Receiver-Initiated Data Collection in Wake-Up Radio Enabled mIoT Networks: Achieving Collision-Free Transmissions by Hashing and Partitioning

To achieve ultra-low energy consumption and decade-long battery lifetime for Internet of Things (IoT) networks, wake-up radio (WuR) appears as an eminent solution. While keeping devices in deep sleep for most of the time, a WuR enabled IoT device can be woken up for data transmission at any time by a wake-up call (WuC). However, collisions happen among WuCs for transmitter-initiated data reporting and among data packets for receiver-initiated data collection. In this article, we propose three novel hashing-based schemes in order to achieve collision-free data transmissions for receiver-initiated data collection. We consider first a simple scenario where all devices in a region of interest are reachable by a WuC message and propose a scheme which facilitates a scheduled time instant for data uploading of each device through a hash function. In the second scenario where IoT devices are distributed across a large region that cannot be covered by a single WuC, we propose two partitioning algorithms to enable data collection across multiple partitions. Furthermore, we extend the scenario by considering device mobility and propose another scheme which improves the partitioning algorithm to deal with mobility. Both analysis and simulations are performed to demonstrate the effectiveness of the proposed schemes.acceptedVersio

Outcomes and characteristics of ertapenem-nonsusceptible Klebsiella pneumoniae bacteremia at a university hospital in Northern Taiwan: A matched case-control study

Background and purposeCarbapenem-resistant Klebsiella pneumoniae is an emerging problem worldwide. The object of this study was to investigate the risk factors, characteristics and outcomes of ertapenem-nonsusceptible K pneumoniae (ENSKp) bacteremia.MethodsWe conducted a 1:2 ratio matched case-control study. The controls were randomly selected among patients with ertapenem-susceptible K pneumoniae (ESKp) bacteremia and were matched with ENSKp cases for bacteremia.ResultsSeventy-five patients were included in this study (25 cases and 50 controls). Bivariate analysis showed that prior exposure to either β-Lactam/β-Lactam-lactamase inhibitors (p = 0.008) or 4th generation cephalosporins (p < 0.001), chronic obstructive pulmonary disease (COPD) (p = 0.001), acute renal failure (p = 0.021), chronic kidney disease without dialysis (p = 0.021), recent hospital stay (p = 0.016), intensive care unit stay (p = 0.002), mechanical ventilation (p = 0.003), central venous catheter placement (p = 0.016), Foley indwelling (p = 0.022), polymicrobial bacteremia (p = 0.003) and higher Pittsburgh bacteremia score (p < 0.001) were associated with ENSKp bacteremia. The multivariate analysis showed that prior exposure to 4th generation cephalosporins (odds ratio [OR], 28.05; 95% confidence interval [CI], 2.92–269.85; p = 0.004), COPD (OR, 21.38; 95% CI, 2.95–154.92; p = 0.002) and higher Pittsburgh bacteremia score (OR, 1.35; 95% CI, 1.10–1.66; p = 0.004) were independent factors for ENSKp bacteremia. ENSKp bacteremia had a higher 14-day mortality rate than ESKp bacteremia (44.0% vs. 22.0%; p = 0.049). The overall in-hospital mortality rates for these two groups were 60.0% and 40.0% respectively (p = 0.102).ConclusionENSKp bacteremia had a poor outcome and the risk factors were prior exposure of 4th generation cephalosporins, COPD and higher Pittsburgh bacteremia score. Antibiotic stewardship may be the solution for the preventive strategy

Risk factors and outcomes of carbapenem-nonsusceptible Escherichia coli bacteremia: A matched case–control study

