Positive and Negative Effects of Administering a Magnetic Field to Patients with Rheumatoid Arthritis (RA).

Background: Magnetotherapy applied to patients with rheumatoid arthritis (RA) produces anti-inflammatory, analgesic and antioedema effects. Observations suggest that the beneficial and adverse effects of magnetotherapy are related to the parameters of the magnetic field applied. This study aimed to assess the positive and negative effects of magnetotherapy, taking into account the type of the field. Methods: This study involved 39 patients with RA, who were randomly assigned to two groups: SMF-static magnetic field (n = 18) and PEMF-low-frequency pulsed electromagnetic field (n = 21). The examinations carried out before and after the therapy included a general assessment of the functional status, assessment of pain severity, measurement of the duration and severity of morning stiffness, computer-aided measurement of the range of motion of the hand joints and measurement of the hand volume using water displacement method. The patients received kinesiotherapy and magnetotherapy, as determined by the randomisation. Results: The findings show improved functional status by 0.26 points on average (p = 0.0166) measured with the Health Assessment Questionnaire (HAQ-20), reduced pain by 2.2 points on average (p = 0.0000) on the Visual Analogue Scale (VAS), decreased duration of morning stiffness by 23.2 min on average (p = 0.0010) and reduced severity of morning stiffness by 15.2 points on average (p = 0.0010). The assessment of the dominant hand showed improved range of motion by 1.9 mm on average (p = 0.0036) and reduced volume by 0.9 mm3 on average (p = 0.0230). A significantly reduced duration and severity of morning stiffness was observed in the SMF group. Statistically significant changes in the HAQ-20 scores, range of motion and the volume of the dominant hand were identified in the PEMF group. Conclusions: Magnetic fields improved the functional status and reduced pain, morning stiffness and swelling in the hand. A static magnetic field may be more effective in reducing morning stiffness, whereas a pulsed magnetic field may, to a greater extent, improve function and reduce swelling in the rheumatoid hand. The effects of magnetotherapy reported so far require further observation.

The Relationship between Self-Rated Health and Physical Fitness in Polish Youth.

Self-rated health (SRH) is a tool for assessing a population's health across the lifetime, and seems to be a dynamic assessment of current health status and a strong predictor of cardiovascular disease and mortality, whereas insufficient levels of physical fitness in adolescence are a significant health problem and may contribute to the development of many disorders in adulthood. In this cross-sectional study, we attempted to assess the relationship between SRH and the physical fitness of adolescents. Two hundred and thirty-five adolescents (eighty-five boys and one hundred and fifty girls) aged 16-17 were recruited for this study. The study procedures included a short author questionnaire and physical fitness assessment (Zuchora's Physical Fitness Index). Boys declared better health states and reported less frequent morbidity of seasonal diseases (p < 0.05). No differences were found in physical fitness, the incidence of postural disorders, lower limb malalignments, foot deformities, sleep duration, and perception of physical activity on physical condition and well-being in boys and girls (p > 0.05). The comparison of physical fitness levels in adolescents with different SRH, sleep duration, perceptions of physical activity on physical condition and well-being also showed significant differences (p < 0.05). Positive SRH and perception of physical activity on physical condition and well-being, proper sleep duration (7-8 h/night), and a lack of foot deformities are associated with a better physical fitness in adolescents. Physical fitness seems to be a good predictor of SRH only in Polish boys, but not girls and the entire population. The lack of significance in the entire population could be attributed to the substantial number of girls in the study group. Despite that, it is recommended to encourage adolescents to engage in regular exercises, sleep routines and healthy lifestyles. Further research should be based on a more representative group, with a comparable number of girls and boys in the study group and potential confounders, but also they should be focused on SRH predictors to improve SRH in Polish girls.

ACL Reconstruction: Which Additional Physiotherapy Interventions Improve Early-Stage Rehabilitation? A Systematic Review.

Despite the restoration of the mechanical stability of the knee joint after ACL reconstruction (ACLR), patients often experience postoperative limitations. To our knowledge, there are no systematic reviews analyzing additional physiotherapy interventions implementing standard rehabilitation programs in the early postoperative phase after ACLR. The objective of this study was to analyze the additional physiotherapy interventions implemented in standard rehabilitation programs that improve early-stage ACLR rehabilitation. For this systematic review, we followed the PRISMA guidelines. In March 2022 we conducted a literature review using electronic databases. Primary outcomes were pain, edema, muscle strength, ROM, and knee function. The risk of bias and scientific quality of included studies were assessed with the RoB 2, ROBINS-I and PEDro scale. For the review, we included 10 studies that met the inclusion criteria (total n = 3271). The included studies evaluated the effectiveness of Kinesio Taping, Whole-body vibration, Local Vibration Training, Trigger Point Dry Needling, High Tone Power Therapy, alternating magnetic field, and App-Based Active Muscle Training Program. Most of the additional physiotherapy interventions improved pain, edema, ROM, knee muscle strength, or knee function in early-stage postoperative ACL rehabilitation. Except for one study, no adverse events occurred in the included studies, which demonstrates the safety of the discussed physiotherapy interventions. Further in-depth research is needed in this area.

