Three-dimensional wall-thickness distributions of unruptured intracranial aneurysms characterized by micro-computed tomography.

Aneurysmal rupture is associated with wall thinning, but the mechanism is poorly understood. This study aimed to characterize the three-dimensional wall-thickness distributions of unruptured intracranial aneurysms. Five aneurysmal tissues were investigated using micro-computed tomography. First, the wall thickness was related to the aneurysmal wall appearances during surgery. The median wall thicknesses of the translucent and non-translucent walls were 50.56 and 155.93 µm, respectively (p < 0.05) with significant variation in the non-translucent wall thicknesses (p < 0.05). The three-dimensional observations characterized the spatial variation of wall thicknesses. Thin walls showed a uniform thickness profile ranging from 10 to 40 µm, whereas thick walls presented a peaked thickness profile ranging from 300 to 500 µm. In transition walls, the profile undulated due to the formation of focal thin/thick spots. Overall, the aneurysmal wall thicknesses were strongly site-dependent and spatially varied by 10 to 40 times within individual cases. Aneurysmal walls are exposed to wall stress driven by blood pressure. In theory, the magnitude of wall stress is inversely proportional to wall thickness. Thus, the observed spatial variation of wall thickness may increase the spatial variation of wall stress to a similar extent. The irregular wall thickness may yield stress concentration. The observed thin walls and focal thin spots may be caused by excessive wall stresses at the range of mechanical failure inducing wall injuries, such as microscopic tears, during aneurysmal enlargement. The present results suggested that blood pressure (wall stress) may have a potential of acting as a trigger of aneurysmal wall injury.

Accessory fragment migration in a professional baseball player with bipartite patella: A case report.

INTRODUCTION: Bipartite patella (BP) is usually recognized as an incidental radiographic finding. Therefore, no reports have observed the process of accessory fragment migration. We present the case of a professional baseball pitcher with significant migration of the fragment during follow-up. PRESENTATION OF CASE: A 26-year-old man was diagnosed with symptomatic BP and underwent conservative therapy. Eleven months later, he was unable to play baseball because of gradually worsening knee pain without obvious trauma. On radiographs, the accessory fragment which had located at the superolateral pole 11 months earlier migrated posterolaterally. The diagnosis of Saupe's type III BP was established, and open excision of the accessory fragment was performed. Postoperatively, full-weight-bearing walking and range-of-motion exercises were started the day after surgery. Three months after surgery, he could pitch with all his power without pain. DISCUSSION: Since our patient was a professional baseball right-handed pitcher who needed to step strongly on his left knee during pitching, strong traction force from the vastus lateralis was likely to have been repeatedly applied to the accessory fragment. It might lead to migration of the accessory fragment. The open excision of the accessory fragment was performed because the accessory fragment had migrated away from the patella body. CONCLUSION: We report a case of professional baseball player with symptomatic BP, in which case the chronological migration of the accessory fragment was observed without obvious trauma. When the accessory fragment is identified without obvious trauma, one of the differential diseases could be a BP.

A New Regression Model for Depression Severity Prediction Based on Correlation among Audio Features Using a Graph Convolutional Neural Network.

Recent studies have revealed mutually correlated audio features in the voices of depressed patients. Thus, the voices of these patients can be characterized based on the combinatorial relationships among the audio features. To date, many deep learning-based methods have been proposed to predict the depression severity using audio data. However, existing methods have assumed that the individual audio features are independent. Hence, in this paper, we propose a new deep learning-based regression model that allows for the prediction of depression severity on the basis of the correlation among audio features. The proposed model was developed using a graph convolutional neural network. This model trains the voice characteristics using graph-structured data generated to express the correlation among audio features. We conducted prediction experiments on depression severity using the DAIC-WOZ dataset employed in several previous studies. The experimental results showed that the proposed model achieved a root mean square error (RMSE) of 2.15, a mean absolute error (MAE) of 1.25, and a symmetric mean absolute percentage error of 50.96%. Notably, RMSE and MAE significantly outperformed the existing state-of-the-art prediction methods. From these results, we conclude that the proposed model can be a promising tool for depression diagnosis.

Multi-Input Speech Emotion Recognition Model Using Mel Spectrogram and GeMAPS.

