Pairs Of Patterns Research Articles

Multi-omics reveal immune microenvironment alterations in multiple myeloma and its precursor stages

Tumor immune microenvironmental alterations occur early in multiple myeloma (MM) development. In this study, we aim to systematically characterize the tumor immune microenvironment (TME) and the tumor-immune interactions from precursor stages, i.e., monoclonal gammopathy of undetermined significance (MGUS) and smoldering MM (SMM), to newly diagnosed MM, comparing these to healthy donors. Using CIBERSORT, mass cytometry (CyTOF), and single-cell RNA sequencing (scRNA-Seq), we examined innate and adaptive immune changes across these stages. We found a decrease in granulocytes in the TME predicts MM outcomes. HLA-DR is reduced in CD16+ monocytes and plasmacytoid dendritic cells, while myeloid dendritic cells show decreased expression of stress and immune-response genes. NK cells and CD8+ T cells shift from a GZMK+ to a GZMB+ cytotoxic phenotype in the TME, with increased inhibitory markers TIM3 and TIGIT. In paired samples, the proportion and gene expression pattern in patient-specific GZMB+CD8+ T cells remain largely unchanged despite MM progression. Our findings provide a comprehensive immune landscape of MM and its precursors, offering insights into therapeutic strategies. Enhancing neutrophil and NK cell cytotoxicity, tumor antigen presentation, and CD8+ T cell versatility in precursor stages may prevent MM progression.

Fixation patterns in pairs of facial expressions—preferences of self-critical individuals

So far, studies have revealed some differences in how long self-critical individuals fixate on specific facial expressions and difficulties in recognising these expressions. However, the research has also indicated a need to distinguish between the different forms of self-criticism (inadequate or hated self), the key underlying factor in psychopathology. Therefore, the aim of the current research was to explore fixation patterns for all seven primary emotions (happiness, sadness, fear, disgust, contempt, anger, and surprise) and the neutral face expression in relation to level of self-criticism by presenting random facial stimuli in the right or left visual field. Based on the previous studies, two groups were defined, and the pattern of fixations and eye movements were compared (high and low inadequate and hated self). The research sample consisted of 120 adult participants, 60 women and 60 men. We used the Forms of Self-Criticizing and Self-Reassuring Scale to measure self-criticism. As stimuli for the eye-tracking task, we used facial expressions from the Umeå University Database of Facial Expressions database. Eye movements were recorded using the Tobii X2 eye tracker. Results showed that in highly self-critical participants with inadequate self, time to first fixation and duration of first fixation was shorter. Respondents with higher inadequate self also exhibited a sustained pattern in fixations (total fixation duration; total fixation duration ratio and average fixation duration)—fixation time increased as self-criticism increased, indicating heightened attention to facial expressions. On the other hand, individuals with high hated self showed increased total fixation duration and fixation count for emotions presented in the right visual field but did not differ in initial fixation metrics in comparison with high inadequate self group. These results suggest that the two forms of self-criticism - inadequate self and hated self, may function as distinct mechanisms in relation to emotional processing, with implications for their role as potential transdiagnostic markers of psychopathology based on the fixation eye-tracking metrics.

Collective swimming pattern and synchronization of fish pairs (Gobiocypris rarus) in response to flow with different velocities.

Collective behaviors in moving fish originate from social interactions, which are thought to be driven by beneficial factors, such as predator avoidance and reduced energy expenditure. Despite numerical simulations and physical experiments aiming at the hydrodynamic mechanisms and interaction rules, how shoaling is influenced by flow velocity and group size is still only partially understood. In this study, spatial distributions, kinematics, and synchronization states between pairs (smallest subsystem of a shoal) of Gobiocypris rarus were investigated in a recirculating swim tunnel with increasing flow velocities from 0.1 to 0.5 m/s (Ucrit = 0.6 m/s). Tests of single fish were also conducted as the control group. The results of spatial distributions showed that fish pairs preferred to swim in the side-by-side configuration under high flows, while under low flows the neighboring fish's positions were more uniformly distributed around the focal fish in the transverse direction. Kinematic analysis revealed that fish pairs adopted similar tail beats (i.e., frequency and Strouhal number) as single fish in low flows, while in high flows both the frequency and Strouhal number of fish pairs were slightly lower. Moreover, the synchronization rates of fish pairs were found to increase with flow velocities, suggesting that synchronized swimming may be beneficial, especially in high flows.

