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1. Total disc replacement alters the biomechanics of cervical spine based on sagittal cervical alignment: A finite element study

   https://doi.org/10.4103/jcvjs.jcvjs_21_22  

   Mumtaz, Muzammil; Mendoza, Justin; Tripathi, Sudharshan; Kelkar, Amey; Nishida, Norihiro; Sahai, Ashish; Goel, Vijay K (January 2022, Journal of Craniovertebral Junction and Spine)

   IntroductionThe correlation between cervical alignment and clinical outcome of total disc replacement (TDR) surgery is arguable. We believe that this conflict exists because the parameters that influence the biomechanics of the cervical spine are not well understood, specifically the effect of TDR on different cervical alignments. Methods:A validated osseo-ligamentous model from C2-C7 was used in this study. The C2-C7 Cobb angle of the base model was modified to represent: lordotic (−10°), straight (0°), and kyphotic (+10°) cervical alignment. The TDR surgery was simulated at the C5-C6 segment. The range of motion (ROM), intradiscal pressure, annular stresses, and facet loads were computed for all the models. Results:The ROM results demonstrated kyphotic alignment after TDR surgery to be the most mobile when compared to intact base model (41% higher in flexion–extension, 51% higher in lateral bending, and 27% higher in axial rotation) followed by straight and lordotic alignment, respectively. The annular stresses for the kyphotic alignment when compared to intact base model were higher at the index level (33% higher in flexion–extension and 48% higher in lateral bending) compared to other alignments. The lordotic model demonstrated higher facet contact forces at the index level (75% higher in extension than kyphotic alignment, 51% higher in lateral bending than kyphotic alignment, and 78% higher in axial rotation than kyphotic alignment) when compared among the three alignment models. Conclusion:Preoperative cervical alignment should be an integral part of surgical planning for TDR surgery as different cervical alignments may significantly alter the postsurgical outcomes. 

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2. HMMerge: an ensemble method for multiple sequence alignment

   https://doi.org/10.1093/bioadv/vbad052  

   Park, Minhyuk; Warnow, Tandy; Lengauer, ed., Thomas (April 2023, Bioinformatics Advances)

   Abstract MotivationDespite advances in method development for multiple sequence alignment over the last several decades, the alignment of datasets exhibiting substantial sequence length heterogeneity, especially when the input sequences include very short sequences (either as a result of sequencing technologies or of large deletions during evolution) remains an inadequately solved problem. ResultsWe present HMMerge, a method to compute an alignment of datasets exhibiting high sequence length heterogeneity, or to add short sequences into a given ‘backbone’ alignment. HMMerge builds on the technique from its predecessor alignment methods, UPP and WITCH, which build an ensemble of profile HMMs to represent the backbone alignment and add the remaining sequences into the backbone alignment using the ensemble. HMMerge differs from UPP and WITCH by building a new ‘merged’ HMM from the ensemble, and then using that merged HMM to align the query sequences. We show that HMMerge is competitive with WITCH, with an advantage over WITCH when adding very short sequences into backbone alignments. Availability and implementationHMMerge is freely available at https://github.com/MinhyukPark/HMMerge. Supplementary informationSupplementary data are available at Bioinformatics Advances online. 

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3. P‐188: Cellulose Nanocrystals as an Alignment Layer for Liquid‐Crystal Displays in a Circular Economy

   https://doi.org/10.1002/sdtp.18667  

   Zhang, Ye; Doherty, James L; Franklin, Aaron; Kymissis, loannis (June 2025, SID Symposium Digest of Technical Papers)

   We report a Liquid Crystal Display (LCD) structure employing cellulose nanocrystals (CNC) as a recyclable, non‐toxic alignment layer in a twisted nematic configuration The CNC alignment layer, fabricated via spin coating and mechanical rubbing, demonstrated comparable performance to polyimide in transparency, threshold voltage, response speed, and liquid crystal alignment This work demonstrates the viability of CNC alignment layers, advancing LCD technology toward circular economy principles. 

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4. EMMA: a new method for computing multiple sequence alignments given a constraint subset alignment

   https://doi.org/10.1186/s13015-023-00247-x  

   Shen, Chengze; Liu, Baqiao; Williams, Kelly P.; Warnow, Tandy (December 2023, Algorithms for Molecular Biology)

   Abstract BackgroundAdding sequences into an existing (possibly user-provided) alignment has multiple applications, including updating a large alignment with new data, adding sequences into a constraint alignment constructed using biological knowledge, or computing alignments in the presence of sequence length heterogeneity. Although this is a natural problem, only a few tools have been developed to use this information with high fidelity. ResultsWe present EMMA (Extending Multiple alignments using MAFFT--add) for the problem of adding a set of unaligned sequences into a multiple sequence alignment (i.e., a constraint alignment). EMMA builds on MAFFT--add, which is also designed to add sequences into a given constraint alignment. EMMA improves on MAFFT--add methods by using a divide-and-conquer framework to scale its most accurate version, MAFFT-linsi--add, to constraint alignments with many sequences. We show that EMMA has an accuracy advantage over other techniques for adding sequences into alignments under many realistic conditions and can scale to large datasets with high accuracy (hundreds of thousands of sequences). EMMA is available athttps://github.com/c5shen/EMMA. ConclusionsEMMA is a new tool that provides high accuracy and scalability for adding sequences into an existing alignment. 

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5. Genome-wide alignment-free phylogenetic distance estimation under a no strand-bias model

   https://doi.org/10.1093/bioadv/vbac055  

   Balaban, Metin; Bristy, Nishat Anjum; Faisal, Ahnaf; Bayzid, Md Shamsuzzoha; Mirarab, Siavash; Lengauer, ed., Thomas (August 2022, Bioinformatics Advances)

   Abstract  Summary: While alignment has been the dominant approach for determining homology prior to phylogenetic inference, alignment-free methods can simplify the analysis, especially when analyzing genome-wide data. Furthermore, alignment-free methods present the only option for emerging forms of data, such as genome skims, which do not permit assembly. Despite the appeal, alignment-free methods have not been competitive with alignment-based methods in terms of accuracy. One limitation of alignment-free methods is their reliance on simplified models of sequence evolution such as Jukes–Cantor. If we can estimate frequencies of base substitutions in an alignment-free setting, we can compute pairwise distances under more complex models. However, since the strand of DNA sequences is unknown for many forms of genome-wide data, which arguably present the best use case for alignment-free methods, the most complex models that one can use are the so-called no strand-bias models. We show how to calculate distances under a four-parameter no strand-bias model called TK4 without relying on alignments or assemblies. The main idea is to replace letters in the input sequences and recompute Jaccard indices between k-mer sets. However, on larger genomes, we also need to compute the number of k-mer mismatches after replacement due to random chance as opposed to homology. We show in simulation that alignment-free distances can be highly accurate when genomes evolve under the assumed models and study the accuracy on assembled and unassembled biological data. Availability and implementationOur software is available open source at https://github.com/nishatbristy007/NSB. Supplementary informationSupplementary data are available at Bioinformatics Advances online. 

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