The existing research on emotion recognition commonly uses mel spectrogram (MelSpec) and Geneva minimalistic acoustic parameter set (GeMAPS) as acoustic parameters to learn the audio features. MelSpec can represent the time-series variations of each frequency but cannot manage multiple types of audio features. On the other hand, GeMAPS can handle multiple audio features but fails to provide information on their time-series variations. Thus, this study proposes a speech emotion recognition model based on a multi-input deep neural network that simultaneously learns these two audio features. The proposed model comprises three parts, specifically, for learning MelSpec in image format, learning GeMAPS in vector format, and integrating them to predict the emotion. Additionally, a focal loss function is introduced to address the imbalanced data problem among the emotion classes. The results of the recognition experiments demonstrate weighted and unweighted accuracies of 0.6657 and 0.6149, respectively, which are higher than or comparable to those of the existing state-of-the-art methods. Overall, the proposed model significantly improves the recognition accuracy of the emotion "happiness", which has been difficult to identify in previous studies owing to limited data. Therefore, the proposed model can effectively recognize emotions from speech and can be applied for practical purposes with future development.

Classification of Depression and Its Severity Based on Multiple Audio Features Using a Graphical Convolutional Neural Network.

Audio features are physical features that reflect single or complex coordinated movements in the vocal organs. Hence, in speech-based automatic depression classification, it is critical to consider the relationship among audio features. Here, we propose a deep learning-based classification model for discriminating depression and its severity using correlation among audio features. This model represents the correlation between audio features as graph structures and learns speech characteristics using a graph convolutional neural network. We conducted classification experiments in which the same subjects were allowed to be included in both the training and test data (Setting 1) and the subjects in the training and test data were completely separated (Setting 2). The results showed that the classification accuracy in Setting 1 significantly outperformed existing state-of-the-art methods, whereas that in Setting 2, which has not been presented in existing studies, was much lower than in Setting 1. We conclude that the proposed model is an effective tool for discriminating recurring patients and their severities, but it is difficult to detect new depressed patients. For practical application of the model, depression-specific speech regions appearing locally rather than the entire speech of depressed patients should be detected and assigned the appropriate class labels.

End-to-End Convolutional Neural Network Model to Detect and Localize Myocardial Infarction Using 12-Lead ECG Images without Preprocessing.

In recent years, many studies have proposed automatic detection and localization techniques for myocardial infarction (MI) using the 12-lead electrocardiogram (ECG). Most of them applied preprocessing to the ECG signals, e.g., noise removal, trend removal, beat segmentation, and feature selection, followed by model construction and classification based on machine-learning algorithms. The selection and implementation of preprocessing methods require specialized knowledge and experience to handle ECG data. In this paper, we propose an end-to-end convolutional neural network model that detects and localizes MI without such complicated multistep preprocessing. The proposed model executes comprehensive learning for the waveform features of unpreprocessed raw ECG images captured from 12-lead ECG signals. We evaluated the classification performance of the proposed model in two experimental settings: ten-fold cross-validation where ECG images were split randomly, and two-fold cross-validation where ECG images were split into one patient and the other patients. The experimental results demonstrate that the proposed model obtained MI detection accuracies of 99.82% and 93.93% and MI localization accuracies of 99.28% and 69.27% in the first and second settings, respectively. The performance of the proposed method is higher than or comparable to that of existing state-of-the-art methods. Thus, the proposed model is expected to be an effective MI diagnosis tool that can be used in intensive care units and as wearable technology.

Pressurized carbon dioxide lavage reduces the incidence of a radiolucent line around the tibial component two years after total knee arthroplasty.

INTRODUCTION: In cemented total knee arthroplasty (TKA), pressurized carbon dioxide (CO2) lavage prior to cement fixation can eliminate debris at the bone-cement interface and is considered effective for increasing cement penetration and preventing aseptic loosening. Regarding the risk of a preliminary diagnosis of implant loosening, a radiolucent line (RLL) is a valuable sign. The purpose of this study was to compare the incidence of a tibial RLL at 2 years after TKA with and without pressurized CO2 lavage. METHODS: This is a retrospective study. One hundred knees from 98 patients were enrolled in this study. TKA was performed without pressurized CO2 lavage (CO2- group) for the first 47 knees, and with pressurized CO2 lavage (CO2+ group) for the next 53 knees. The depth of cement penetration was measured just after surgery, and the incidence of tibial RLL > 2 mm at 2 years after TKA was determined. RESULTS: Significant differences between groups were not seen regarding pre- and postoperative clinical factors. The depth of cement penetration in each area was significantly higher in the CO2+ group. The frequency of knees with RLL > 2 mm was significantly lower in the CO2+ group than in the CO2- group (p < 0.001). CONCLUSIONS: Pressurized CO2 lavage improved cement penetration and decreased the incidence of tibial RLL > 2 mm at 2 years after TKA.

