Smart Gateway for Healthcare Networks Based on Beam Steering Technology.

To ensure high-reliability communication in healthcare networks, this paper presents a smart gateway system that includes an angle-of-arrival (AOA) estimation and a beam steering function for a small circular antenna array. To form a beam toward healthcare sensors, the proposed antenna estimates the direction of the sensors utilizing the radio-frequency-based interferometric monopulse technique. The fabricated antenna was assessed based on the measurements of complex directivity and the over-the-air (OTA) testing in Rice propagation environments using a two-dimensional fading emulator. The measurement results reveal that the accuracy of the AOA estimation agrees well with that of the analytical data obtained through the Monte Carlo simulation. This antenna is embedded with a beam steering function employing phased array technology, which can form a beam spaced at 45° intervals. The ability of full-azimuth beam steering with regard to the proposed antenna was evaluated by beam propagation experiments using a human phantom in an indoor environment. The received signal of the proposed antenna with beam steering increases more than that of a conventional dipole antenna, confirming that the developed antenna has great potential of achieving high-reliability communication in a healthcare network.

The ratio of 12α to non-12-hydroxylated bile acids reflects hepatic triacylglycerol accumulation in high-fat diet-fed C57BL/6J mice.

In our previous study, enterohepatic 12α-hydroxylated (12α) bile acid (BA) levels were found to be correlated with hepatic triacylglycerol concentration in rats fed high-fat (HF) diet. Since BA composition is diverse depending on animal species, we evaluated whether such a relationship is applicable in mice in response to an HF diet. C57BL/6JJmsSLC (B6) male mice were fed HF diet for 13 weeks and analyzed for triacylglycerol, cholesterol, oxysterols, and other metabolites in the liver. The BA composition was determined in the liver, small intestinal contents, portal plasma, aortic plasma, and feces. Neutral sterols were also measured in the feces. The ratio of 12α BA/non-12 BA increased in the liver, portal plasma, small intestinal contents, and feces of HF-fed B6 mice. Moreover, a positive correlation was observed between the ratio of fecal 12α BAs/non-12 BAs and hepatic triacylglycerol concentration. The concentration of 7α-hydroxycholesterol was increased in the liver of HF-fed B6 mice, whereas no increase was observed in the hepatic expression of cytochrome P450 family 7 subfamily A member 1. The present study showed that the ratio of 12α BA/non-12 BA in feces is closely associated with hepatic triacylglycerol accumulation in B6 mice fed HF diet.

Single-strand specific nuclease enhances accuracy of error-corrected sequencing and improves rare mutation-detection sensitivity.

Error-corrected sequences (ECSs) that utilize double-stranded DNA sequences are useful in detecting mutagen-induced mutations. However, relatively higher frequencies of G:C > T:A (1 × 10-7 bp) and G:C > C:G (2 × 10-7 bp) errors decrease the accuracy of detection of rare G:C mutations (approximately 10-7 bp). Oxidized guanines in single-strand (SS) overhangs generated after shearing could serve as the source of these errors. To remove these errors, we first computationally discarded up to 20 read bases corresponding to the ends of the DNA fragments. Error frequencies decreased proportionately with trimming length; however, the results indicated that they were not sufficiently removed. To efficiently remove SS overhangs, we evaluated three mechanistically distinct SS-specific nucleases (S1 Nuclease, mung bean nuclease, and RecJf exonuclease) and found that they were more efficient than computational trimming. Consequently, we established Jade-Seq™, an ECS protocol with S1 Nuclease treatment, which reduced G:C > T:A and G:C > C:G errors to 0.50 × 10-7 bp and 0.12 × 10-7 bp, respectively. This was probably because S1 Nuclease removed SS regions, such as gaps and nicks, depending on its wide substrate specificity. Subsequently, we evaluated the mutation-detection sensitivity of Jade-Seq™ using DNA samples from TA100 cells exposed to 3-methylcholanthrene and 7,12-dimethylbenz[a]anthracene, which contained the rare G:C > T:A mutation (i.e., 2 × 10-7 bp). Fold changes of G:C > T:A compared to the vehicle control were 1.2- and 1.3-times higher than those of samples without S1 Nuclease treatment, respectively. These findings indicate the potential of Jade-Seq™ for detecting rare mutations and determining the mutagenicity of environmental mutagens.

Hawk-Seq™ differentiates between various mutations in Salmonella typhimurium TA100 strain caused by exposure to Ames test-positive mutagens.

