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Background Little is known about the effects of antimicrobial stewardship team (AST) without infectious disease physician (IDP) on clinical outcome in patients with candidemia. Methods We conducted a before and after study involving patients with hospital‐acquired candidemia at a tertiary hospital without IDPs. The AST consisted of physicians, pharmacists, nurse, microbiologist, and administrative staff. A candidemia care bundle was developed based on the Infectious Disease Society of America (IDSA) guideline. The non‐IDP AST provided recommendations to the attending physicians whose patients developed candidemia during hospitalization. The primary outcome was 30‐day all‐cause mortality, while the secondary outcomes were adherence to the IDSA guidelines regarding the management of candidemia. Data of up to 3 years of preintervention and 3 years of intervention period were analyzed. Results By 30 days, 11 of 46 patients (23.9%) in the intervention group and 7 of 30 patients (23.3%) in the preintervention group died (adjusted hazard ratio for the intervention group: 0.68 [95% CI 0.24‐1.91]). The non‐IDP AST was associated with appropriate empirical antifungal therapy (100% vs 60.0%; proportion ratio 1.67 [95% CI 1.24‐2.23]), appropriate duration of treatment (84.7% vs 43.3%; 1.96 [1.28‐3.00]), removal of central venous catheters (94.4% vs 70.8%; 1.33 [1.02‐1.74]), and ophthalmological examination (93.5% vs 63.3%; 1.48 [1.12‐1.96]). Conclusions Although we found no significant difference in 30‐day mortality, the non‐IDP AST was associated with improved adherence to guidelines for management of candidemia.

Hot-bitumen burn is a unique case in all types of burns. This melting substance is difficult to remove when it adheres to the skin and solidifies. It causes burns and sticks to the skin when it is cooled to the skin temperature. Some reports are available on many kinds of solvents for the removal of solid bitumen. However, there have thus far been no comparative studies. It is necessary to seek for an optimum method to remove bitumen without consuming so much time and with minimum injury to the skin. The selected solvents in this study were petrolatum, olive oil, salad oil, butter, Neosporin ointment and De-solv-it. They were often reported as being effective for hot-bitumen burn injuries with little irritation for a damaged skin. It is easy to purchase them commercially. Each solvent was poured over the bitumen in a test tube. Afterwards, the concentrations of the bitumen in the solvents were quantified with the fluorescence measurement technique. We consider De-solv-it is the one of the best solvent for the removal of bitumen and highly recommended for hot-bitumen burns. The results of this study suggest that dressing change should be done every 4 to 8 h or as frequently as needed until the bitumen is entirely removed.

This paper proposes a user-modeling method for folksonomic data. Since data mining of folksonomic data is difficult due to their complexity, significant amounts of preprocessing are usually required. To catch sketchy characteristics of such complex data, our method employs two steps: (1) using the infinite relational model (IRM) to perform relational clustering of a folksonomic data set, and (2) using tag-weighting to extract the characteristics of each user cluster. As an experimental evaluation, we applied our method to real-world data from one of the most popular social bookmarking services in Japan. Our user-modeling method successfully extracted semantically clustered user models, thus demonstrating that relational data analysis has promise for mining folksonomic data. In addition, we developed the user-model-based filtering algorithm (UMF), which evaluates the user models by their resource recommendations. The F-measure was higher than that of random recommendation, and the running time was much shorter than that of collaborative-filtering-based top-n recommendation.

Therapeutic communication and interpersonal relationships in care homes can help people to improve their mental wellbeing. Assessment of the efficacy of these dynamic and complex processes are necessary for psychosocial planning and management. This paper presents a pilot application of photoplethysmography in synchronized physiological measurements of communications between the care-giver and people with dementia. Signal-based evaluations of the therapy can be carried out using the measures of spectral distortion and the inference of phylogenetic trees. The proposed computational models can be of assistance and cost-effectiveness in caring for and monitoring people with cognitive decline.

We describe here sequencing and analysis of expressed sequence tags (ESTs) generated from burma mangrove, Bruguiera gymnorrhiza. A total of 26,400 cDNA were partially sequenced from five different cDNA libraries constructed from the leaves and roots. These sequences were processed into 14,842 high-quality sequences. Clustering and assembling of these sequences resulted in 6943 unique genes. Blast searches show that 4339 (62.5%) genes had a similarity with known proteins in UniProt database. Of these, 2074 genes are assigned in at least one Gene Ontology terms. Expression profiles are generated based on EST frequency in each cDNA library. The profile suggested co-expression and organ specific gene regulations.

The beta(2)-adrenergic receptor (beta2AR) is the key target for the beta(2)-agonist drugs used for bronchodilation in asthma and chronic obstructive pulmonary disease. To detect four SNPs with amino acid variations at positions -47T/C (CysBUP19Arg), 46A/G (Gly16Arg), 79C/G (Gln27Glu), and 491C/T (Thr164Ile) in the beta 2AR gene, we used the electronic microchip assay, denaturing high-performance liquid chromatography (DHPLC), and direct sequencing. Genomic DNA samples were obtained from the blood of 84 Japanese healthy volunteers. The agreement rates of the first data set with the final data (allele calls) were 99.7% (332/333), 99.2% (246/248), and 96.7% (329/340). The percentages of no allele designation (ND) were 2.06% (7/340), 2.75% (7/255), and 0.00% (0/340) for the electronic microchip assay, DHPLC, and direct sequencing, respectively. Furthermore, we found three samples that had a novel haplotype.