Association between magnetic resonance imaging characteristics and pathological findings in entire posterior cruciate ligament with mucoid degeneration.

Magnetic resonance imaging (MRI) findings of a tram-track appearance and celery stalk appearance in mucoid degeneration of the cruciate ligament are valuable; however, their pathological basis is unclear. Because these appearances are generally seen throughout the entire ligament, the association between MRI findings and pathological findings must be verified in specimens of the whole degenerated ligament, including the ligamentous attachments to bone. We herein report two cases of mucoid degeneration of the posterior cruciate ligament with osteoarthritis of the knee requiring total knee arthroplasty. The entire degenerated ligament, including the ligamentous attachments to bone, was removed and pathologically evaluated. On pathological examination, the central portion of the lesion showed typical mucoid degeneration, whereas the marginal and adherent portions showed normal ligament tissue, consistent with a tram-track appearance on T2-weighted MRI. The fibrous normal ligament tissues in the longitudinal direction in regions of mucoid degeneration were consistent with a celery stalk appearance on T2-weighted MRI. No mucoid degeneration was found in the attachment area. The tram-track appearance and celery stalk appearance of mucoid degeneration on MRI can be explained by the pathological findings.

Identifying Voice Individuality Unaffected by Age-Related Voice Changes during Adolescence.

Identifying voice individuality is a key issue in the biometrics field. Previous studies have demonstrated that voice individuality is caused by differences in the shape and size of the vocal organs; however, these studies did not discuss voice individuality over a long term that includes periods of voice change. Therefore, we focus on adolescence (early teens to early twenties), which includes voice changes due to growth of vocal organs, and we reveal invariant voice individuality over a long period. In this study, the immature and mature periods during vocal organ development were defined as unstable and stable periods, respectively. We performed speaker verification tests across these two periods and evaluated voice features that are common to these periods using Fisher's F-ratio. The results of the speaker verification test demonstrated a verification accuracy of 60% or more in most cases, and the results of the evaluation using Fisher's F-ratio demonstrated that robust voice individuality existed in the frequency regions of 1-2 kHz and 4-6 kHz regardless of the period. These results suggest that voice individuality is unaffected by age-related changes over the long term, including adolescence.

Missing Value Imputation Method for Multiclass Matrix Data Based on Closed Itemset.

Handling missing values in matrix data is an important step in data analysis. To date, many methods to estimate missing values based on data pattern similarity have been proposed. Most previously proposed methods perform missing value imputation based on data trends over the entire feature space. However, individual missing values are likely to show similarity to data patterns in local feature space. In addition, most existing methods focus on single class data, while multiclass analysis is frequently required in various fields. Missing value imputation for multiclass data must consider the characteristics of each class. In this paper, we propose two methods based on closed itemsets, CIimpute and ICIimpute, to achieve missing value imputation using local feature space for multiclass matrix data. CIimpute estimates missing values using closed itemsets extracted from each class. ICIimpute is an improved method of CIimpute in which an attribute reduction process is introduced. Experimental results demonstrate that attribute reduction considerably reduces computational time and improves imputation accuracy. Furthermore, it is shown that, compared to existing methods, ICIimpute provides superior imputation accuracy but requires more computational time.

Not Using a Tourniquet May Reduce the Incidence of Asymptomatic Deep Venous Thrombosis After ACL Reconstruction: An Observational Study.

