Radiological and pathological characteristics of synovial hemangioma of the knee

Synovial hemangioma, a rare benign tumor that occurs most frequently in the knee in children and young adults, has four histological subtypes: Venous, arteriovenous, cavernous and capillary hemangiomas. Since the clinical presentation and radiological findings of synovial hemangioma are non-specific, there is frequently a long period between the onset and the diagnosis. The cases of nine patients, pathologically diagnosed with synovial hemangioma and surgically treated, were retrospectively analyzed. All nine patients had persistent knee pain. In addition, three patients also had a swollen knee with intra-articular hemorrhage. Plain radiography revealed intra-articular phleboliths in two patients. In seven patients, T1-weighted magnetic resonance imaging showed low signal intensity with small signal voids. On T2-weighted imaging, all patients showed high signal intensity containing small signal voids. All patients underwent surgical excision; there was no postoperative recurrence after the final operation, and the knee pain had disappeared at the final follow-up. From the pathological findings, the diagnoses were venous hemangioma, cavernous hemangioma and capillary hemangioma (three patients each).

Cauda equina movement during the Valsalva maneuver in two patients with Lumbar spinal canal stenosis

Lumbar spinal canal stenosis (LSS) is a common spinal disorder among older people. Some LSS patients say that their pain worsens when they lift heavy objects. The Valsalva maneuver is the optimal breathing pattern for producing maximal force. Herein, we present two cases of LSS where the movement of the cauda equina was observed during the Valsalva maneuver.

Subclinical involvement of the trunk muscles in idiopathic inflammatory myopathies

Background

Whole-body magnetic resonance imaging (WB-MRI) is a useful tool for revealing the disease-specific distribution of affected muscles and clinically asymptomatic muscle involvements in idiopathic inflammatory myopathies (IIMs).

Purpose

To examine inflammatory changes in the systemic skeletal muscles, including the thoracoabdominal trunk, in IIMs using WB-MRI.

Material and Methods

We prospectively obtained WB-MRI axial images from 10 patients with IIMs, including antisynthetase syndrome (ASS), immune-mediated necrotizing myopathy (IMNM), sporadic inclusion body myositis, and myopathy associated with antimitochondrial antibody. We evaluated 108 systemic skeletal muscles in short-tau inversion recovery (STIR) images and rated changes in signal intensity using a semiquantitative scale. Correlations between STIR sum score, peak creatine kinase (CK) and muscle strength were examined. We also investigated the correlation between STIR sum score within the thoracoabdominal trunk and forced vital capacity.

Results

High STIR signal changes were frequently identified in asymptomatic and routinely unexamined muscles. Thoracoabdominal trunk muscles were frequently involved in ASS and IMNM. Peak CK was positively correlated with the STIR sum score (R² = 0.62, p < .01). There was no significant correlation between the STIR sum score within the thoracoabdominal trunk and forced vital capacity.

Conclusion

WB-MRI can detect subclinical muscle inflammation in the systemic muscles including the trunk muscles. STIR sum score is positively correlated with serum peak CK level; therefore, it could be a biomarker of overall muscle inflammation.

Very late relapse of high-grade osteosarcoma: A case report and review of the literature

RATIONALE

Osteosarcoma is the most common primary malignant bone tumor in children. The prognosis of osteosarcoma has improved with the use of aggressive systemic chemotherapy in addition to surgery. The relapse of osteosarcomas is usually as lung metastasis observed within 2 to 3 years after the initial treatment. A relapse is rarely observed at >10 years.

PATIENT CONCERNS

We report the case of a 51-year-old Japanese man who was treated for high-grade osteosarcoma of the femur at 13 years old. He was referred to our hospital with a suspicion of primary lung cancer based on back pain, respiratory distress, and an abnormal mass on chest radiograph.

DIAGNOSES

Computed tomography-guided biopsy confirmed the lung lesion as a metastatic recurrence of high-grade osteosarcoma without local recurrence.

INTERVENTIONS

Chemotherapy was planned, but the patient's general condition rapidly deteriorated and thus palliative therapy was provided.

OUTCOMES

The patient died 2 months after the initial consultation.

LESSONS

The survival durations of osteosarcoma patients have been prolonged by recent progress in multimodality therapy, and thus clinicians as well as osteosarcoma patients should always keep in mind the possibility of very late relapse.