A precise understanding of differences in genomic mutations according to the mutagenic mechanisms detected in mutagenicity data is required to evaluate the carcinogenicity of environmental mutagens. Recently, we developed a highly accurate genome sequencing method, 'Hawk-Seq™', that enables the detection of mutagen-induced genome-wide mutations. However, its applicability to detect various mutagens and identify differences in mutational profiles is not well understood. Thus, we evaluated DNA samples from Salmonella typhimurium TA100 exposed to 11 mutagens, including alkylating agents, aldehydes, an aromatic nitro compound, epoxides, aromatic amines and polycyclic aromatic hydrocarbons (PAHs). We extensively analysed mutagen-induced mutational profiles and studied their association with the mechanisms of mutagens. Hawk-Seq™ sensitively detected mutations induced by all 11 mutagens, including one that increased the number of revertants by approximately 2-fold in the Ames test. Although the sensitivity for less water-soluble mutagens was relatively low, we increased the sensitivity to obtain high-resolution spectra by modifying the exposure protocol. Moreover, two epoxides indicated similar 6- or 96-dimensional mutational patterns; likewise, three SN1-type alkylating agents indicated similar mutational patterns, suggesting that the mutational patterns are compound category specific. Meanwhile, an SN2 type alkylating agent exhibited unique mutational patterns compared to those of the SN1 type alkylating agents. Although the mutational patterns induced by aldehydes, the aromatic nitro compound, aromatic amines and PAHs did not differ substantially from each other, the maximum total base substitution frequencies (MTSFs) were similar among mutagens in the same structural groups. Furthermore, the MTSF was found to be associated with the carcinogenic potency of some direct-acting mutagens. These results indicate that our method can generate high-resolution mutational profiles to identify characteristic features of each mutagen. The detailed mutational data obtained by Hawk-Seq™ can provide useful information regarding mutagenic mechanisms and help identify its association with the carcinogenicity of mutagens without requiring carcinogenicity data.

Adjustment of a no expected sensitization induction level derived from Bayesian network integrated testing strategy for skin sensitization risk assessment.

Skin sensitization is a key adverse effect to be addressed during hazard identification and risk assessment of chemicals, because it is the first step in the development of allergic contact dermatitis. Multiple non-animal testing strategies incorporating in vitro tests and in silico tools have achieved good predictivities when compared with murine local lymph node assay (LLNA). The binary test battery of KeratinoSensTM and h-CLAT could be used to classify non-sensitizers as the first part of bottom-up approach. However, the quantitative risk assessment for sensitizing chemicals requires a No Expected Sensitization Induction Level (NESIL), the dose not expected to induce skin sensitization in humans. We used Bayesian network integrated testing strategy (BN ITS-3) for chemical potency classification. BN ITS-3 predictions were performed without a pre-processing step (selecting data from their physic-chemical applicability domains) or post-processing step (Michael acceptor chemistry correction), neither of which necessarily improve prediction accuracy. For chemicals within newly defined applicability domain, all under-predictions fell within one potency class when compared with LLNA results, indicating no chemicals that were incorrectly classified by more than one class. Considering the potential under-prediction by one class, a worst case value to each class from BN ITS-3 was used to derive a NESIL. When in vivo and human data from suitable analogs cannot be used to estimate the uncertainty, adjusting the NESIL derived from BN ITS-3 may help perform skin sensitization risk assessment. The overall workflow for risk assessment was demonstrated by incorporating the binary test battery of KeratinoSensTM and h-CLAT.

Genome-wide somatic mutation analysis via Hawk-Seq™ reveals mutation profiles associated with chemical mutagens.

It is difficult to identify mutagen-induced genome-wide somatic mutations using next generation sequencing; hence, mutagenic features of each mutagen and their roles in cancer development require further elucidation. We described Hawk-Seq™, a highly accurate genome sequencing method and the optimal conditions, for using it to construct libraries that would enable the accurate (c.a. 1 error/107-108 bp) and efficient survey of genome-wide mutations. Genomic mutations in gpt delta mice or Salmonella typhimurium TA100 exposed to methylnitrosourea (MNU), ethylnitrosourea (ENU), diethylnitrosamine (DEN), benzo[a]pyrene (BP), and aristolochic acid (AA) were profiled using Hawk-Seq™ to analyse positions, substitution patterns, or frequencies. The resultant vast mutation data provided high-resolution mutational signatures, including for minor mutational fractions (e.g. G:C>A:T by AA), which enabled the clarification of the mutagenic features of all mutagens. The 96-type mutational signatures of MNU, AA, and BP indicate their partial similarity to signature 11, 22, and 4 or 29, respectively. Meanwhile, signatures attributable to ENU and DEN were highly similar to each other, but not to signature 11, suggesting that the mechanisms of these agents differed from those of typical alkylating agents. Thus, Hawk-Seq™ can clarify genome-wide chemical mutagenicity profiles at extraordinary resolutions, thereby providing insight into mutagen mechanisms and their roles in cancer development.