Polypill Strategy in Secondary Cardiovascular Prevention.

BACKGROUND: A polypill that includes key medications associated with improved outcomes (aspirin, angiotensin-converting-enzyme [ACE] inhibitor, and statin) has been proposed as a simple approach to the secondary prevention of cardiovascular death and complications after myocardial infarction. METHODS: In this phase 3, randomized, controlled clinical trial, we assigned patients with myocardial infarction within the previous 6 months to a polypill-based strategy or usual care. The polypill treatment consisted of aspirin (100 mg), ramipril (2.5, 5, or 10 mg), and atorvastatin (20 or 40 mg). The primary composite outcome was cardiovascular death, nonfatal type 1 myocardial infarction, nonfatal ischemic stroke, or urgent revascularization. The key secondary end point was a composite of cardiovascular death, nonfatal type 1 myocardial infarction, or nonfatal ischemic stroke. RESULTS: A total of 2499 patients underwent randomization and were followed for a median of 36 months. A primary-outcome event occurred in 118 of 1237 patients (9.5%) in the polypill group and in 156 of 1229 (12.7%) in the usual-care group (hazard ratio, 0.76; 95% confidence interval [CI], 0.60 to 0.96; P = 0.02). A key secondary-outcome event occurred in 101 patients (8.2%) in the polypill group and in 144 (11.7%) in the usual-care group (hazard ratio, 0.70; 95% CI, 0.54 to 0.90; P = 0.005). The results were consistent across prespecified subgroups. Medication adherence as reported by the patients was higher in the polypill group than in the usual-care group. Adverse events were similar between groups. CONCLUSIONS: Treatment with a polypill containing aspirin, ramipril, and atorvastatin within 6 months after myocardial infarction resulted in a significantly lower risk of major adverse cardiovascular events than usual care. (Funded by the European Union Horizon 2020; SECURE ClinicalTrials.gov number, NCT02596126; EudraCT number, 2015-002868-17.).

Genome-scale de novo assembly using ALGA.

MOTIVATION: There are very few methods for de novo genome assembly based on the overlap graph approach. It is considered as giving more exact results than the so-called de Bruijn graph approach but in much greater time and of much higher memory usage. It is not uncommon that assembly methods involving the overlap graph model are not able to successfully compute greater datasets, mainly due to memory limitation of a computer. This was the reason for developing in last decades mainly de Bruijn-based assembly methods, fast and fairly accurate. However, the latter methods can fail for longer or more repetitive genomes, as they decompose reads to shorter fragments and lose a part of information. An efficient assembler for processing big datasets and using the overlap graph model is still looked out. RESULTS: We propose a new genome-scale de novo assembler based on the overlap graph approach, designed for short-read sequencing data. The method, ALGA, incorporates several new ideas resulting in more exact contigs produced in short time. Among these ideas, we have creation of a sparse but quite informative graph, reduction of the graph including a procedure referring to the problem of minimum spanning tree of a local subgraph, and graph traversal connected with simultaneous analysis of contigs stored so far. What is rare in genome assembly, the algorithm is almost parameter-free, with only one optional parameter to be set by a user. ALGA was compared with nine state-of-the-art assemblers in tests on genome-scale sequencing data obtained from real experiments on six organisms, differing in size, coverage, GC content and repetition rate. ALGA produced best results in the sense of overall quality of genome reconstruction, understood as a good balance between genome coverage, accuracy and length of resulting sequences. The algorithm is one of tools involved in processing data in currently realized national project Genomic Map of Poland. AVAILABILITY AND IMPLEMENTATION: ALGA is available at http://alga.put.poznan.pl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

GRASShopPER-An algorithm for de novo assembly based on GPU alignments.

Next generation sequencers produce billions of short DNA sequences in a massively parallel manner, which causes a great computational challenge in accurately reconstructing a genome sequence de novo using these short sequences. Here, we propose the GRASShopPER assembler, which follows an approach of overlap-layout-consensus. It uses an efficient GPU implementation for the sequence alignment during the graph construction stage and a greedy hyper-heuristic algorithm at the fork detection stage. A two-part fork detection method allows us to identify repeated fragments of a genome and to reconstruct them without misassemblies. The assemblies of data sets of bacteria Candidatus Microthrix, nematode Caenorhabditis elegans, and human chromosome 14 were evaluated with the golden standard tool QUAST. In comparison with other assemblers, GRASShopPER provided contigs that covered the largest part of the genomes and, at the same time, kept good values of other metrics, e.g., NG50 and misassembly rate.