On Scrolls, the Visual, and Visuality in Jewish Art

Abstract This article investigates the images of paired scrolling patterns recurring in the design of Jewish ritual spaces and objects. It explores a facet of non-narrative visual expression within Jewish visual culture. The chronologically and geographically disconnected depictions of similar paired scrolled patterns on Jewish artifacts exemplify the process of creating and recreating symbolic meanings based on the mimetic qualities of an image. In their various renditions and contexts, volutes in their resemblance to growing plant branches enacted visual references to the vital powers of nature as a promise for resurrection and a metaphor for the vitality of Judaism and the Mosaic law. The Jewish manifestations of symbolic scrolls emerged in surroundings that maintained classical architectural vocabulary containing volutes and shared the Christian topos of the flourishing cross visualized in its arboreal or vegetative renditions. This very act of construing of a non-narrative visual sign of a couple of spirals aims at reaffirming visual evidence as a meaningful source in its own right.

Grapheme-Color Synesthesia and Its Connection to Memory.

Synesthesia is the involuntary association of different senses, where individuals experience one sensory modality in response to the stimulation of another. For example, a synesthete may perceive colors when reading certain numbers or associate specific tastes with particular words. Synesthesia manifests differently for individuals grouping the condition in subcategories such as grapheme-color, sound-to-color, lexical-gustatory, mirror-touch, and much more. This review covers grapheme-color synesthesia, described as the involuntary perception of specific colors or color associations when seeing or thinking about certain letters, numbers, or symbols. This review explores the performance of declarative memory tasks in individuals with grapheme-color synesthesia. A comprehensive search of controlled trials published between 2014 to 2024 was conducted through PubMed and Google Scholar databases. In Google Scholar, the search terms grapheme-color synesthesia, grapheme-color synaesthesia, and memory were used. In PubMed, additional MeSH (Medical Subject Headings) terms were used which included grapheme-color synesthesia and memory. Studies that measured declarative memory and grapheme-color synesthesia were included yielding a total of seven controlled trials. Grapheme-color synesthetes demonstrated advanced performance in declarative memory tasks; however, this may not have any clinical significance. Grapheme-color synesthetes demonstrated a better performance in their ability to recall colors, but not as much recalling words. Synesthetes were shown to outperform non-synesthetes in visual memory tasks. Synesthetes showed better recall of paired patterns, shape-color associations, and visual grids compared to control groups, but the influence of synesthesia on word memory remains unclear. Future research should consider adding control for confounding factors, collaborating with other institutions, and increasing sample size.

Analysis of Stokes singularities using a lateral shear interferometer

Polarization and Poincaré singularities in the optical fields can be studied by analyzing the phase singularities of mathematically constructed Stokes vector fields. The wider applicability of the Stokes construction is found by exploring the generation and detection methods for various types of Stokes singularities and their analysis. Here, we detect and analyze all forms of the Stokes singularities through lateral shear interferometry. Specifically, the projections of a Stokes singularity on three pairs of orthogonal polarization basis states, defined by the eigen polarization states of Pauli’s matrices, are analyzed through unique fork patterns in the shearogram pairs. These interference patterns also provide the topological indices of the singularities. Such a self-referencing interferometric method also helps to remove the degeneracy in the Stokes index and polarization. Through both, simulations and experiments, we have analyzed specific beams represented by higher order Poincaré sphere and hybrid order Poincaré sphere topological constructs.

Using rDNA ITS2 barcoding to identify kratom (Mitragyna speciosa) from the genus Mitragyna and Neolamarckia cadamba.

This study collected 80 samples of suspected kratom plant powder. A polymerase chain reaction sequence analysis was conducted using two sets of DNA barcode primers for plant ribosomal (r)DNA internal transcribed spacers (ITSs), namely, ITS3/ITS4 and ITS-p3/ITS-u4. Among the 80 samples, 40 were analyzed using the ITS3/ITS4 primer pair, and then DNA sequences were subjected to a National Center for Biotechnology Information-Basic Local Alignment Search Tool (NCBI-BLAST) comparison. Results showed that 29 samples had a 100% match (364/364) with Mitragyna speciosa (kratom), and 6 samples had a 99.73% match (363/364) with M. speciosa, whereas 5 samples had disordered and unreadable sequences. The 5 unreadable samples and an additional 40 suspected kratom samples were then analyzed using the ITS-p3/ITS-u4 primer pair, followed by an NCBI-BLAST comparison. Among these, 32 samples had a 100% match (404/404) with M. speciosa, and 11 samples had a 99.75% match (403/404) with M. speciosa. Among the samples with sequences matching M. speciosa, three distinct types were observed (no variance/404, 287M/404, and 287A/404). One sample had a 99.51% match (404/406) with Neolamarckia cadamba, and another sample had a sequencing length of 305bp, with 25 positions showing mixed base pairs, indicating a mixture of different species. Analysis of the mixed base pair pattern suggested a possible mixture of M. speciosa and N. cadamba. Actually, M. speciosa and N. cadamba have very similar external morphologies. This indicates that the ITS-p3/ITS-u4 primer pair is effective in distinguishing mixtures of M. speciosa and N. cadamba and is thus more suitable than ITS3/ITS4 for identifying and analyzing samples of suspected kratom plant powder.