Effect of Short-Term Essential Amino Acid-Containing Dialysate in Young Children on CAPD

In young children on CAPD, hypoproteinemia and malnutrition are often observed. We used essential amino acid-containing dialysate (EMD) to assess short-term effectiveness on serum amino acid concentrations in young children undergoing CAPD. EMD consisted of a 540 ml, 1.5% glucose-containing dialysate and 100 ml of 7.4% essential amino acid (EM) solution. Aside from methionine, all serum EM rose during the 6 hour peritoneal dialysis cycle using EMD, peaking at about 200% of pre-treatment level one hour after start of treatment. They then returned to near pre-treatment levels at the end of the cycle. However, serum methionine increased 680% of pre-treatment level, one hour after start and 390% at the end of the cycle. In the serum non-EM tyrosine, which showed low levels in patients with chronic renal failure, increased after EMD treatment. Other non-EM, most of which showed increased levels in patients with chronic renal failure, decreased after EMD treatment. These changes in serum amino acids suggest that EM, absorbed from EMD, may have increased uptake of non-EM in protein synthesis. This may improve the nutritional status of young children on CAPD.

Establishing a Treatment Algorithm for Puerperal Genital Hematoma Based on the Clinical Findings

Postpartum hemorrhage within 24 hours after delivery remains the leading cause of maternal mortality worldwide. Puerperal genital hematoma (PGHA) is a rare complication of postpartum hemorrhage, and PGHA can be life-threatening if hemostasis is not properly achieved. However, a reliable management algorithm for PGHA based on the clinical findings has not been developed. The objectives were to evaluate the management strategies for PGHA and identify the clinical findings that help select the treatment for PGHA. The medical records of women who were treated for PGHA in our department were reviewed, and data regarding the clinical findings and the treatment strategy for PGHA were analyzed. Thirty-four women who underwent treatment for PGHA were identified and divided into three groups according to the final procedure that achieved hemostasis: conservative management (CM) (n = 9), surgical management (SURG) (n = 15), and arterial embolization management (AEM) (n = 10). Regarding the clinical findings on initial evaluation, the shock index was significantly higher in the AEM group than in the CM or SURG group; and initial platelet count and fibrinogen level were significantly lower in the AEM group than in the CM group. There was no significant difference in any computed tomography (CT) finding among the three groups. In conclusion, this study clearly shows the difference in clinical findings among treatment strategies for PGHA. We suggest that the clinical findings of shock index, platelet count, and fibrinogen level together with CT findings are helpful and valuable for selecting the treatment strategy for PGHA.

Simultaneous Forecasting of Meteorological Data Based on a Self-Organizing Incremental Neural Network

In this study, we propose a simultaneous forecasting model for meteorological time-series data based on a self-organizing incremental neural network (SOINN). Meteorological parameters (i.e., temperature, wet bulb temperature, humidity, wind speed, atmospheric pressure, and total solar radiation on a horizontal surface) are considered as input data for the prediction of meteorological time-series information. Based on a SOINN within normalized-refined-meteorological data, proposed model succeeded forecasting temperature, humidity, wind speed and atmospheric pressure simultaneously. In addition, proposed model does not take more than 2 s in training half-year period and 15 s in testing half-year period. This paper also elucidates the SOINN and the algorithm of the learning process. The effectiveness of our model is established by comparison of our results with experimental results and with results obtained by another model. Three advantages of our model are also described. The obtained information can be effective in applications based on neural networks, and the proposed model for handling meteorological phenomena may be helpful for other studies worldwide including energy management system.

Time Series Prediction of Tropical Storm Trajectory Using Self-Organizing Incremental Neural Networks and Error Evaluation

This study proposes a route prediction method using a self-organizing incremental neural network. The route trajectory is predicted from two location parameters (the latitude and longitude of the middle of a tropical storm) and the meteorological information (the atmospheric pressure). The method accurately predicted the normalized atmospheric pressure data of East Asia in the topological space of latitude and longitude, with low calculation cost. This paper explains the algorithms for training the self-organizing incremental neural network, the procedure for refining the datasets and the method for predicting the storm trajectory. The effectiveness of the proposed method was confirmed in experiments. With the results of experiments, possibility of prediction model improvement is discussed. Additionally, this paper explains the limitations of proposed method and brief solution to resolve. Although the proposed method was applied only to typhoon phenomena in the present study, it is potentially applicable to a wide range of global problems.

A Non-Linear Manifold Alignment Approach to Robot Learning from Demonstrations

The number and variety of robots active in real-world environments are growing, as well as the skills they are expected to acquire, and to this end we present an approach for non-robotics-expert users to be able to easily teach a skill to a robot with potentially different, but unknown, kinematics from humans. This paper proposes a method that enables robots with unknown kinematics to learn skills from demonstrations. Our proposed method requires a motion trajectory obtained from human demonstrations via a vision-based system, which is then projected onto a corresponding human skeletal model. The kinematics mapping between the robot and the human model is learned by employing Local Procrustes Analysis, a manifold alignment technique which enables the transfer of the demonstrated trajectory from the human model to the robot. Finally, the transferred trajectory is encoded onto a parameterized motion skill, using Dynamic Movement Primitives, allowing it to be generalized to different situations. Experiments in simulation on the PR2 and Meka robots show that our method is able to correctly imitate various skills demonstrated by a human, and an analysis of the transfer of the acquired skills between the two robots is provided.

