-month project, the team facilitated 19 multi-actor networks in five countries through six critical steps in the innovation process: problem identification, generation of ideas, planning, small scale trials, implementation and sharing with others. The networks included farmers, processors, veterinarians, technical advisors, market representatives and scientists. The interaction between the farmers and the other network actors, including scientists, was essential for farmer innovation. New relationships emerged between the scientists and farmers, based on experimental learning and the co-production of knowledge for improving laying hen welfare. The project demonstrated that a practice-led approach can be a major stimulus for innovation with several networks generating novel ideas and testing them in their commercial context. The Hennovation innovation networks not only contributed to bridging the science-practice gap by application of existing scientific solutions in practice but more so by jointly finding new solutions. Successful multi-actor, practice-led innovation networks appeared to depend upon the following key factors: active participation from relevant actors, professional facilitation, moderate resource support and access to relevant expertise. Farmers and processors involved in the project were often very enthusiastic about the approach, committing significant time to the network's activities. It is suggested that the agricultural research community and funding agencies should place greater value on practice-led multi-actor innovation networks alongside technology and advisor focused initiatives to improve animal welfare and embed best practices.

• Keywords
• industry, innovation, laying hen, networks, practice-led,
• Publication type
• Journal Article MeSH

The proper way of breathing is important for everyone. Healthy people often do not follow respiration until breathing problems start-during stress or during sport activity in physiological cases. More serious cases are stroke, injury, or surgery of the chest and others. So, learning to breathe correctly and/or breathing diagnosis is considerable for many reasons. Two novel methods of breath analysis suitable for diagnostics and rehabilitation are presented. The first technique utilizes pressure belts fastened to the patient's belly and chest, and the second method relies on a SwissRanger SR-4000 time-of-flight camera. The measurement principles are described together with the advantages and disadvantages of the applied techniques. The SwissRanger camera depth calibration is proposed to facilitate better results during the breath analysis. The methods are tested on a group of students to provide a comparison of their individual performances. As it was demonstrated, presented methods proved to work reliably. The method based on time-of-flight camera seems to be more suitable for diagnosis, while the method based on pressure belts is more suitable for rehabilitation and biofeedback applications.

• Keywords
• Breath analysis, Calibration, Pressure measurement, Range measurement,
• MeSH
• Video Recording instrumentation   methods   MeSH
• Breath Tests instrumentation   methods   MeSH
• Equipment Design MeSH
• Adult MeSH
• Respiration MeSH
• Calibration MeSH
• Humans MeSH
• Young Adult MeSH
• Pressure MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

A significant development in pedagogical strategies which make use of the principles of embodied cognition can be found within the implementation of Immersive Virtual Reality (IVR) into art and design education. This theoretical study investigates how IVR-mediated embodiment enhances spatial thinking and creative problem-solving in art and design education by examining the taxonomy of embodied learning and principles of embodied cognition. The pedagogical affordances and limitations of IVR for creative learning are analyzed through a combination of empirical research and case studies, such as the Tangible and Embodied Spatial Cognition (TASC) system and Tilt Brush studies. Through gesture, spatial navigation, and environmental manipulation, IVR provides numerous possibilities for externalizing creative ideation; however, its implementation requires negotiating contradictions between virtual and physical materiality. IVR-based educational technologies have the potential to revolutionize teaching and learning. The goal of this paper is to provide educators with a theoretically grounded framework for applying embodied practices in IVR-based learning environments, while also acknowledging the current limitations of this technology.

• Keywords
• art education, creative thinking, design pedagogy, educational technology, embodied cognition, immersive virtual reality, sensorimotor learning, spatial reasoning,
• Publication type
• Journal Article MeSH
• Review MeSH

The prevention of engram interference, pattern separation, flexibility, cognitive coordination and spatial navigation are usually studied separately at the behavioral level. Impairment in executive functions is often observed in patients suffering from schizophrenia. We have designed a protocol for assessing these functions all together as behavioral separation. This protocol is based on alternated or sequential training in two tasks testing different hippocampal functions (the Morris water maze and active place avoidance), and alternated or sequential training in two similar environments of the active place avoidance task. In Experiment 1, we tested, in adult rats, whether the performance in two different spatial tasks was affected by their order in sequential learning, or by their day-to-day alternation. In Experiment 2, rats learned to solve the active place avoidance task in two environments either alternately or sequentially. We found that rats are able to acquire both tasks and to discriminate both similar contexts without obvious problems regardless of the order or the alternation. We used two groups of rats, controls and a rat model of psychosis induced by a subchronic intraperitoneal application of 0.08mg/kg of dizocilpine (MK-801), a non-competitive antagonist of NMDA receptors. Dizocilpine had no selective effect on parallel/sequential learning of tasks/contexts. However, it caused hyperlocomotion and a significant deficit in learning in the active place avoidance task regardless of the task alternation. Cognitive coordination tested by this task is probably more sensitive to dizocilpine than spatial orientation because no hyperactivity or learning impairment was observed in the Morris water maze.