Sensitivity of KeratinoSensTM and h-CLAT for detecting minute amounts of sensitizers to evaluate botanical extract.

Cosmetic ingredients are often complex mixtures from natural sources such as botanical extracts that might contain minute amounts of constituents with sensitizing potential. The sensitivity of in vitro skin sensitization test methods such as KeratinoSensTM and h-CLAT for the detection of minute amounts of sensitizer in mixtures remains unclear. In this study, we assessed the detection sensitivity of the binary test battery comprising KeratinoSensTM and h-CLAT for minute amounts of sensitizers by comparing the LLNA EC3 (estimated concentration of a substance expected to produce a stimulation index of 3) values to the minimum detection concentrations (MDCs) exceeding the positive criteria for each of the two in vitro test methods. 146 sensitizers with both sets of in vitro data and LLNA data were used. MDC values for KeratinoSensTM and h-CLAT were calculated from exposure concentrations exceeding positive criteria for each in vitro test method (EC1.5 and minimum induction thresholds, respectively). The dilution rate used to expose culture medium was also considered. For 86% of analyzed sensitizers, the in vitro test methods showed MDC values lower than LLNA EC3 values, suggesting that the binary test battery with KeratinoSensTM and h-CLAT have greater sensitivity for detection of minute amounts of sensitizer than LLNA. These results suggest the high applicability of KeratinoSensTM and h-CLAT for detecting skin sensitizing constituents present in botanical extract.

The dermal sensitization threshold (DST) approach for mixtures evaluated as negative in in vitro test methods; mixture DST.

Cosmetic ingredients often comprise complex mixtures, such as botanical extracts, which may contain skin sensitizing constituents. In our previous study for the sensitivity of the evaluations of skin sensitizing constituents in mixtures using the binary in vitro test battery with KeratinoSensTM and h-CLAT, some sensitizers showed higher detection limits in in vitro test methods than in murine local lymph node assays (LLNA). Thus, to minimize the uncertainty associated with decreased sensitivity for these sensitizers, a risk assessment strategy was developed for mixtures with negative results from the binary test battery. Assuming that the no expected sensitization induction level of mixtures (mixture NESIL) can be derived for mixtures with negative in vitro test results, we assessed 146 sensitizers with in vitro and LLNA data according to the assumption of indeterminate constituents in mixtures. Finally, we calculated 95th percentile probabilities of mixture NESILs and derived dermal sensitization thresholds for mixtures (mixture DST) with negative in vitro test results of 6010 µg/cm2. Feasibility studies indicated that this approach was practical for risk assessments of products in the cosmetic industry. This approach would be a novel risk assessment strategy for incorporating the DST approach and information from in vitro test methods.

Binary test battery with KeratinoSens™ and h-CLAT as part of a bottom-up approach for skin sensitization hazard prediction.

Skin sensitization is one of the key safety endpoints for chemicals applied directly to the skin. Several integrated testing strategies (ITS) using multiple non-animal test methods have been developed to accurately evaluate the sensitizing potential of chemicals, but there is no regulatory-accepted ITS to classify a chemical as a non-sensitizer. In this study, the predictive performance of a binary test battery with KeratinoSens™ and h-CLAT compared to the local lymph node assay (LLNA) and human data was examined using comprehensive dataset of 203 chemicals. When two negative results indicate a non-sensitizer, the binary test battery provided sensitivity of 93.4% or 94.4% compared with the LLNA or human data. Taking into account the predictive limitations (i.e. high log Kow, pre-/pro-haptens and acyl transfer agents (or amine-reactive)), the binary test battery had extremely high sensitivity comparable to that of the 3 out of 3 ITS where three negative results of the DPRA, KeratinoSens™ and h-CLAT indicate a non-sensitizer. Therefore, the data from KeratinoSens™ or h-CLAT may provide partly redundant information on the molecular initiating event derived from DPRA. Taken together, the binary test battery of KeratinoSens™ and h-CLAT could be used as part of a bottom-up approach for skin sensitization hazard prediction.