Magnetic field effects (MFE) on asymmetric photolysis involving a biradical intermediate have been investigated on a kinetic model where an intersystem crossing (ISC) of the intermediate is taken into account. Changes in the enantiomeric excesses (ee) of chiral substances with circularly polarized light (CPL) irradiation have been simulated, and the necessary conditions for observing the MFE were obtained. The asymmetric photolysis of racemic 2-phenylcycloalkanones (2-PCAs) with CPL has been carried out in both the presence and absence of a magnetic field. Since the anisotropy g factors of 2-PCAs are considerably large, the CPL-induced ee are achieved to a few percent after 90% decomposition though the MFE are not observed. The photolysis mechanism of 2-PCAs in an air-saturated solution has been also clarified. Triplet acyl–benzyl biradicals, formed via photochemical α-cleavage of 2-PCAs, react with O2 dissolved in the solution and result in the formation of acetophenone and alkenoic acids. The bimolecular reactions are diffusion-controlled and the rates are comparable to those of ISC to the singlet biradicals for all 2-PCAs. The recombination yields of the biradicals are sufficiently large. However, the biradical ISC rate shows little magnetic field dependence, which explains the absence of the MFE in this asymmetric photolysis.

An immortal nonhormone-producing cell line with a characteristic star-shaped morphology, named Tpit/F1, was derived from an anterior pituitary gland of a temperature-sensitive large T antigen transgenic mouse. To characterize Tpit/F1 cells, we performed cytological studies, which revealed that Tpit/F1 cells express the messenger RNAs of neruonal nitric oxide (NO) synthase, S-100 protein, basic fibroblast growth factor, and pituitary-restricted transcription factor. The Tpit/F1 cells response to pituitary adenylate cyclase-activating peptide comprised the stimulated secretion of interleukin-6. Furthermore, glucocorticoids stimulate glutamine synthase production by Tpit/F1 cells. Considering these cytological characteristics together with their morphology, we deduced that Tpit/F1 cells are derived from pituitary folliculo-stellate (FS) cells. Our cytophysiological analyses of Tpit/F1 cells revealed that intracellular Ca2+ increased dose dependently on ATP administration (0–100 μm), and that this effect did ...

The problem in which the input signal sequence is segmented into multiple signal sources and the signal source is estimated appear in a wide range of problems, such as speech information processing and language processing. In this paper, this kind of problem is called the unknown-multiple signal source clustering problem, and a solution method is proposed based on the ergodic HMM. In ergodic HMM, the state corresponds to the signal source and the symbol sequence output from the state corresponds to the signal sequence. Then, using the Viterbi decoding and the forward decoding, the segmentation point and the category can simultaneously be estimated. As an application of the problem, the classification of the utterances by multiple speakers is attempted. As a result of the experiment, it is shown that the initial parameter values are important in the ergodic HMM, and the LPC cepstrum with a long-term window is useful as the feature vector reflecting the speaker individuality.

This paper describes the speech segmentation and clustering problem based on unknown-multiple signal source modeling, where a sequence of signals is generated by signal sources one by one without overlap. This problem and its subproblem with given segmentation information have wide applications in various fields. This paper formulates the problem, and the solution and its application of the subproblem are proposed. The solution is based on clustering symbol output probability functions. The other possible solution, which gives the segmentation and clustering simultaneously, is based on an ergodic HMM which can transit among all states. In this paper the subproblem is applied to speech clustering based on speaker features. Here, each speaker corresponds to a single signal source. The performance is evaluated using simulated dialog speech data.

Summary The cytoplasmic domains of the erythropoietin receptor essential for signal transduction were identified by assessing a series of truncated and deletional mutant receptors. A 91-amino acid region proximal to the transmembrane domain was required for growth signaling. In this region, residues between 353 Pro and 362 His and between 278 Gln and 308 Leu appeared to constitute the essential cytoplasmic domains. These two domains contain the conserved amino acids common in the cytokine receptor superfamily, which indicates that these domains in the cytoplasmic regions of the erythropoietin receptor may be important for interaction with common signal transducers or protein tyrosine kinases.

This paper proposes a new optimization technique for speaker mapping neutral network training using the minimal classification error criterion. Recently, neural network modeling has been widely applied to various fields of speech processing. Most neural network applications are classification tasks; however, one of the authors of this paper proposed a speaker mapping neural network as a non-linear continuous mapping application, and showed its effectiveness. On the other hand, the minimal classification error optimization technique has been proposed and applied to several recognition architectures. Since the conventional speaker mapping neural networks have been trained under the minimal distortion criteria, the minimal classification error optimization technique is expected to provide better speaker mapping neural networks. This paper describes the speaker mapping neural network, the minimal classification error optimization technique, derives the algorithm of the minimal classification error optimization technique in the speaker mapping neural network and investigates the relationship between the derived algorithm and the conventional Back Propagation algorithm. Vowel classification experiments are carried out, showing the effectiveness of the proposed algorithm.