BACKGROUND: Deep venous thrombosis (DVT) and pulmonary embolism are serious potential complications after anterior cruciate ligament reconstruction (ACLR). Little is known about the influence of tourniquet use on the incidence of DVT after ACLR. PURPOSE: To compare the incidence of DVT after ACLR with and without the use of a tourniquet. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: Between November 2018 and May 2020, a total of 60 consecutive ACLRs in 60 patients, including 7 revision surgeries, were performed without tourniquet use at our hospital and were enrolled in this study (T- group). In addition, 55 consecutive ACLRs in 55 patients, including 10 revision surgeries, were performed with tourniquet use between April 2017 and September 2018 and were enrolled as the control group (T+ group). DVT was diagnosed using ultrasonography of both legs performed preoperatively and at postoperative week 1. The incidence of postoperative DVT was compared between the T- and T+ groups. Logistic regression analysis was performed to evaluate the effect of older age (≥40 vs <40 years) and tourniquet use on the occurrence of DVT. RESULTS: No DVTs were detected preoperatively. The incidence of postoperative DVT was significantly lower in the T- group compared with the T+ group (1 patient [1.7%] vs 9 patients [16.4%]; P = .005). All patients with DVT were asymptomatic. Although the mean operative time was not significantly different (80.8 minutes in the T+ group vs 78.5 minutes in the T- group; P = .461), the mean blood loss from the drain was significantly lower in the T- group than in the T+ group (149.9 vs 201.9 mL; P < .001). Age ≥40 years and tourniquet use were significantly related to the occurrence of DVT (odds ratio, 8.3 [95% CI, 1.9-36.8]; P = .005; and odds ratio, 8.8 [95% CI, 1.0-75.3]; P = .047, respectively). CONCLUSION: ACLRs performed without tourniquet resulted in a significantly lower incidence of DVT after ACLR and significantly less bleeding from drains. If adequate visibility of the surgical field is obtained, ACLR without tourniquet use may reduce the incidence of DVT.

Preliminary Clinical Outcome of One-level Mobi-C Total Disc Replacement in Japanese Population.

INTRODUCTION: In 2018, the first Mobi-CⓇ total disk replacement (TDR) case was performed in Japan. In this study, we examined the preliminary clinical outcome of Mobi-CⓇ for degenerative cervical spine disease. METHODS: We examined 24 consecutive patients who underwent 1-level TDR after 2018 and followed up for more than 6 months after surgery. The evaluation criteria included age, gender, diagnosis, follow-up period, surgical level, implant size, surgery time, intraoperative bleeding volume, complications, revision surgery, imaging findings, JOA score, and various questionnaires. RESULTS: The mean age was 52.7 years, 13 males and 11 females. There were 15 cases of cervical disk herniation and 9 cases of cervical spondylosis. The mean follow-up period was 17.4 months. Surgical levels were C3/4 in 4 cases, C4/5 in 2 cases, C5/6 in 16 cases, and C6/7 in 2 cases. The mean operation time was 138.5 minutes, the amount of intraoperative bleeding was 32.1 ml, and there were no serious intraoperative complications. The range of motion of the affected level increased significantly, from 6.6 degrees preoperatively to 12.2 degrees at final follow-up. No patients required revision surgery at final follow-up, and there were no cases of heterotopic ossification or adjacent segment disease. One patient exhibited radiculopathy due to mild subsidence 1 year after surgery, and 1 had asymptomatic contact of device plates. Preoperative and final JOA scores improved from 11.7 to 15.8 points, and NRS improved from 4.3 to 1.3 points for neck pain and 4.3 to 1.7 points for arm pain. Preoperative and final NDI improved from 39.7% to 14.0%, and EQ-5D improved from 0.602 to 0.801. CONCLUSIONS: The short-term treatment outcomes of Mobi-CⓇ TDR were generally favorable. Spine surgeons should comply with guidelines when introducing this procedure and strive to adopt this new technology in Japan.

Suture Anchor Repair With Fully Threaded Knotless Anchors for Quadriceps Tendon Rupture Resulted in Favorable Outcomes After 2 Years.

PURPOSE: To investigate clinical outcomes over 2 years in cases of quadriceps tendon rupture (QTR) that were surgically treated using fully threaded knotless anchors. METHODS: A total of four knees in four male patients with QTR repaired with fully threaded knotless anchors at our hospital from November 2017 to January 2019 were enrolled. Mean patient age at surgery was 65.3 years (range: 61-70 years). Intraoperatively, stability of the sutured site was confirmed by knee flexion to 90°. Full weight walking with the orthosis in extension was commenced on the seventh postoperative day. Surgical findings, pathologies of the ruptured quadriceps tendons, and postoperative clinical outcomes were evaluated in all patients. RESULTS: The QTR was complete in three cases and partial in one. Average surgical duration was 58.5 (range: 49-74) minutes. Pathological evaluation revealed hyaline degeneration with granulation of the quadriceps tendon in two cases. No complications, such as infection and rerupture, occurred. Magnetic resonance imaging performed 1 year postoperatively confirmed complete healing of the repaired tendon. The mean follow-up period was 35.5 months (range: 24-46 months). None of the patients had extension lag of the knee, and mean Lysholm score and range of flexion were 95.3 (range: 85-100) and 141.3° (range: 140-145°), respectively, at the final follow-up. CONCLUSIONS: Clinical outcomes were favorable in all cases, including two cases with pathological degenerative changes. Suture anchor repair with fully threaded knotless anchors can be considered a minimally invasive and effective method for QTR, with sufficient strength to allow early rehabilitation.