Primary malignant lymphoma of the talus: A case report and review of the literature

Malignant lymphoma commonly occurs in adults, with a peak incidence between the seventh and ninth decades of life. Although malignant lymphoma usually occurs in the lymph nodes, it rarely occurs primarily in the bone. We herein describe an extremely rare case of primary malignant lymphoma of the talus in a 74-year-old man. Although plain radiographs showed no abnormality, gadolinium-enhanced magnetic resonance imaging (MRI) revealed a well-circumscribed intra- and extraosseous tumor of the talus. ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography/MRI revealed a marked increase of FDG uptake in the right ankle and the right inguinal lymph nodes. As the tumor was diagnosed as diffuse large B-cell lymphoma by core needle biopsy, combination therapy with chemo- and radiotherapy was initiated. The patient achieved complete remission, with no sign of recurrence at 8 months after initial chemoradiotherapy. Since primary malignant lymphoma of the bone is chemo- and radiosensitive and has a good prognosis, accurate staging by radiological investigation as well as correct pathological diagnosis by biopsy are required for optimal treatment.

Learning Quadcopter Maneuvers with Concurrent Methods of Policy Optimization

This study presents an aerial robotic application of deep reinforcement learning that imparts an asynchronous learning framework and trust region policy optimization to a simulated quad-rotor helicopter (quadcopter) environment. In particular, we optimized a control policy asynchronously through interaction with concurrent instances of the environment. The control system was benchmarked and extended with examples to tackle continuous state-action tasks for the quadcoptor: hovering control and balancing an inverted pole. Performing these maneuvers required continuous actions for sensitive control of small acceleration changes of the quadcoptor, thereby maximizing the scalar reward of the defined tasks. The simulation results demonstrated an enhancement of the learning speed and reliability for the tasks.

Effects of barbed suture during robot-assisted radical prostatectomy on postoperative tissue damage and longitudinal changes in lower urinary tract outcome

OBJECTIVE

To compare the postoperative tissue damage and longitudinal changes in functional and patient-reported outcomes after vesicourethral anastomosis with barbed suture and nonbarbed suture in robot-assisted laparoscopic radical prostatectomy (RARP).

MATERIALS AND METHODS

This was a prospective cohort study involving 88 consecutive patients who underwent RARP. These patients were categorized into the barbed suture group (n = 50) and the nonbarbed suture group (n = 38). Urethral and periurethral damages determined by magnetic resonance imaging at nine months after RARP were compared using generalized linear models. The International Prostate Symptom Score (IPSS), quality of life (QOL) index, uroflowmetry, and the 1-h pad test were measured at baseline and at 1, 3, 6, 9, and 12 months after RARP. The findings were analyzed using mixed-effects models. Confounding was adjusted for using propensity score covariate adjustment.

RESULTS

The likelihood of having Grade 2/3 urethral and periurethral damages was greater in the barbed suture group than in the nonbarbed suture group (adjusted risk ratios: 2.98 and 3.85, respectively). IPSS, QOL index, and urinary leakage transiently increased at one month after RARP in both groups. QOL index was higher in the barbed suture group than in the nonbarbed suture group at 1, 9, and 12 months (P = 0.023, P = 0.025, and P = 0.011, respectively). The barbed suture group had significantly more cases of urinary incontinence than the nonbarbed suture group at 3 months (P = 0.041). Other outcomes were comparable between the two groups at all time points.

CONCLUSIONS

This cohort study showed that, after RARP, barbed sutures during VUA induced more severe tissue damage as determined by MRI and greater transient aggravation of QOL and continence function than nonbarbed sutures. The present findings suggest that using nonbarbed sutures during VUA may facilitate earlier acquisition of urinary QOL and urinary continence.

Development of immersion vaccine for bacterial cold-water disease in ayu Plecoglossus altivelis

Flavobacterium psychrophilum (F. psychrophilum) is the causative agent of bacterial cold-water disease (BCWD) that occurs in ayu Plecoglossus altivelis. Formalin-killed cell of F. psychrophilum has long been studied as an immersion vaccine for BCWD. In this study, we explored the possibility of F. psychrophilum collagenase (fpcol) for use as the immersion vaccine. BCWD convalescent ayu sera contained specific IgM antibodies against somatic F. psychrophilum and fpcol, meaning that fpcol is a promising antigen for the vaccine development. The recombinant fpcol was successfully expressed in Escherichia coli and Brevibacillus chosinensis (B. chosinensis). The culture supernatant of the B. chosinensis was used as an immersion vaccine solution. The vaccinated ayu were then challenged by soaking into F. psychrophilum culture. In two experimental groups, the relative percentages of survivals were 63 and 38%, respectively, suggesting that fpcol is promising as the immersion vaccine for ayu-BCWD.

Nonparametric Density Estimation Based on Self-Organizing Incremental Neural Network for Large Noisy Data

With the ongoing development and expansion of communication networks and sensors, massive amounts of data are continuously generated in real time from real environments. Beforehand, prediction of a distribution underlying such data is difficult; furthermore, the data include substantial amounts of noise. These factors make it difficult to estimate probability densities. To handle these issues and massive amounts of data, we propose a nonparametric density estimator that rapidly learns data online and has high robustness. Our approach is an extension of both kernel density estimation (KDE) and a self-organizing incremental neural network (SOINN); therefore, we call our approach KDESOINN. An SOINN provides a clustering method that learns about the given data as networks of prototype of data; more specifically, an SOINN can learn the distribution underlying the given data. Using this information, KDESOINN estimates the probability density function. The results of our experiments show that KDESOINN outperforms or achieves performance comparable to the current state-of-the-art approaches in terms of robustness, learning time, and accuracy.

[A case of sensory ataxic axonal polyneuropathy with IgGλ monoclonal gammopathy successfully treated with intravenous immunoglobulin therapy]

We report the case of an 84-year-old man with sensory ataxic polyneuropathy and IgGλ monoclonal gammopathy of undetermined significance (MGUS), which was successfully treated with intravenous immunoglobulin (IVIG) therapy. He had developed progressive ataxic gait over the span of 2 years before he was admitted to our hospital. On admission, he was unable to walk without assistance because of severe sensory ataxia. He performed poorly on the finger-nose-finger and heel-knee tests, and his vibration and position sense in the feet was remarkably diminished. However, motor involvement was not remarkable. Serum immunoelectrophoresis revealed IgGλ monoclonal gammopathy, and MGUS was diagnosed. Nerve conduction studies revealed sensory-dominant axonal polyneuropathy. The patient was successfully treated with IVIG (400 mg/kg/day, for 5 days). He regained his capacity to walk independently after treatment, but his nerve conduction results remained unchanged. This sensory ataxia might be partially due to underlying cervical spondylotic myelopathy. To our knowledge, this is the first report in our country of the successful use of IVIG therapy to treat a patient with IgGλ monoclonal gammopathy and related sensory ataxic axonal polyneuropathy.

Missed causative tumors in diagnosing tumor-induced osteomalacia with (18)F-FDG PET/CT: a potential pitfall of standard-field imaging

OBJECTIVE

We describe herein two tumor-induced osteomalacia (TIO) cases for whom the causative lesions, located in their popliteal fossa, that were not identified in the standard field of fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT), which usually images only the head, trunk, and proximal parts of the extremities.

CLINICAL PRESENTATION AND INTERVENTION

A 47 years old Japanese man with multiple pathological fractures due to osteomalacia, accompanied by muscle weakness, hypophosphatemia, and an elevation of alkaline phosphatase (ALP) was referred to our hospital. A (18)F-FDG PET/CT scan was performed, but no (18)F-FDG uptake was detected in the standard field of imaging. Magnetic resonance imaging revealed a small subcutaneous tumor (1.9×1.2×0.6cm) of the left posteriomedial knee, displaying uniform enhancement on gadolinium-enhanced T1-weighted fat-suppression imaging. The tumor was resected widely and diagnosed as phosphaturic mesenchymal tumor, mixed connective tissue variant (PMTMCT). The other patient was a 31 years old Japanese woman with multiple pathological fractures, hypophosphatemia and elevated of ALP and was referred to our hospital on suspicion of TIO. Although the causative lesion was not identified in the standard field of (18)F-FDG PET/CT, (18)F-FDG uptake (SUVmax 2.9) was detected on the right knee in the additional whole-body (18)F-FDG PET/CT. Magnetic resonance imaging revealed a soft-tissue tumor (6.4×4.1×2.9cm) in the right posterior knee. Following biopsy, the tumor was marginally resected, and was pathologically diagnosed as PMTMCT.

CONCLUSION

Once patients are suspected to have TIO, a whole-body nuclear imaging study such as (18)F-FDG PET/CT should be performed, in order not to miss the hidden causative tumor, especially occurring in the distal extremities.