BackgroundInfections due to carbapenem-resistant Enterobacteriaceae have been the emerging problem worldwide. This primary object of this study was to understand the risk factors and clinical outcomes of carbapenem-nonsusceptible Escherichia coli (CNSEc) bacteremia.MethodsWe conducted a matched case–control study in a 3,715-bed tertiary care medical center in northern Taiwan. The controls were selected among patients with carbapenem-susceptible E coli and were matched with CNSEc for bacteremia.ResultsFifty-one patients were included in this study (17 cases and 34 controls). Bivariate analysis showed that prior exposure to carbapenems (p<0.001), stay in intensive care units (p=0.016), placement of central venous catheters (p=0.001), chronic liver diseases (p<0.001), uremia with regular dialysis (p=0.004), and mechanical ventilation (p=0.004) were associated with CNSEc bacteremia. Multivariate analysis revealed that prior exposure to carbapenems [odds ratio (OR), 29.17; 95% confidence interval (CI), 1.76–484.70; p=0.019], uremia with regular dialysis (OR, 98.58; 95% CI, 4.02–999; p=0.005) and chronic liver diseases (OR, 27.86; 95% CI, 2.31–335.83; p=0.009) were independent risk factors for CNSEc bacteremia. Compared with carbapenem-susceptible E coli group, CNSEc group had a longer hospital stay (68.4 days vs. 35.8 days; p=0.04) and a higher disease severity, as indicated by a Pittsburgh bacteremia score greater than or equal to 4 (5.6% vs. 2.5%; p=0.015). Patients with CNSEc bacteremia had a higher overall in-hospital mortality rate (94.12% vs. 50.00%; p=0.002), but there was no difference in the 28-day mortality between these two groups.ConclusionsCNSEc bacteremia would lead to a poor outcome among patients with prior exposure to carbapenems, chronic liver disease, and uremia with regular dialysis

Receiver-Initiated Data Collection in Wake-Up Radio Enabled mIoT Networks: Achieving Collision-Free Transmissions by Hashing and Partitioning

To achieve ultra-low energy consumption and decade-long battery lifetime for Internet of Things (IoT) networks, wake-up radio (WuR) appears as an eminent solution. While keeping devices in deep sleep for most of the time, a WuR enabled IoT device can be woken up for data transmission at any time by a wake-up call (WuC). However, collisions happen among WuCs for transmitter-initiated data reporting and among data packets for receiver-initiated data collection. In this article, we propose three novel hashing-based schemes in order to achieve collision-free data transmissions for receiver-initiated data collection. We consider first a simple scenario where all devices in a region of interest are reachable by a WuC message and propose a scheme which facilitates a scheduled time instant for data uploading of each device through a hash function. In the second scenario where IoT devices are distributed across a large region that cannot be covered by a single WuC, we propose two partitioning algorithms to enable data collection across multiple partitions. Furthermore, we extend the scenario by considering device mobility and propose another scheme which improves the partitioning algorithm to deal with mobility. Both analysis and simulations are performed to demonstrate the effectiveness of the proposed schemes

Molecular epidemiology of Clostridium difficile at a medical center in Taiwan: persistence of genetically clustering of A⁻B⁺ isolates and increase of A⁺B⁺ isolates.

INTRODUCTION: We investigated the changing trend of various toxigenic Clostridium difficile isolates at a 3 500-bed hospital in Taiwan. Genetic relatedness and antimicrobial susceptibility of toxigenic C. difficile isolates were also examined. METHODS: A total of 110 non-repeat toxigenic C. difficile isolates from different patients were collected between 2002 and 2007. Characterization of the 110 toxigenic isolates was performed using agar dilution method, multilocus variable-number tandem-repeat analysis (MLVA) genotyping, tcdC genotyping, and toxinotyping. RESULTS: Among the 110 toxigenic isolates studied, 70 isolates harbored tcdA and tcdB (A⁺B⁺) and 40 isolates harbored tcdB only (A⁻B⁺). The annual number of A⁺B⁺ isolates considerably increased over the 6-year study (P = 0.055). A total of 109 different MLVA genotypes were identified, in which A⁺B⁺ isolates and A⁻B⁺ isolates were differentiated into two genetic clusters with similarity of 17.6%. Twenty-four (60%) of the 40 A⁻B⁺ isolates formed a major cluster, MLVA-group 1, with a similarity of 85%. Seven (6.4%) resistant isolates were identified, including two metronidazole-resistant and five vancomycin-resistant isolates. CONCLUSIONS: This study indicated a persistence of a MLVA group 1 A⁻B⁺ isolates and an increase of A⁺B⁺ isolates with diverse MLVA types. Moreover, C. difficile isolates with antimicrobial resistance to metronidazole or vancomycin were found to have emerged. Continuous surveillance is warranted to understand the recent situation and control the further spread of the toxigenic C. difficile isolates, especially among hospitalized patients

d-Penicillamine induced elastosis perforans serpiginosa with involvement of glans penis