A clinical study comparing ultrasound-measured pyloric antrum cross-sectional area to computed tomography-measured gastric content volume to detect high-risk stomach in supine patients undergoing emergency abdominal surgery.

The main aim of this study was to assess whether the ultrasound examination and measurement of the pyloric antral cross-sectional area (antral-CSA) in the supine position could be useful to diagnose a full stomach using a computed tomography (CT) as a comparator in emergency patients. Immediately before general anesthesia induction in patients undergoing emergency abdominal surgery, antral-CSA was measured and the volume of the gastric contents was evaluated via ultrasound in the supine position. Gastric content volume was also calculated from a CT image taken prior to the operation. The primary outcome of this study was to determine the antral-CSA threshold of the "high-risk stomach" defined as the presence of solid/thick fluid and/or gastric content volume > 1.5 mL/kg. The secondary outcome was to evaluate the correlation between gastric content volume calculated by CT and antral-CSA. Thirty-nine patients provided consent and were included. Ten patients had gastric contents over 1.5 mL/kg, and 18 patients showed solid contents/thick fluids. The median [IQR] antral-CSA and gastric content volume were 3.82 [2.74-5.07] cm2 and 0.32 [0.09-2.08] mL/kg, respectively. The antral-CSA cutoff value of "high-risk stomach" was 3.01 cm2. This value had a sensitivity of 85%, a negative predictive value of 53%, and AUC of the ROC of 0.670 (p = 0.03). The Spearman rank-order correlation between both measures was 0.420 (p = 0.01). The correlation was improved, particularly in stomachs with solid contents/thick fluids. Antral-CSA measured in the supine position may help to assess the high-risk stomach patients undergoing emergency surgery.Trial registration: www.umin.ac.jp (UMIN 000013416). Registered 14 March 2014.

[Effects of Anesthetics on Perioperative Short-term Outcomes in Patients Undergoing Thoracic Surgery with One-lung Ventilation].

BACKGROUND: The present study was designed to evaluate the postoperative values such as body temperature (BT), white blood cells (WBC), P/F ratio and C-reactive protein (CRP) associated with propofol or sevoflurane in patients undergoing thoracic surgery with one-lung ventilation. METHODS: We retrospectively reviewed outcomes of patients undergoing video-associated thoracic surgery of the esophagus (VATS-E) with propofol (group P, n = 71) or sevoflurane (group S, n = 34). Data were taken at 1 POD and 2 POD in ICU. In addition, data of WBC and CRP were taken just before the operation and on 5 POD. Statistical analyses used t-value and two-way ANOVA with statistic significance as P < 0.05. RESULTS: There was no significant difference between the two groups and we could not find the correlation between anesthetics and each factor. CONCLUSIONS: Propofol and sevoflurane had similar effect on BT, WBC, P/F ratio and CRP in patients undergoing thoracic surgery with one-lung ventilation.

[A Case of Cesarean Section Preceded by Coil Embolization for Subarachnoid Hemorrhage under General Anesthesia].

We report a case of subarachnoid hemorrhage due to rupture of a cerebral aneurysm in a 29-year-old woman in the 34th week of pregnancy. The aneurysm at the anterior communicating artery was up to 10 mm in diameter on magnetic resonance imaging and scheduled for emergent coil embolization. Simultaneously, obstetricians determined that cesarean section should be performed. Maintaining anesthesia by propofol and remifentanil, coil embolization was first performed to avoid aneurism re-rupture, and the patient was then transferred from an angiography room to an operating room where a cesarean section was performed. After delivery, fentanyl 600 µg was intravenously administered, and the patient was extubated immediately after the operation without any complaints. The neonate (weighing 1,882 g, Apgar score 4 at 1 min and 5 at 5 min) also recovered with no complications after 24 hr artificial ventilation. In conclusion, intravenous anesthesia mainly with remifentanil is adequate for a pregnant patient receiving cesarean section preceded by neurosurgery.