C5-azobenzene-functionalized locked nucleic acid uridine: isomerization properties, hybridization ability, and enzymatic stability

Oligonucleotides (ONs) modified with a locked nucleic acid (LNA) are widely used in the fields of therapeutics, diagnosis, and nanotechnology. There have been significant efforts towards developing LNA analogues bearing modified bridges to improve their hybridization ability, nuclease resistance, and pharmacokinetic profiles. Moreover, nucleobase modifications of LNA are useful strategies for the functionalization of ONs. Modifications of the C5-position of pyrimidine nucleobases are particularly interesting because they enable predictable positioning of functional groups in the major groove of the duplex. Here we report the synthesis of C5-azobenzene-functionalized LNA uridine (LNA-U(Az)) and properties of LNA-U(Az)-modified ONs, including isomerization properties, hybridization ability, and enzyme stability. LNA-U(Az) in ON is photo-isomerized effectively and reversibly by irradiation at 365 nm (trans to cis) and 450 nm (cis to trans). LNA-U(Az)-modified ONs show RNA-selective hybridization ability despite the large hydrophobic azobenzene moiety extending into the major groove of the duplex. The enzymatic stability of LNA-U(Az)-modified ONs is higher than that of natural and LNA-modified ONs with or without photo-irradiation. Our results indicate that LNA-U(Az) holds promise for RNA targeting and photo-switchable technologies.

Superior Mesenteric Artery Syndrome Complicated by Diabetic Ketoacidosis and Graves' Disease in Slowly Progressive Insulin Dependent Diabetes Mellitus (SPIDDM): A Case Report and a Review of the Literature

A 48-year-old woman with a history of diabetes was admitted for nausea and vomiting with body weight loss. A blood examination revealed high plasma glucose and thyroid hormone levels and metabolic acidosis. She was therefore diagnosed with both diabetic ketoacidosis (DKA) and hyperthyroidism. Nausea and vomiting continued intermittently despite the administration of saline and insulin. The patient was further diagnosed with superior mesenteric artery syndrome (SMAS) after abdominal computed tomography revealed that a horizontal portion of the duodenum was sandwiched between the aorta and the superior mesenteric artery. Clinicians should be vigilant for SMAS in patients with both DKA and hyperthyroidism who present body weight loss.

Hebbian Network of Self-Organizing Receptive Field Neurons as Associative Incremental Learner

Associative learning plays a major role in the formation of the internal dynamic engine of an adaptive system or a cognitive robot. Interaction with the environment can provide a sparse and discrete set of sample correlations of input–output incidences. These incidences of associative data points can provide useful hints for capturing underlying mechanisms that govern the system’s behavioral dynamics. In many approaches to solving this problem, of learning system’s input–output relation, a set of previously prepared data points need to be presented to the learning mechanism, as a training data, before a useful estimations can be obtained. Besides data-coding is usually based on symbolic or nonimplicit representation schemes. In this paper, we propose an incremental learning mechanism that can bootstrap from a state of complete ignorance of any representative sample associations. Besides, the proposed system provides a novel mechanism for data representation in nonlinear manner through the fusion of self-organizing maps and Gaussian receptive fields. Our architecture is based solely on cortically-inspired techniques of coding and learning as: Hebbian plasticity and adaptive populations of neural circuitry for stimuli representation.

We define a neural network that captures the problem’s data space components using emergent arrangement of receptive field neurons that self-organize incrementally in response to sparse experiences of system–environment interactions. These learned components are correlated using a process of Hebbian plasticity that relates major components of input space to those of the output space. The viability of the proposed mechanism is demonstrated through multiple experimental setups from real-world regression and robotic arm sensory-motor learning problems.

Polymerase incorporation of a 2'-deoxynucleoside-5'-triphosphate bearing a 4-hydroxy-2-mercaptobenzimidazole nucleobase analogue

Here, we describe the enzymatic construction of a new larger base pair formed between adenine (A) and a 4-hydroxy-2-mercaptobenzimidazole (SB) nucleobase analogue. We investigated the enzymatic incorporation of 2'-deoxynucleoside-5'-triphosphate bearing a SB nucleobase analogue (dSBTP) into oligonucleotides (ONs) by DNA polymerases. dSBTP could be effectively incorporated at the site opposite a dA in a DNA template by several B family DNA polymerases. These findings provide new insights into various aspects of biotechnology, including the design of non-natural base pairs.