• Keywords
• Active place avoidance, Context alternation, Dizocilpine, Morris water maze, Schizophrenia, Task alternation,
• MeSH
• Analysis of Variance MeSH
• Excitatory Amino Acid Antagonists toxicity   MeSH
• Maze Learning drug effects   MeSH
• Dizocilpine Maleate toxicity   MeSH
• Rats MeSH
• Locomotion drug effects   MeSH
• Disease Models, Animal MeSH
• Learning Disabilities chemically induced   physiopathology   MeSH
• Rats, Long-Evans MeSH
• Reaction Time drug effects   MeSH
• Avoidance Learning drug effects   MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Male MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Names of Substances
• Excitatory Amino Acid Antagonists MeSH
• Dizocilpine Maleate MeSH

This research paper develops a novel hybrid approach, called hybrid particle swarm optimization-teaching-learning-based optimization (hPSO-TLBO), by combining two metaheuristic algorithms to solve optimization problems. The main idea in hPSO-TLBO design is to integrate the exploitation ability of PSO with the exploration ability of TLBO. The meaning of "exploitation capabilities of PSO" is the ability of PSO to manage local search with the aim of obtaining possible better solutions near the obtained solutions and promising areas of the problem-solving space. Also, "exploration abilities of TLBO" means the ability of TLBO to manage the global search with the aim of preventing the algorithm from getting stuck in inappropriate local optima. hPSO-TLBO design methodology is such that in the first step, the teacher phase in TLBO is combined with the speed equation in PSO. Then, in the second step, the learning phase of TLBO is improved based on each student learning from a selected better student that has a better value for the objective function against the corresponding student. The algorithm is presented in detail, accompanied by a comprehensive mathematical model. A group of benchmarks is used to evaluate the effectiveness of hPSO-TLBO, covering various types such as unimodal, high-dimensional multimodal, and fixed-dimensional multimodal. In addition, CEC 2017 benchmark problems are also utilized for evaluation purposes. The optimization results clearly demonstrate that hPSO-TLBO performs remarkably well in addressing the benchmark functions. It exhibits a remarkable ability to explore and exploit the search space while maintaining a balanced approach throughout the optimization process. Furthermore, a comparative analysis is conducted to evaluate the performance of hPSO-TLBO against twelve widely recognized metaheuristic algorithms. The evaluation of the experimental findings illustrates that hPSO-TLBO consistently outperforms the competing algorithms across various benchmark functions, showcasing its superior performance. The successful deployment of hPSO-TLBO in addressing four engineering challenges highlights its effectiveness in tackling real-world applications.

• Keywords
• exploitation, exploration, hybrid-based algorithm, metaheuristic, optimization, particle swarm optimization, teaching–learning-based optimization,
• Publication type
• Journal Article MeSH

BACKGROUND: Identification of coordinately regulated genes according to the level of their expression during the time course of a process allows for discovering functional relationships among genes involved in the process. RESULTS: We present a single class classification method for the identification of genes of similar function from a gene expression time series. It is based on a parallel genetic algorithm which is a supervised computer learning method exploiting prior knowledge of gene function to identify unknown genes of similar function from expression data. The algorithm was tested with a set of randomly generated patterns; the results were compared with seven other classification algorithms including support vector machines. The algorithm avoids several problems associated with unsupervised clustering methods, and it shows better performance then the other algorithms. The algorithm was applied to the identification of secondary metabolite gene clusters of the antibiotic-producing eubacterium Streptomyces coelicolor. The algorithm also identified pathways associated with transport of the secondary metabolites out of the cell. We used the method for the prediction of the functional role of particular ORFs based on the expression data. CONCLUSION: Through analysis of a time series of gene expression, the algorithm identifies pathways which are directly or indirectly associated with genes of interest, and which are active during the time course of the experiment.

• MeSH
• Algorithms MeSH
• Chromosomes, Bacterial genetics   MeSH
• Computer Simulation MeSH
• Oligonucleotide Array Sequence Analysis MeSH
• Gene Expression Profiling * MeSH
• Streptomyces coelicolor classification   genetics   metabolism   MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH