An Assessment of PC-mer's Performance in Alignment-Free Phylogenetic Tree Construction

Background: Sequence comparison is essential in bioinformatics, serving various purposes such as taxonomy, functional inference, and drug discovery. The traditional method of aligning sequences for comparison is time-consuming, especially with large datasets. To overcome this, alignment-free methods have emerged as an alternative approach, prioritizing comparison scores over alignment itself. These methods directly compare sequences without the need for alignment. However, accurately representing the relationships between sequences is a significant challenge in the design of these tools. Methods:One of the alignment-free comparison approaches utilizes the frequency of fixed-length substrings, known as K-mers, which serves as the foundation for many sequence comparison methods. However, a challenge arises in these methods when increasing the length of the substring (K), as it leads to an exponential growth in the number of possible states. In this work, we explore the PC-mer method, which utilizes a more limited set of words that experience slower growth 2^k instead of 4^k compared to K. We conducted a comparison of sequences and evaluated how the reduced input vector size influenced the performance of the PC-mer method. Results: For the evaluation, we selected the Clustal Omega method as our reference approach, alongside three alignment-free methods: kmacs, FFP, and alfpy (word count). These methods also leverage the frequency of K-mers. We applied all five methods to 9 datasets for comprehensive analysis. The results were compared using phylogenetic trees and metrics such as Robinson-Foulds and normalized quartet distance (nQD). Conclusion: Our findings indicate that, unlike reducing the input features in other alignment-independent methods, the PC-mer method exhibits competitive performance when compared to the aforementioned methods especially when input sequences are very varied

A novel deletion mutation in ASPM gene in an Iranian family with autosomal recessive primary microcephaly

How to Cite This Article: Akbarizar E, Ebrahimpour M, Akbari S, Arzhanghi S, Abedini SS, Najmabadi H, Kahrizi K. A Novel Deletion Mutation in ASPM Gene in an Iranian Family with Autosomal Recessive Primary Microcephaly. Iran J Child Neurol.  2013 Spring;7(2):23-30. ObjectiveAutosomal recessive primary microcephaly (MCPH) is a neurodevelopmental and genetically heterogeneous disorder with decreased head circumference due to the abnormality in fetal brain growth. To date, nine loci and nine genes responsible for the situation have been identified. Mutations in the ASPM gene (MCPH5) is the most common cause of MCPH. The ASPM gene with 28 exons is essential for normal mitotic spindle function in embryonic neuroblasts.Materials & MethodsWe have ascertained twenty-two consanguineous families withintellectual disability and different ethnic backgrounds from Iran. Ten out of twenty-two families showed primary microcephaly in clinical examination. We investigated MCPH5 locus using homozygosity mapping by microsatellite marker. ResultSequence analysis of exon 8 revealed a deletion of nucleotide (T) in donor site of splicing site of ASPM in one family. The remaining nine families were not linked to any of the known loci. More investigation will be needed to detect the causative defect in these families.ConlusionWe detected a novel mutation in the donor splicing site of exon 8 of the ASPM gene. This deletion mutation can alter the ASPM transcript leading to functional impairment of the gene product. References1. Pattison L, Crow YJ, Deeble VJ, Jackson AP, Jafri H, Rashid Y, et al. A Fifth Locus for Primary Autosomal Recessive Microcephaly Maps to Chromosome 1q31. Am J Hum Genet 2000;67(6):1578-80.2. Darvish H, Esmaeeli-Nieh S, Monajemi G, Mohseni M, Ghasemi-Firouzabadi S, Abedini S, et al. A clinical and molecular genetic study of 112 Iranian families with primary microcephaly. Journal of Medical Genetics 2010;47(12):823-8.3. Tolmie JL, M M, JB S, D D, JM C. Microcephaly: genetic counselling and antenatal diagnosis after the birth of an affected child. Am JMed Genet 1987;27583-94.4. Cowie V. The genetics and sub-classification of microcephaly. J Ment Defic Res 1960;4:42-7. 5. Woods C. Human microcephaly. Curr Opin Neurobiol 2004;14(1):112-7.6. Kaindl AM PS, Kumar P, Kraemer N, Issa L, Zwirner A, Gerard B, Verloes A MS,et al.Many roads lead to primary autosomal recessive microcephaly. Prog Neurobiol 2010;90:363-83.7. Kumar A BS, Babu M, Markandaya M, Girimaji SC. Genetic analysis of primary microcephaly in Indian families: novel ASPM mutations. Clin Genet 2004;66:341-8.8. Jackson AP, Eastwood H, Bell SM, Adu J, Toomes C, Carr IM, et al. Identification of microcephalin, a protein implicated in determining the size of the human brain. The American Journal of Human Genetics 2002;71(1):136-42.9. Roberts E, Jackson AP, Carradice AC, Deeble VJ, Mannan J, Rashid Y, et al. The second locus for autosomal recessive primary microcephaly (MCPH2) maps to chromosome 19q13. 1-13.2. European journal of human genetics: EJHG  1999;7(7):815.10. Kousar R, Hassan MJ, Khan B, Basit S, Mahmood S, Mir A, et al. Mutations in WDR62 gene in Pakistani families with autosomal recessive primary microcephaly. BMC neurology 2011;11(1):119.11. Evans PD, Vallender EJ, Lahn BT. Molecular evolutionof the brain size regulator genes<i> CDK5RAP2</i>and<i> CENPJ</i>. Gene 2006;375:75-9.12. Nagase T, Nakayama M, Nakajima D, Kikuno R, Ohara O. Prediction of the coding sequences of unidentified human genes. XX. The complete sequences of 100 new cDNA clones from brain which code for large proteins in vitro. DNA research 2001;8(2):85-95. 13. Jamieson CR GC, Abramowicz MJ. Primary autosomal recessive microcephaly: homozygosity mapping of MCPH4 to chromosome 15. Am J Hum Genet 1999;65:1465-9.14. Genin A, Desir J, Lambert N, Biervliet M, Van Der Aa N, Pierquin G, et al. Kinetochore KMN network gene CASC5 mutated in Primary Microcephaly. Human molecular genetics 2012.15. Bond J, Roberts E, Mochida GH, Hampshire DJ, Scott S, Askham JM, et al. ASPM is a major determinant of cerebral cortical size. Nature genetics 2002;32(2):316-20.16. Fish JL, Kosodo Y, Enard W, Pääbo S, Huttner WB. Aspm specifically maintains symmetric proliferative divisions of neuroepithelial cells. Proceedings of the National Academy of Sciences 2006;103(27):10438-43.17. Leal G, Roberts E, Silva E, Costa S, Hampshire D, Woods C. A novel locus for autosomal recessive primary microcephaly (MCPH6) maps to 13q12.2. Journal of Medical Genetics 2003;40(7):540-2.18. Kumar A. Mutations in STIL, encoding a pericentriolar and centrosomal protein, cause primary microcephaly. The American Journal of Human Genetics 2009;84(2):286-90.19. Hussain MS, Baig SM, Neumann S, Nurnberg G, Farooq M, Ahmad I, et al. Atruncating mutation on CEP135 causes primary microcephaly and disturbed centrosomal function.AMJ,HumGenet 2012;90:871-8.20. Guernsey DL, Jiang H, Hussin J, Arnold M, Bouyakdan K, Perry S, et al. Mutations in centrosomal protein CEP152 in primary microcephaly families linked to MCPH4. The American Journal of Human Genetics 2010;87(1):40-51.21. Gul A, Hassan MJ, Mahmood S, Chen W, Rahmani S, Naseer MI, et al. Genetic studies of autosomal recessive primary microcephaly in 33 Pakistani families: novel sequence variants in ASPM gene. Neurogenetics 2006;7(2):105-10.22. Roberts E, Hampshire D, Springell K, Pattison L, Y C, Jafri H, et al. Autosomal recessive primary microcephaly: an analysis of locus heterogeneity and phenotypic variation. J Med Genet 2002;39:718–721.23. Woods CG BJ, Enard W. Autosomal recessive primary microcephaly (MCPH): a review of clinical, molecular, and evolutionary findings. Am J Hum Genet 2005 May;76(5):717-28.24. Kouprina N, Pavlicek A, Collins NK, Nakano M, Noskov VN, Ohzeki JI, et al. The microcephaly ASPM gene is expressed in proliferating tissues and encodes for a mitotic spindle protein. Human Molecular Genetics 2005;14(15):2155-65.25. Bond J, Scott S, Hampshire DJ, Springell K, Corry P, Abramowicz MJ, et al. Protein-Truncating Mutations in< i> ASPM</i> Cause Variable Reduction in Brain Size. The American Journal of Human Genetics 2003;73(5):1170-7.26. Pichon B, Vankerckhove S, Bourrouillou G, Duprez L, Abramowicz MJ. A translocation breakpoint disrupts the ASPM gene in a patient with primary microcephaly. European journal of Human Genetics 2004;12(5):419-21.27. Garshasbi.M, Motazacker M, Kahrizi K, Behjati F, Abedini S, Nieh S, et al. SNP array-based homozygosity mapping reveals MCPH1 deletion in family with autosomal recessive mental retardation and mild microcephaly. Hum Genet 2006 Feb;118(6):708-15.28. Jackson A, McHale D, Campbell D, Jafri H, Rashid Y, Mannan J, et al. Primary autosomal recessive microcephaly (MCPH1) maps to chromosome 8p22-pter. Am J Hum Genet 1998 Aug;63(2):541-6.29. Moynihan L, Jackson A, Roberts E, Karbani G, Lewis I, Corry P, et al. A third novel locus for primary autosomal recessive microcephaly maps to chromosome 9q34. Am J Hum Genet 2000 Feb;66(2):724-7.30. Bond J, Roberts E, Springell K, Lizarraga S, Scott S, Higgins J, et al. A centrosomalmechanism involving CDK5RAP2 and CENPJ controls brain size. Nat Genet.2005 Apr;37(4):353-5. Nat Genet 2005 Apr;37(4):353-5.31. Jamieson C, Govaerts C, Abramowicz M, J. Primary autosomal recessive microcephaly: homozygosity mapping of MCPH4 to chromosome 15. Am J Hum Genet. 1999;65:1465-9

Evaluation of Noise, Light and Burnout in the Intensive Care unit of Neurosurgery, Loghman Hakim Hospital

سابقه و هدف: آلودگي صوتي و کمبود روشنایی، بر میزان بهبود فعالیت‌های کارکنان تاثیر مستقیم دارند و باعث ایجاد فرسودگی شغلی و ایجاد رفتار‌های منفی در فرد می‌شوند. پژوهش حاضر با هدف بررسی عوامل میزان صدا، روشنایی موضعی محیط کار و میزان فرسودگی شغلی در بخش مراقبت‌ ویژه مغزی در بیمارستان لقمان حکیم انجام شد. روش بررسی: مطالعه حاضر از نوع مقطعـی و مـشاهده‌ای – توصـیفی بوده و جامعه آماري، کارکنان بخش مراقبت‌ ویژه مغزی بيمارستان لقمان حکيم بوده‌اند. ابزار مطالعه شامل پرسشنامه فرسودگی شغلی مسلش (25)، دستگاه صداسنج و لوکس‌متر بوده است. نتایج: میانگین صدا در محیط کار 44/3 دسی‌بل و بیش از حد استاندارد بود. وضعیت روشنایی موضعی 38 ایستگاه اندازه‌گیری شده در 20 ایستگاه (معادل 78/95 درصد) نامطلوب بود. پرسشنامه فرسودگی شغلی نشان داد تمام کارکنان داری افسردگی بوده و بیش‌ترین میزان فرسودگی شغلی در بعد خستگی عاطفی و عملکرد شخصی و کم‌ترین میزان در بعد مسخ شخصیت مشاهده ‌شد. نتیجه گیری: افرادی که در بخش مراقبت‌ ویژه مغزی کار می‌کنند به دلیل ماهیت شغلی در مواجهه استرس بیش‌تری قراردارند و امکان بروز فرسودگی شغلی در سطوح بالا در آنان پیش‌بینی می‌شود که برگزاری دوره‌‌های آموزشی و ارتقای مهارت‌های مدیریت استرس در جهت پیشگیری از فرسودگی برای کارکنان این بخش می‌‌بایست مورد توجه قرارگیرد. How to cite this article: Bahramzadeh AH, Monazami-Tehrani G, Nateghinia S, Akbari-Dilmaghani N. Evaluation of Noise, Light and Burnout in the Intensive Care unit of Neurosurgery, Loghman Hakim Hospital. Irtiqa Imini Pishgiri Masdumiyat. 2021;9(3):183-9.  Background and Objectives: Noise pollution and lack of light directly affect the activities of employees and cause burnout and negative behaviors in the individual. The aim of this study was to investigate the physically harmful factors of noise and local illumination of the workplace and the rate of burnout in the intensive care unit of the brain in Loghman Hakim Hospital. Method and Materials: The present study is a cross-sectional and observational-descriptive study and the statistical population was the staff of the intensive care unit of Loghman Hakim Hospital. The study instruments included the Maslach burnout questionnaire (25), sound meter, and luxometer. Results: The average noise in the workplace is 44.3 decibels and exceeds the standard. The local lighting condition of 38 stations measured in 20 stations (equivalent to 78.95%) was unfavorable. The burnout questionnaire showed that all employees had depression and the highest rate of burnout was observed in the dimension of emotional fatigue and personal performance and the lowest rate was observed in the dimension of depersonalization. Conclusion: People who work in the intensive care unit of the brain are more exposed to stress due to the nature of the job and the possibility of burnout at high levels is predicted in them to hold training courses and improve stress management skills to prevent burnout. The staff of this department should be taken into consideration . How to cite this article: Bahramzadeh AH, Monazami-Tehrani G, Nateghinia S, Akbari-Dilmaghani N. Evaluation of Noise, Light and Burnout in the Intensive Care unit of Neurosurgery, Loghman Hakim Hospital. Irtiqa Imini Pishgiri Masdumiyat. 2021;9(3):183-9

A new profiling approach for DNA sequences based on the nucleotides' physicochemical features for accurate analysis of SARS-CoV-2 genomes

Abstract Background The prevalence of the COVID-19 disease in recent years and its widespread impact on mortality, as well as various aspects of life around the world, has made it important to study this disease and its viral cause. However, very long sequences of this virus increase the processing time, complexity of calculation, and memory consumption required by the available tools to compare and analyze the sequences. Results We present a new encoding method, named PC-mer, based on the k-mer and physic-chemical properties of nucleotides. This method minimizes the size of encoded data by around 2 k times compared to the classical k-mer based profiling method. Moreover, using PC-mer, we designed two tools: 1) a machine-learning-based classification tool for coronavirus family members with the ability to recive input sequences from the NCBI database, and 2) an alignment-free computational comparison tool for calculating dissimilarity scores between coronaviruses at the genus and species levels. Conclusions PC-mer achieves 100% accuracy despite the use of very simple classification algorithms based on Machine Learning. Assuming dynamic programming-based pairwise alignment as the ground truth approach, we achieved a degree of convergence of more than 98% for coronavirus genus-level sequences and 93% for SARS-CoV-2 sequences using PC-mer in the alignment-free classification method. This outperformance of PC-mer suggests that it can serve as a replacement for alignment-based approaches in certain sequence analysis applications that rely on similarity/dissimilarity scores, such as searching sequences, comparing sequences, and certain types of phylogenetic analysis methods that are based on sequence comparison

Optical pattern generator for efficient bio-data encoding in a photonic sequence comparison architecture.

In this study, optical technology is considered as SA issues' solution with the potential ability to increase the speed, overcome memory-limitation, reduce power consumption, and increase output accuracy. So we examine the effect of bio-data encoding and the creation of input images on the pattern-recognition error-rate at the output of optical Vander-lugt correlator. Moreover, we present a genetic algorithm-based coding approach, named as GAC, to minimize output noises of cross-correlating data. As a case study, we adopt the proposed coding approach within a correlation-based optical architecture for counting k-mers in a DNA string. As verified by the simulations on Salmonella whole-genome, we can improve sensitivity and speed more than 86% and 81%, respectively, compared to BLAST by using coding set generated by GAC method fed to the proposed optical correlator system. Moreover, we present a comprehensive report on the impact of 1D and 2D cross-correlation approaches, as-well-as various coding parameters on the output noise, which motivate the system designers to customize the coding sets within the optical setup

An optimized graph-based structure for single-cell RNA-seq cell-type classification based on non-linear dimension reduction

Abstract Background It is now possible to analyze cellular heterogeneity at the single-cell level thanks to the rapid developments in single-cell sequencing technologies. The clustering of cells is a fundamental and common step in heterogeneity analysis. Even so, accurate cell clustering remains a challenge due to the high levels of noise, the high dimensions, and the high sparsity of data. Results Here, we present SCEA, a clustering approach for scRNA-seq data. Using two consecutive units, an encoder based on MLP and a graph attention auto-encoder, to obtain cell embedding and gene embedding, SCEA can simultaneously achieve cell low-dimensional representation and clustering performing various examinations to obtain the optimal value for each parameter, the presented result is in its most optimal form. To evaluate the performance of SCEA, we performed it on several real scRNA-seq datasets for clustering and visualization analysis. Conclusions The experimental results show that SCEA generally outperforms several popular single-cell analysis methods. As a result of using all available datasets, SCEA, in average, improves clustering accuracy by 4.4% in ARI Parameters over the well-known method scGAC. Also, the accuracy improvement of 11.65% is achieved by SCEA, compared to the Seurat model

Investigation Genetic Causes Of Hereditary Intellectual Disability in Ahvaz (2011-2012)

Objective: Intellectual Disability (ID) characterize by significant limitations both in intellectual functioning and in adaptative behavior, originates before the age of 18. Over 70% of severe to profound intellectual disabilities (ID) caused by genetic factors. The aim of this study was to investigate genetic causes of ID in fourty Ahvazi families and provide information for genetic counseling, carrier detection, and prenatal diagnosis. Materials & Methods: In collaboration with Welfare Organization of Khuzestan Province, a total of 183 ID families from Ahwaz were investigated from which 40 (62 male and 42 female) families whose ID had been confirmed by psychiatrist and had more than one affected individual were selected for molecular analysis. Blood samples were collected from all normal and affected individuals in each family on EDTA pre-coated tubes. Thorough clinical characterization, dysmorphism examinations, karyotype analysis were carried out for all of the patients. Results: Three out of 40 (7.5%) families had full mutation of Fragile X syndrome. No chromosomal abnormalities were identified. Metabolic screening revealed none of families had metabolic disorder. None of three families with primary microcephaly showed linkage to any of the seven known MCPH loci. Conclusion: The most common causes of ID in Ahvaz was Fragile X syndrome and Autosomal Reccesive Primary Microcephaly with the frequency of (7.5%). It seems that autosomal reccesive primary microcephaly is a relatively common heterogenous condition in Ahvaz

Including Tables A1-A96, assuming dataset 5: <i>Hub Proteins Protein-Protein Interactions Dataset, AARR1 Gene Set</i> [57].

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