A Robust Visual-Feature-Extraction Method for Simultaneous Localization and Mapping in Public Outdoor Environment

We describe a new feature extraction method based on the geometric structure of matched local feature points that extracts robust features from an image sequence and performs satisfactorily in highly dynamic environments. Our proposed method is more accurate than other such methods in appearance-only simultaneous localization and mapping (SLAM). Compared to position-invariant robust features [1], it is also more suitable for low-cost, single lens cameras with narrow fields of view. Testing our method in an outdoor environment at Shibuya Station. We captured images using a conventional hand-held single-lens video camera. These environments of experiments are public environments without any planned landmarks. Results have shown that the proposed method accurately obtains matches for two visual-feature sets and that stable, accurate SLAM is achieved in dynamic public environments.

Radiological and pathological characteristics of giant cell tumor of bone treated with denosumab

Abstract

We describe a case of giant cell tumor of the proximal tibia with skip bone metastases of the ipsilateral femur in a 20-year-old man. After the neoadjuvant treatment with denosumab, plain radiographs and computed tomography showed marked osteosclerosis and sclerotic rim formation, and ¹⁸F-FDG PET/CT showed a decreased standardized uptake value, whereas magnetic resonance imaging showed diffuse enhancement of the tumor, nearly the same findings as those at pretreatment. Pathological findings of the surgical specimen after the denosumab treatment showed benign fibrous histiocytoma-like features with complete disappearance of both mononuclear stromal cells and multinuclear osteoclast-like giant cells.

Virtual Slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1090602085125068

[Skeletal muscle MRI in a patient with neuralgic amyotrophy]

Neuralgic amyotrophy has been attributed to lesions in the brachial plexus. However, recent studies suggest mononeuropathy multiplex as an underlying pathology at least in a group of patients with neuralgic amyotrophy. We report a man who developed weakness of finger extensors following severe shoulder pain. Neurological examination revealed weakness in the muscles innervated by the left posterior interosseus nerve and the ulnar nerve. We diagnosed him with neuralgic amyotrophy based on the typical clinical course and the neurological and neurophysiological findings. A skeletal muscle MRI revealed abnormal high T2 and STIR signals in the left triceps brachialis muscle, which is innervated by a proximal branch of the radial nerve, and in the muscles innervated by the posterior interosseous and ulnar nerves. The distribution of the denervated muscles suggested that our patient had combined lesions of the peripheral nerve branches rather than the brachial plexopathy. Our report highlights the potential of MRI for detecting denervated muscles in neuralgic amyotrophy.

Relationship between coronary artery disease and retinopathy in patients with type 2 diabetes mellitus

OBJECTIVE

To examine risk factors for coronary artery disease (CAD) and retinopathy in patients with type 2 diabetes mellitus (DM) and assess the relationship between CAD and retinopathy.

METHODS

A total of 1,003 outpatients with type 2 DM (578 men and 425 women) were classified into two groups according to the presence (based on ischemic findings on a resting electrocardiogram or a history of angina or myocardial infarction) or absence of CAD and four retinopathy stages based on the International Clinical Classification of Diabetic Retinopathy.

RESULTS

Stepwise multiple regression analyses showed that independent risk factors for CAD were age, the triglyceride (TG) level and smoking, while those for retinopathy included age, age of DM diagnosis, the HbA1c level and a female gender. The prevalence of CAD increased in association with the progression of retinopathy (p<0.01).

CONCLUSION

Since it is difficult to distinguish macrovascular and microvascular diseases, diabetic vascular disorders require comprehensive approaches to assessment and treatment.

A Proposal of Stock Price Predictor Using Associated Memory

The novel method [1] we propose for predicting stock prices is a case-based reasoning predictor based on associative stock price data memory using Self-Organizing and IncrementalNeural Networks (SOINN) [2]. When a user inputs stock price data, the predictor outputs the most likely prediction based on statistically summarizing similar stock price pattern. It also outputs all cases included in the prediction. Our method has following advantages: (a) our predictor gives users grounds by giving all cases consisting of the prediction using associative memory. Users thereby recognize and are ready for prediction risk. (b) Our predictor avoids large prediction failures because it modifies itself through online learning and continues to learn without its learning parameters being reassigned. This makes it much safer where investment loss may be large. (c) Our predictor is as profitable as previous work while realizing unique, useful functions, as shown by experimental results using actual stock price data from the US and Japan markets between 1998 and 2005.

Sonographic assessment of fatty liver infiltration using the measurement of para- and perirenal fat thickness

PURPOSE

Usefulness of abdominal ultrasonography for quantitative estimation of fatty liver by measurement of para- and perirenal sonographic fat thickness (UFT) was investigated.