Elastosis perforans serpiginosa (EPS) is an unusual perforating disorder characterized by extrusion of altered elastic fibers through the epidermis. Clinically, it presents as keratotic papules with a tendency for serpiginous or annular distribution that most commonly involves the sides of the neck and the back. However, involvement of the penis has rarely been reported. We present a case of EPS involving the neck, axilla, and glans penis in a 42-year-old man who had received long-term d-penicillamine treatment for Wilson disease. Skin biopsy revealed perforating channels containing numerous altered elastic fibers, with a characteristic “bramble brush” or “lumpy-bumpy” appearance as demonstrated by an elastin stain. The latter is thought to be pathognomonic for penicillamine-induced degenerative elastosis. These degenerative changes occurring in glans penis have rarely been described in the literature. Prompt recognition of the rare presentation could lead to early discontinuation of the offending drug, to prevent further sequelae

Development of a Multiplex PCR and SHV Melting-Curve Mutation Detection System for Detection of Some SHV and CTX-M β-Lactamases of Escherichia coli, Klebsiella pneumoniae, and Enterobacter cloacae in Taiwan

Infection by extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae has been increasing in Taiwan. Accurate identification of the ESBL genes is necessary for surveillance and for epidemiological studies of the mode of transmission in the hospital setting. We describe herein the development of a novel system, which consists of a multiplex PCR to identify bla(SHV), bla(CTX-M-3)-like, and bla(CTX-M-14)-like genes and a modified SHV melting-curve mutation detection method to rapidly distinguish six prevalent bla(SHV) genes (bla(SHV-1), bla(SHV-2), bla(SHV-2a), bla(SHV-5), bla(SHV-11), and bla(SHV-12)) in Taiwan. Sixty-five clinical isolates, which had been characterized by nucleotide sequencing of the bla(SHV) and bla(CTX-M) genes, were identified by the system. The system was then used to genotype the ESBLs from 199 clinical isolates, including 40 Enterobacter cloacae, 68 Escherichia coli, and 91 Klebsiella pneumoniae, collected between August 2002 and March 2003. SHV-12 (80 isolates) was the most prevalent type of ESBL identified, followed in order of frequency by CTX-M-3 (65 isolates) and CTX-M-14 (36 isolates). Seventeen (9%) of the 199 clinical isolates harbored both SHV- and CTX-M-type ESBLs. In contrast to Enterobacter cloacae, the majority of which produced SHV-type ESBLs, E. coli and K. pneumoniae were more likely to possess CTX-M-type ESBLs. Three rare CTX-M types were identified through sequencing of the bla(CTX-M-3)-like (CTX-M-15) and bla(CTX-M-14)-like (CTX-M-9 and CTX-M-13) genes. The system appears to provide an efficient differentiation of ESBLs among E. coli, K. pneumoniae, and Enterobacter cloacae in Taiwan. Moreover, the design of the system can be easily adapted for similar purposes in areas where different ESBLs are prevalent

Range of MIC values and resistance rate of the 110 toxigenic <i>C. difficile</i> isolates analyzed by year.

<p>MIC: minimum inhibitory concentrations.</p>a<p>The breakpoints for metronidazole and vancomycin recommended by the EUCAST: susceptible, ≦2 mg/L; resistant, >2 mg/L.</p

Numbers and types of <i>C. difficile</i> isolates determined using toxinotyping, <i>tcdC</i> genotyping and the occurrence of toxin genes A, B and the binary toxin genes CDT.

<p>A⁻B⁺CDT^-: toxin A-negative, toxin B-positive, and binary toxin genes-negative <i>C. difficile</i>; A⁺B⁺CDT^-: toxin A-positive, toxin B-positive, and binary toxin genes-negative <i>C. difficile</i>; A⁺B⁺CDT⁺: toxin A-positive, toxin B-positive, and binary toxin genes-positive <i>C. difficile</i>.</p