DeepIMAGER: Deeply Analyzing Gene Regulatory Networks from scRNA-seq Data.

Understanding the dynamics of gene regulatory networks (GRNs) across diverse cell types poses a challenge yet holds immense value in unraveling the molecular mechanisms governing cellular processes. Current computational methods, which rely solely on expression changes from bulk RNA-seq and/or scRNA-seq data, often result in high rates of false positives and low precision. Here, we introduce an advanced computational tool, DeepIMAGER, for inferring cell-specific GRNs through deep learning and data integration. DeepIMAGER employs a supervised approach that transforms the co-expression patterns of gene pairs into image-like representations and leverages transcription factor (TF) binding information for model training. It is trained using comprehensive datasets that encompass scRNA-seq profiles and ChIP-seq data, capturing TF-gene pair information across various cell types. Comprehensive validations on six cell lines show DeepIMAGER exhibits superior performance in ten popular GRN inference tools and has remarkable robustness against dropout-zero events. DeepIMAGER was applied to scRNA-seq datasets of multiple myeloma (MM) and detected potential GRNs for TFs of RORC, MITF, and FOXD2 in MM dendritic cells. This technical innovation, combined with its capability to accurately decode GRNs from scRNA-seq, establishes DeepIMAGER as a valuable tool for unraveling complex regulatory networks in various cell types.

A multivariate to multivariate approach for voxel-wise genome-wide association analysis.

The joint analysis of imaging-genetics data facilitates the systematic investigation of genetic effects on brain structures and functions with spatial specificity. We focus on voxel-wise genome-wide association analysis, which may involve trillions of single nucleotide polymorphism (SNP)-voxel pairs. We attempt to identify underlying organized association patterns of SNP-voxel pairs and understand the polygenic and pleiotropic networks on brain imaging traits. We propose a bi-clique graph structure (ie, a set of SNPs highly correlated with a cluster of voxels) for the systematic association pattern. Next, we develop computational strategies to detect latent SNP-voxel bi-cliques and an inference model for statistical testing. We further provide theoretical results to guarantee the accuracy of our computational algorithms and statistical inference. We validate our method by extensive simulation studies, and then apply it to the whole genome genetic and voxel-level white matter integrity data collected from 1052 participants of the human connectome project. The results demonstrate multiple genetic loci influencing white matter integrity measures on splenium and genu of the corpus callosum.

Understanding the Consumption of Plant-Based Drink in South Korea: Drinking Situations and Food Pairings

This study aims to investigate how consumption situations, consumer characteristics and food pairing patterns differ based on milk selection, namely cow milk and plant-based drink, using food diary data (117,728 cases). The consumer characteristics and drinking situations of milk and plant-based drink were analyzed using probit model, and food pairing patterns of milk and plant-based drink were analyzed using decision tree analysis. Plant-based drink consumers are more likely to be older, female, and have lower incomes, compared to milk consumers. Consumers are more likely to have plant-based drink on the move. Plant-based drink is mainly consumed with eggs, bananas, sweet potatoes, and nuts, while milk is consumed with cereals, bananas, and bread. It provides marketers with a stepping stone for developing marketing strategies associated with plant-based drink. This is the first empirical study to compare food pairing patterns between milk and plant-based drink, extending the scope of food pairing.

Entangled photon-pair generation in nonlinear thin-films

Abstract We develop a fully vectorial and non-paraxial formalism to describe spontaneous parametric down-conversion in nonlinear thin films. The formalism is capable of treating slabs with a sub-wavelength thickness, describe the associated Fabry–Pérot effects, and even treat absorptive nonlinear materials. With this formalism, we perform an in-depth study of the dynamics of entangled photon-pair generation in nonlinear thin films, to provide a needed theoretical understanding for such systems that have recently attracted much experimental attention as sources of photon pairs. As an important example, we study the far-field radiation properties of photon pairs generated from a high-refractive-index nonlinear thin-film with zinc-blende structure that is deposited on a linear low-refractive-index substrate. In particular, we study the thickness-dependent effect of Fabry–Pérot interferences on the far-field radiation pattern of the photon pairs. We also pay special attention to study of entanglement generation, and find the conditions under which maximally polarization-entangled photon pairs can be generated and detected in such nonlinear thin-films.

Hybrid Clot Histomic-Transcriptomic Models Predict Functional Outcome After Mechanical Thrombectomy in Acute Ischemic Stroke.

Histologic and transcriptomic analyses of retrieved stroke clots have identified features associated with patient outcomes. Previous studies have demonstrated the predictive capacity of histology or expression features in isolation. Few studies, however, have investigated how paired histologic image features and expression patterns from the retrieved clots can improve understanding of clot pathobiology and our ability to predict long-term prognosis. We hypothesized that computational models trained using clot histomics and mRNA expression can predict early neurological improvement (ENI) and 90-day functional outcome (modified Rankin Scale Score, mRS) better than models developed using histological composition or expression data alone. We performed paired histological and transcriptomic analysis of 32 stroke clots. ENI was defined as a delta-National Institutes of Health Stroke Score/Scale > 4, and a good long-term outcome was defined as mRS ≤2 at 90 days after procedure. Clots were H&E-stained and whole-slide imaged at 40×. An established digital pathology pipeline was used to extract 237 histomic features and to compute clot percent composition (%Comp). When dichotomized by either the ENI or mRS thresholds, differentially expressed genes were identified as those with absolute fold-change >1.5 and q < 0.05. Machine learning with recursive feature elimination (RFE) was used to select clot features and evaluate computational models for outcome prognostication. For ENI, RFE identified 9 optimal histologic and transcriptomic features for the hybrid model, which achieved an accuracy of 90.8% (area under the curve [AUC] = 0.98 ± 0.08) in testing and outperformed models based on histomics (AUC = 0.94 ± 0.09), transcriptomics (AUC = 0.86 ± 0.16), or %Comp (AUC = 0.70 ± 0.15) alone. For mRS, RFE identified 7 optimal histomic and transcriptomic features for the hybrid model. This model achieved an accuracy of 93.7% (AUC = 0.94 ± 0.09) in testing, also outperforming models based on histomics (AUC = 0.90 ± 0.11), transcriptomics (AUC = 0.55 ± 0.27), or %Comp (AUC = 0.58 ± 0.16) alone. Hybrid models offer improved outcome prognostication for patients with stroke. Identified digital histology and mRNA signatures warrant further investigation as biomarkers of patient functional outcome after thrombectomy.

Comprehensive analysis and characterization of glycan pairing in therapeutic antibodies and Fc-containing biotherapeutics: Addressing current limitations and implications for N-glycan impact

N-glycosylation of the Fc part is a (critical) quality attribute of therapeutic antibodies and Fc-containing biotherapeutics, that impacts their stability, immunogenicity, pharmacokinetics, and effector functions. Current glycosylation analysis methods focus on the absolute amounts of glycans, neglecting the apparent glycan distribution over the entirety of proteins. The combination of the two Fc N-glycans, herein referred to as glyco-pair, therefore remains unknown, which is a major drawback for N-glycan impact assessment. This study presents a comprehensive workflow for the analysis and characterization of Fc N-glycan pairing in biotherapeutics, addressing the limitations of current glycosylation analysis methods. The applicability of the method across various biotherapeutic proteins including antibodies, bispecific antibody formats, and a Fc-Fusion protein is demonstrated, and the impact of method conditions on glycan pairing analysis is highlighted. Moreover, the influence of the molecular format, Fc backbone, production process, and cell line on glycan pairing pattern was investigated. The results underscore the significance of comprehensive glycan pairing analysis to accurately assess the impact of N-glycans on important product quality attributes of therapeutic antibodies and Fc-containing biotherapeutics.