METHODS

Study subjects were 286 patients hospitalized for the treatment of diabetes. These subjects underwent blood chemistry studies, abdominal ultrasonography, and CT. On sonography, the thickness of combined para- and perirenal fat was measured between the kidney and the inner aspect of the abdominal musculature. Measurements on both sides were averaged as the UFT. Fatty liver infiltration was graded on a scale of grade 0 to 3: 0, none; 1, mild; 2, moderate; and 3, severe. With abdominal CT, the ratio of CT attenuation value of the liver to that of the spleen (L/S ratio) was measured.

RESULTS

A positive correlation was found between UFT and FL grade or between UFT and L/S ratio (p < 0.0001). Positive correlations were also found between UFT and glutamic pyruvic transaminase (p < 0.05), or cholinesterase (p < 0.0001).

CONCLUSION

Measurement of UFT is a useful method for the quantification of fatty liver as well as for the quantification of visceral fat.

A second generation genetic linkage map of Japanese flounder (Paralichthys olivaceus)

BACKGROUND

Japanese flounder (Paralichthys olivaceus) is one of the most economically important marine species in Northeast Asia. Information on genetic markers associated with quantitative trait loci (QTL) can be used in breeding programs to identify and select individuals carrying desired traits. Commercial production of Japanese flounder could be increased by developing disease-resistant fish and improving commercially important traits. Previous maps have been constructed with AFLP markers and a limited number of microsatellite markers. In this study, improved genetic linkage maps are presented. In contrast with previous studies, these maps were built mainly with a large number of codominant markers so they can potentially be used to analyze different families and populations.

RESULTS

Sex-specific genetic linkage maps were constructed for the Japanese flounder including a total of 1,375 markers [1,268 microsatellites, 105 single nucleotide polymorphisms (SNPs) and two genes]; 1,167 markers are linked to the male map and 1,067 markers are linked to the female map. The lengths of the male and female maps are 1,147.7 cM and 833.8 cM, respectively. Based on estimations of map lengths, the female and male maps covered 79 and 82% of the genome, respectively. Recombination ratio in the new maps revealed F:M of 1:0.7. All linkage groups in the maps presented large differences in the location of sex-specific recombination hot-spots.

CONCLUSIONS

The improved genetic linkage maps are very useful for QTL analyses and marker-assisted selection (MAS) breeding programs for economically important traits in Japanese flounder. In addition, SNP flanking sequences were blasted against Tetraodon nigroviridis (puffer fish) and Danio rerio (zebrafish), and synteny analysis has been carried out. The ability to detect synteny among species or genera based on homology analysis of SNP flanking sequences may provide opportunities to complement initial QTL experiments with candidate gene approaches from homologous chromosomal locations identified in related model organisms.

An Online Incremental Semi-Supervised Learning Method

Using labeled data and large amounts of unlabeled data, our proposed online incremental semisupervised learning automatically learns the topology of input data distribution without prior knowledge of numbers of nodes or network structure. Using labeled data, it labels generated nodes and divides a learned topology into substructures corresponding to classes. Node weights used as prototype vectors enable classification. New labeled or unlabeled data is added incrementally to the system during learning. Experimental results for artificial and real-world data show that this learning efficiently learns online incremental tasks even in noisy and non-stationary environments.

Online and Incremental Appearance-based SLAM in Highly Dynamic Environments

In this paper we present a novel method for online and incremental appearance-based localization and mapping in a highly dynamic environment. Using position-invariant robust features (PIRFs), the method can achieve a high rate of recall with 100% precision. It can handle both strong perceptual aliasing and dynamic changes of places efficiently. Its performance also extends beyond conventional images; it is applicable to omnidirectional images for which the major portions of scenes are similar for most places. The proposed PIRF-based Navigation method named PIRF-Nav is evaluated by testing it on two standard datasets in a similar manner as in FAB-MAP and on an additional omnidirectional image dataset that we collected. This extra dataset was collected on 2 days with different specific events, i.e. an open-campus event, to present challenges related to illumination variance and strong dynamic changes, and to test assessment of dynamic scene changes. Results show that PIRF-Nav outperforms FAB-MAP; PIRF-Nav at precision-1 yields a recall rate about twice as high (approximately 80% increase) than that of FAB-MAP. Its computation time is sufficiently short for real-time applications. The method is fully incremental, and requires no offline process for dictionary creation. Additional testing using combined datasets proves that PIRF-Nav can function over the long term and can solve the kidnapped robot problem.