Structural alignment of protein descriptors - a combinatorial model.

BACKGROUND: Structural alignment of proteins is one of the most challenging problems in molecular biology. The tertiary structure of a protein strictly correlates with its function and computationally predicted structures are nowadays a main premise for understanding the latter. However, computationally derived 3D models often exhibit deviations from the native structure. A way to confirm a model is a comparison with other structures. The structural alignment of a pair of proteins can be defined with the use of a concept of protein descriptors. The protein descriptors are local substructures of protein molecules, which allow us to divide the original problem into a set of subproblems and, consequently, to propose a more efficient algorithmic solution. In the literature, one can find many applications of the descriptors concept that prove its usefulness for insight into protein 3D structures, but the proposed approaches are presented rather from the biological perspective than from the computational or algorithmic point of view. Efficient algorithms for identification and structural comparison of descriptors can become crucial components of methods for structural quality assessment as well as tertiary structure prediction. RESULTS: In this paper, we propose a new combinatorial model and new polynomial-time algorithms for the structural alignment of descriptors. The model is based on the maximum-size assignment problem, which we define here and prove that it can be solved in polynomial time. We demonstrate suitability of this approach by comparison with an exact backtracking algorithm. Besides a simplification coming from the combinatorial modeling, both on the conceptual and complexity level, we gain with this approach high quality of obtained results, in terms of 3D alignment accuracy and processing efficiency. CONCLUSIONS: All the proposed algorithms were developed and integrated in a computationally efficient tool descs-standalone, which allows the user to identify and structurally compare descriptors of biological molecules, such as proteins and RNAs. Both PDB (Protein Data Bank) and mmCIF (macromolecular Crystallographic Information File) formats are supported. The proposed tool is available as an open source project stored on GitHub ( https://github.com/mantczak/descs-standalone ).

An integrated approach (CLuster Analysis Integration Method) to combine expression data and protein-protein interaction networks in agrigenomics: application on Arabidopsis thaliana.

Experimental co-expression data and protein-protein interaction networks are frequently used to analyze the interactions among genes or proteins. Recent studies have investigated methods to integrate these two sources of information. We propose a new method to integrate co-expression data obtained through DNA microarray analysis (MA) and protein-protein interaction (PPI) network data, and apply it to Arabidopsis thaliana. The proposed method identifies small subsets of highly interacting proteins. Based on the analysis of the basis of co-localization and mRNA developmental expression, we show that these groups provide important biological insights; additionally, these subsets are significantly enriched with respect to KEGG Pathways and can be used to predict successfully whether proteins belong to known pathways. Thus, the method is able to provide relevant biological information and support the functional identification of complex genetic traits of economic value in plant agrigenomics research. The method has been implemented in a prototype software tool named CLAIM (CLuster Analysis Integration Method) and can be downloaded from http://bio.cs.put.poznan.pl/research_fields . CLAIM is based on the separate clustering of MA and PPI data; the clusters are merged in a special graph; cliques of this graph are subsets of strongly connected proteins. The proposed method was successfully compared with existing methods. CLAIM appears to be a useful semi-automated tool for protein functional analysis and warrants further evaluation in agrigenomics research.

RNA partial degradation problem: motivation, complexity, algorithm.

Studies conducted during the last decade unexpectedly revealed several new biological functions of RNA molecules. The involvement of RNA in many complex processes requires highly effective systems controlling its accumulation. In this context, the mechanisms of degradation appear as one of the most important factors influencing RNA activity. Here, we present our first attempt to describe the RNA degradation process using bioinformatics methods. Based on the obtained data, we propose a formulation of a new problem, called RNA Partial Degradation Problem (RNA PDP) and the algorithm that is capable of reconstructing an RNA molecule using the results of biochemical analysis of its degradation. In addition, we present the results of biochemical experiments and computational tests.

Whole genome assembly from 454 sequencing output via modified DNA graph concept.

Recently, 454 Life Sciences Corporation proposed a new biochemical approach to DNA sequencing (the 454 sequencing). It is based on the pyrosequencing protocol. The 454 sequencing aims to give reliable output at a low cost and in a short time. The produced sequences are shorter than reads produced by classical methods. Our paper proposes a new DNA assembly algorithm which deals well with such data and outperforms other assembly algorithms used in practice. The constructed SR-ASM algorithm is a heuristic method based on a graph model, the graph being a modified DNA graph proposed for DNA sequencing by hybridization procedure. Other new features of the assembly algorithm are, among others, temporary compression of input sequences, and a new and fast multiple alignment heuristics taking advantage of the way the output data for the 454 sequencing are presented and coded. The usefulness of the algorithm has been proved in tests on raw data generated during sequencing of the whole 1.84Mbp genome of Prochlorococcus marinus bacteria and also on a part of chromosome 15 of Homo sapiens. The source code of SR-ASM can be downloaded from http://bio.cs.put.poznan.pl/ in the section 'Current research'--> 'DNA Assembly'. Among publicly available assemblers our algorithm appeared to generate the best results, especially in the number of produced contigs and in the lengths of the contigs with high similarity to the genome sequence.

Simplified partial digest problem: enumerative and dynamic programming algorithms.

We study the Simplified Partial Digest Problem (SPDP), which is a mathematical model for a new simplified partial digest method of genome mapping. This method is easy for laboratory implementation and robust with respect to the experimental errors. SPDP is NP-hard in the strong sense. We present an $O(n2;n)$ time enumerative algorithm and an O(n(2q)) time dynamic programming algorithm for the error-free SPDP, where $n$ is the number of restriction sites and n is the number of distinct intersite distances. We also give examples of the problem, in which there are 2(n+2)/(3)-1 non-congruent solutions. These examples partially answer a question recently posed in the literature about the number of solutions of SPDP. We adapt our enumerative algorithm for handling SPDP with imprecise input data. Finally, we describe and discuss the results of the computer experiments with our algorithms.

Dealing with repetitions in sequencing by hybridization.

DNA sequencing by hybridization (SBH) induces errors in the biochemical experiment. Some of them are random and disappear when the experiment is repeated. Others are systematic, involving repetitions in the probes of the target sequence. A good method for solving SBH problems must deal with both types of errors. In this work we propose a new hybrid genetic algorithm for isothermic and standard sequencing that incorporates the concept of structured combinations. The algorithm is then compared with other methods designed for handling errors that arise in standard and isothermic SBH approaches. DNA sequences used for testing are taken from GenBank. The set of instances for testing was divided into two groups. The first group consisted of sequences containing positive and negative errors in the spectrum, at a rate of up to 20%, excluding errors coming from repetitions. The second group consisted of sequences containing repeated oligonucleotides, and containing additional errors up to 5% added into the spectra. Our new method outperforms the best alternative procedures for both data sets. Moreover, the method produces solutions exhibiting extremely high degree of similarity to the target sequences in the cases without repetitions, which is an important outcome for biologists. The spectra prepared from the sequences taken from GenBank are available on our website http://bio.cs.put.poznan.pl/.

Assembling the SARS-CoV genome -- new method based on graph theoretical approach.

Nowadays, scientists may learn a lot about the organisms studied just by analyzing their genetic material. This requires the development of methods of reading genomes with high accuracy. It has become clear that the knowledge of the changes occurring within a viral genome is indispensable for effective fighting of the pathogen. A good example is SARS-CoV, which was a cause of death of many people and frightened the entire world with its fast and hard to prevent propagation. Rapid development of sequencing methods, like shotgun sequencing or sequencing by hybridization (SBH), gives scientists a good tool for reading genomes. However, since sequencing methods can read fragments of up to 1000 bp only, methods for sequence assembling are required in order to read whole genomes. In this paper a new assembling method, based on graph theoretical approach, is presented. The method was tested on SARS-CoV and the results were compared to the outcome of other widely known methods.

Tabu search algorithm for DNA sequencing by hybridization with isothermic libraries.

In this paper, a problem of isothermic DNA sequencing by hybridization (SBH) is considered. In isothermic SBH a new type of oligonucleotide libraries is used. The library consists of oligonucleotides of different lengths depending on an oligonucleotide content. It is assumed that every oligonucleotide in such a library has an equal melting temperature. Each nucleotide adds its increment to the oligonucleotide temperature and it is assumed that A and T add 2 degrees C and C and G add 4 degrees C. The hybridization experiment using isothermic libraries should provide data with a lower number of errors due to an expected similarity of melting temperatures. From the computational point of view the problem of isothermic DNA sequencing with errors is hard, similarly like its classical counterpart. Hence, there is a need for developing heuristic algorithms that construct good suboptimal solutions. The aim of the paper is to propose a heuristic algorithm based on tabu search approach. The algorithm solves the problem with both positive and negative errors. Results of an extensive computational experiment are presented, which prove the high quality of the proposed method.

A heuristic managing errors for DNA sequencing.

MOTIVATION: A new heuristic algorithm for solving DNA sequencing by hybridization problem with positive and negative errors. RESULTS: A heuristic algorithm providing better solutions than algorithms known from the literature based on tabu search method.