Types and Fecundity of Neotenic Reproductives Produced in 5-Year-Old Orphaned Colonies of the Drywood Termite, Cryptotermes domesticus (Blattodea: Kalotermitidae)

Orphaned colonies of Cryptotermes domesticus readily produce replacement reproductives and continue propagation. In this study, we aimed to investigate the production and fecundity of neotenic reproductives in 5-year-old colonies of C. domesticus after orphaning. All 15 experimental colonies were successfully re-established by the neotenic reproductive pair. Three types of neotenic reproductives with various wing-bud lengths were observed: type I with micro wing buds, type II with short wing buds, and type III with long wing buds. Four patterns of pairs made up of these neotenics, namely, type I + type II, type I + type III, type II + type II, and type II + type III, exhibited reproductive capacities similar to those of the primary reproductive pair. We speculated that these neotenic reproductives were derived from various nymphal instars. The 5-year-old colonies had three instars of nymphs, with the majority being in the second instar, followed by the first. Thus, the combination of neotenic reproductives with short wing buds and micro wing buds was the dominant differentiation pathway of the orphaned colonies. After the removal of the original primary reproductive pair, the nymphs matured into neotenic reproductives and took over reproduction in the colony in 107.40 ± 15.18 days. This study highlights the importance of quarantine and routine inspection of wood, as well as the significance of early prevention and control of C. domesticus infestation in wood. Moreover, this study confirms the high differentiation and reproductive capacities of C. domesticus.

Two-flavor Color Superconducting Quark Stars May Not Exist

Large uncertainties in the determinations of the equation of state of dense stellar matter allow for the intriguing possibility that the bulk quark matter in beta equilibrium might be the true ground state of the matter at zero pressure. Also, quarks will form Cooper pairs very readily since the dominant interaction between quarks is attractive in some channels. As a result, quark matter will generically exhibit color superconductivity, with the favored pairing pattern at intermediately high densities being two-flavor pairing. In the light of several possible candidates for such self-bound quark stars, including the very low-mass central compact object in supernova remnant HESS J1731-347 reported recently, we carry out a one-field theoretic model, the Nambu–Jona–Lasinio model, to investigate the stability of the beta-stable two-flavor color superconducting (2SC) phase of quark matter, but find no physically allowed parameter space for the existence of 2SC quark stars.

Markov Blankets and Mirror Symmetries-Free Energy Minimization and Mesocortical Anatomy.

A theoretical account of development in mesocortical anatomy is derived from the free energy principle, operating in a neural field with both Hebbian and anti-Hebbian neural plasticity. An elementary structural unit is proposed, in which synaptic connections at mesoscale are arranged in paired patterns with mirror symmetry. Exchanges of synaptic flux in each pattern form coupled spatial eigenmodes, and the line of mirror reflection between the paired patterns operates as a Markov blanket, so that prediction errors in exchanges between the pairs are minimized. The theoretical analysis is then compared to the outcomes from a biological model of neocortical development, in which neuron precursors are selected by apoptosis for cell body and synaptic connections maximizing synchrony and also minimizing axonal length. It is shown that this model results in patterns of connection with the anticipated mirror symmetries, at micro-, meso- and inter-arial scales, among lateral connections, and in cortical depth. This explains the spatial organization and functional significance of neuron response preferences, and is compatible with the structural form of both columnar and noncolumnar cortex. Multi-way interactions of mirrored representations can provide a preliminary anatomically realistic model of cortical information processing.

Effects of ABC Running and Bodyweight Training combination: A case study on the speed of hurdling athletes

The use of exercise in sports must be right on target on the physical component needed. Similarly, hurdling not only utilizes speed, but requires strength to get maximum results. The purpose of the study was to analyze the effects arising from the use of Running ABC exercises combined with Bodyweight Training. The study design used a two-group post-test pre-test of 22 trained male subjects enrolled in the study. The first stage includes initial tests to see initial ability and as a basis for determining the treatment group which is divided into two groups with ordinally paired patterns A-B-B-A for group alignment. Group 1 was given Running ABC exercises, and Group 2 Running ABC exercises were combined with Bodyweight Training. Each group was trained for 16 meetings. The test instrument used is a 50yard sprint over obstacles by measuring the speed of the athlete's travel time. The data analysis technique used was a difference test with IBM SPSS 24 statistics. The results of the study were obtained from data analysis there was a significant difference between group 1 who only used Running ABC exercises with group 2 who used Running ABC exercises combined with Bodyweight Training exercises with a difference value of 0.043&lt;0.05. This means that running abc (agility, balance, and coordination) and body weight training are significant in increasing the running speed of hurdling athletes, but combining body weight training and running abc (agility, balance and coordination) is more effective than training using only one type of physical component exercise. By combining running abc exercises and body weight training, trainers can improve their athletes' overall fitness and technique, effectively improving balance, coordination, and functional strength. Keyword: Exercise, Bodyweight Training, Running ABC, Hurdles.