MIRSNP rs2910164 of miR-146a is associated with the muscle involvement in polymyositis/dermatomyositis.

BACKGROUND: Recently, single nucleotide polymorphisms (SNPs) located in microRNAs, the so-called MIRSNPs, have attracted attention for their possible involvement in the pathogenesis of various diseases. Such MIRSNPs may have a functional role, due to the alteration of microRNA function, and can be a disease marker. In this study, we evaluated the possibility that MIRSNP rs2910164 in miR-146a can be a useful marker for the diagnosis and evaluation of disease activity of polymyositis/dermatomyositis (PM/DM).Methods DNA was obtained from 25 patients with DM, 16 with clinically amyopathic DM,and three with PM, and genotyped by polymerase chain reaction (PCR). The PCR products were digested by MnlI, and the digested products were run out on a 3% agarosegel. Serum levels of miR-146a were measured by real-time PCR.Results We could not find a significant difference in the frequency of genotype distribution between controls and patients with PM/DM. However, the frequency of muscle weakness and dysphagia in patients with CC genotype was significantly higher as compared with patients with CG or GG genotype. In addition, the minimum free energy between miR-146a and its complementary strand with G allele is estimated at −26.8 kcal/mol, while that of Callele is at −24.0 kcal/mol, suggesting that the MIRSNP rs2910164 is functional. Serum miR-146a levels tended to be decreased in patients with DM with the CC genotype.Conclusions Taken together, miR-146a may be involved in the pathogenesis of PM/DM, and patients with the CC genotype are at higher risk of muscle involvement.

Metastatic brain sarcoma with gliomatous component.

Here we report a metastatic brain carcinosarcoma from the uterus that posed a problem on diagnosis by containing an extensive gliomatous component. A 56-year woman developed motor aphasia 3 months after hysterectomy for a uterine tumor. Magnetic resonance imaging (MRI) demonstrated a left frontal cystic tumor, which was treated by stereotactic radiosurgery. The lesion recurred 5 months later and was resected. Histological examination demonstrated neoplastic cells that were positive for glial fibrillary acidic protein (GFAP), leading to the diagnosis of high-grade glioma. This lesion recurred again after 9 months, and was resected again. The tumor tissue mostly consisted of GFAP-positive gliomatous cells, but close examination identified a sarcomatous component compatible with the metastatic lesion from the uterine sarcoma. This sarcoma component contained GFAP-negative-CD10-positive cells and GFAP-positive-CD10-negative cells. There was no clear border between those components, and, therefore, the lesion was considered to be a metastatic tumor from the uterus showing extensive neural differentiation. Although rare, uterine tumors are known to show such neural differentiation, and the histological diagnosis in such cases can be challenging.

A heuristic method for discovering biomarker candidates based on rough set theory.

We apply a combined method of heuristic attribute reduction and evaluation of relative reducts in rough set theory to gene expression data analysis. Our method extracts as many relative reducts as possible from the gene-expression data and selects the best relative reduct from the viewpoint of constructing useful decision rules. Using a breast cancer dataset and a leukemia dataset, we evaluated the classification accuracy for the test samples and biological meanings of the rules. As a result, our method presented superior classification accuracy comparable to existing salient classifiers. Moreover, our method extracted interesting rules including a novel biomarker gene identified in recent studies. These results indicate the possibility that our method can serve as a useful tool for gene expression data analysis.

High-performance gene expression module analysis tool and its application to chemical toxicity data.

Gene clustering is one of the main themes of data mining approaches in bioinformatics. Although it has the power to analyze gene function, interpretation of the results becomes increasingly difficult when the number of experiments (samples) exceeds hundreds or more. A new type of clustering called "biclustering," where genes and experiments are coclustered in a large-scale of gene expression data, has been extensively studied in the last decade. We have developed "SAMURAI," an original program that detects all the biclusters or "gene modules" whose genes have similar expression patterns to query profile using the ultrafast data mining algorithm called Linear-time Closed itemset Miner (LCM). Using chemical toxicity dataset from J&J rat liver experiments, we compiled an exhaustive dictionary of gene modules by searching datasets of gene modules with each chemical exposure experiment as query. Through the module analysis, we found that our program can detect up/down-regulated gene sets that significantly represent particular GO functions or KEGG pathways, thereby unraveling reactions and mechanisms common to different toxicochemical treatments of hepatocytes.