Associative memory for online learning in noisy environments using self-organizing incremental neural network

Associative memory operating in a real environment must perform well in online incremental learning and be robust to noisy data because noisy associative patterns are presented sequentially in a real environment. We propose a novel associative memory that satisfies these requirements. Using the proposed method, new associative pairs that are presented sequentially can be learned accurately without forgetting previously learned patterns. The memory size of the proposed method increases adaptively with learning patterns. Therefore, it suffers neither redundancy nor insufficiency of memory size, even in an environment in which the maximum number of associative pairs to be presented is unknown before learning. Noisy inputs in real environments are classifiable into two types: noise-added original patterns and faultily presented random patterns. The proposed method deals with two types of noise. To our knowledge, no conventional associative memory addresses noise of both types. The proposed associative memory performs as a bidirectional one-to-many or many-to-one associative memory and deals not only with bipolar data, but also with real-valued data. Results demonstrate that the proposed method's features are important for application to an intelligent robot operating in a real environment. The originality of our work consists of two points: employing a growing self-organizing network for an associative memory, and discussing what features are necessary for an associative memory for an intelligent robot and proposing an associative memory that satisfies those requirements.

[Application of microneurography to the evaluation of diabetic neuropathy]

The use of microneurography for recording of the compound nerve action potentials enables a more accurate evaluation of even severe cases of diabetic polyneuropathy. A tungsten microelectrode with a tip diameter of approximately 1 microm is percutaneously inserted into the median nerve trunk in the elbow without the administration of anesthesia. The median nerve in the wrist is subiected to supramaximal electric stimulation, and the largest compound nerve action potential is recorded by the microelectrode. In healthy controls, the median nerve action potential appeared as a large triphasic wave (positive-negative-positive; average amplitude, 400 microV) followed by small multiphasic waves. In diabetic patients, the maximal nerve conduction velocity (NCV) and the amplitude of the triphasic wave (Amp) were decreased, and the multiphasic waves were more prominent. The reproducibility of the compound nerve action potentials in the same subject was acceptable. Diminution of Amp appeared to be associated with temporal dispersion due to segmental demyelination. In diabetic polyneuropathy, NCV and Amp decrease with disease progression. In patients with advanced disease and subjective symptoms, low Amp and prominent multiphasic waves were apparent. Because a recording microelectrode is directly inserted into the nerve trunk, this method has many advantages: large potentials measuring several hundred microvolts can be obtained, averaging is not required, and quantitative analysis of the nerve action potential and evaluation of slow fibers are possible. This compound nerve action potential is considered to represent the density of large myelinated fibers (7 microm), especially sensory fibers, around the electrode. This technique may evaluate nerve function more accurately than that of "near-nerve recording of action potentials", a technique reported by Buchthal et al. This method can be a valuable tool for evaluating the function of large myelinated fibers without the use of time-consuming averaging procedures or computer analysis.

Random field model for integration of local information and global information

This paper presents a proposal of a general framework that explicitly models local information and global information in a conditional random field. The proposed method extracts global image features as well as local ones and uses them to predict the scene of the input image. Scene-based top-down information is generated based on the predicted scene. It represents a global spatial configuration of labels and category compatibility over an image. Incorporation of the global information helps to resolve local ambiguities and achieves locally and globally consistent image recognition. In spite of the model's simplicity, the proposed method demonstrates good performance in image labeling of two datasets.

A fast nearest neighbor classifier based on self-organizing incremental neural network

A fast prototype-based nearest neighbor classifier is introduced. The proposed Adjusted SOINN Classifier (ASC) is based on SOINN (self-organizing incremental neural network), it automatically learns the number of prototypes needed to determine the decision boundary, and learns new information without destroying old learned information. It is robust to noisy training data, and it realizes very fast classification. In the experiment, we use some artificial datasets and real-world datasets to illustrate ASC. We also compare ASC with other prototype-based classifiers with regard to its classification error, compression ratio, and speed up ratio. The results show that ASC has the best performance and it is a very efficient classifier.

Sonographic evaluation of visceral fat by measuring para- and perirenal fat

PURPOSE

To evaluate a new method of determining visceral fat amount by measuring para- and perirenal fat on abdominal sonography.

METHODS

Fifty-seven patients hospitalized for treatment of their diabetes were examined via waist circumference, abdominal sonography, and CT. On sonography, the thickness of combined para- and perirenal fat was measured between the kidney and the inner aspect of the abdominal musculature. Measurements on both sides were averaged as the ultrasound fat thickness (UFT). The visceral fat area was measured on abdominal CT scans at the umbilicus level. Visceral fat deposition was considered elevated above 100 cm2.

RESULTS

UFT correlated significantly with VFA and waist circumference (p < 0.0001). A VFA of 100 cm2 was equivalent to a UFT of 10 mm. Waist circumference values of 85 cm in males and 90 cm in females were equivalent to UFT measurements of 11 and 10 mm, respectively.

CONCLUSION

A UFT of > or =10 mm reflects increased visceral fat deposition.