The Effect of Basic Passing Movements In Volleyball Through Playing Bouncing Ball With A Pair Pattern

This research aims to determine the effect of applying the method quantitatively experimentally with One Group Pretest and Post Test Design. in improving basic volleyball passing techniques at SDN 8 Cicalengka, Cicalengka District, Bandung Regency. Data collection techniques from the pre-test sig normality test = 0.2 Sig value (0.2) &gt; 0.05, the conclusion is that the pretest data is normally distributed. Post-test sig data = 0.11 Sig value (0.11) &gt; 0.05, in conclusion the posttest data is normally distributed, homogeneity test Sig = 0.32 After carrying out a homogeneity test using SPSS, a sig value of (0.32) is obtained, meaning that the sig value (0.6) &gt; 0.05 then the data The test is homogeneous, and the following is the T test H0: There is no result/influence. HI: There is a result/influence. If the sig value is &gt; 0.05 then the HI is rejected. If the sig value is &lt; 0.05 then the HI is accepted. Sig value: 0.001. As for the results of the paired pattern data from the pre-test and post-test normality tests, the results of the homogeneity test using SPSS obtained a sig value of (0.23), meaning that the sig value is (0.6) &gt; 0.05, so the data is homogeneous, and as for the T test, there is H0: None HI results/influence: There are results/influence If the sig value is &gt; 0.05 then the HI is Rejected If the sig value is &lt; 0.05 then the HI is Accepted.

Multi-Point Control for Face-Milled Spiral Bevel Gears with a Predesigned Fourth-Order Motion Curve

This paper presents an ultimate motion methodology of a face-milling spiral bevel gear pair to synthesize the mating tooth surfaces with a predesigned fourth-order motion curve. The methodology is to control some contact points along the contact path in the process of tooth contact analysis via application of an extended local synthesis which permits some transmission errors rather than zero at the concerned contact point. The modified offset motion correction is selected to demonstrate the proposed methodology. Applied torque corresponding to an elastic approach of 0.00635 mm at the mean contact point is calculated and the loaded tooth contact analysis is performed. Numerical results show that the extended local synthesis can effectively control the transmission errors on the predesigned fourth-order motion curve at arbitrarily predesigned contact points along the contact path of the spiral bevel gear pair. The tooth contact pattern for the actual tooth pair is scattered into three segments since the rotational motion of the driven gear at any instant angular position is dependent on the tooth pair with the least transmission error among the three adjacent tooth pairs. The actual tooth contact patterns of the spiral bevel gear pair become continuous when meshing tooth surfaces are elastically deformed.

Interpretable CRISPR/Cas9 off-target activities with mismatches and indels prediction using BERT

Off-target effects of CRISPR/Cas9 can lead to suboptimal genome editing outcomes. Numerous deep learning-based approaches have achieved excellent performance for off-target prediction; however, few can predict the off-target activities with both mismatches and indels between single guide RNA (sgRNA) and target DNA sequence pair. In addition, data imbalance is a common pitfall for off-target prediction. Moreover, due to the complexity of genomic contexts, generating an interpretable model also remains challenged. To address these issues, firstly we developed a BERT-based model called CRISPR-BERT for enhancing the prediction of off-target activities with both mismatches and indels. Secondly, we proposed an adaptive batch-wise class balancing strategy to combat the noise exists in imbalanced off-target data. Finally, we applied a visualization approach for investigating the generalizable nucleotide position-dependent patterns of sgRNA-DNA pair for off-target activity. In our comprehensive comparison to existing methods on five mismatches-only datasets and two mismatches-and-indels datasets, CRISPR-BERT achieved the best performance in terms of AUROC and PRAUC. Besides, the visualization analysis demonstrated how implicit knowledge learned by CRISPR-BERT facilitates off-target prediction, which shows potential in model interpretability. Collectively, CRISPR-BERT provides an accurate and interpretable framework for off-target prediction, further contributes to sgRNA optimization in practical use for improved target specificity in CRISPR/Cas9 genome editing. The source code is available at https://github.com/BrokenStringx/CRISPR-BERT.