Successful removal of a telephone cable, a foreign body through the urethra into the bladder: a case report

The variety of foreign bodies inserted into or externally attached to the genitourinary tract defies imagination and includes all types of objects. The frequency of such cases renders these an important addition to the diseases of the genitourinary organs. The most common motive associated with the insertion of foreign bodies into the genitourinary tract is sexual or erotic in nature. In adults this is commonly caused by the insertion of objects used for masturbation and is frequently associated with mental health disorders. We report a case of insertion of telephone cable wire into the urethra. Our case highlights the importance of good history, clinical examination, relevant radiological investigation and simple measures to solve the problem

Impact of attributed audit on procedural performance in cardiac electrophysiology catheter laboratory

PURPOSE: Audit has played a key role in monitoring and improving clinical practice. However, audit often fails to drive change as summative institutional data alone may be insufficient to do so. We hypothesised that the practice of attributed audit, wherein each individual's procedural performance is presented will have a greater impact on clinical practice. This hypothesis was tested in an observational study evaluating improvement in fluoroscopy times for AF ablation. METHODS: Retrospective analyses of fluoroscopy times in AF ablations at the Barts Heart Centre (BHC) from 2012-2017. Fluoroscopy times were compared pre- and post- the introduction of attributed audit in 2012 at St Bartholomew's Hospital (SBH). In order to test the hypothesis, this concept was introduced to a second group of experienced operators from the Heart Hospital (HH) as part of a merger of the two institutions in 2015 and change in fluoroscopy times recorded. RESULTS: A significant drop in fluoroscopy times (33.3 ± 9.14 to 8.95 ± 2.50, p < 0.0001) from 2012-2014 was noted after the introduction of attributed audit. At the time of merger, a significant difference in fluoroscopy times between operators from the two centres was seen in 2015. Each operator's procedural performance was shared openly at the audit meeting. Subsequent audits showed a steady decrease in fluoroscopy times for each operator with the fluoroscopy time (min, mean±SD) decreasing from 13.29 ± 7.3 in 2015 to 8.84 ± 4.8 (p < 0.0001) in 2017 across the entire group. CONCLUSIONS: Systematic improvement in fluoroscopy times for AF ablation procedures was noted byevaluating individual operators' performance. Attributing data to physicians in attributed audit can promptsignificant improvement and hence should be adopted in clinical practice

Soil application of Bacillus thuringiensis Berliner isolates against root-knot nematode (Meloidogyne javanica (Treub) Chitwood) in okra (Abelmoschus esculentus (L.) Moench)

Bacillus thuringiensis (B.t) is well known for its biocontrol potential against a variety of insects. Nematicidal potential of ten B.t isolates was tested against root-knot nematodes (Meloidogyne javanica (Treub) Chitwood) in vitro, under greenhouse as well as in field conditions. Eggs and second stage juveniles (J2) were exposed to 5 and 25% concentrations of bacterial cell-free aqueous extracts up to 96 h. B.t isolates showed lesser degrees of nematicidal activity at 5% concentration. However, some B.t isolates (B.t-14, B.t-16 and B.t-64) greatly reduced egg hatching and increased J2. All B.t isolates revealed suppressed egg hatching and increased mortality of J2 at 25% concentration. Soil applications with most of the B.t isolates under greenhouse and field conditions significantly improved height and fresh weights of root-knot nematode parasitized okra (Abelmoschus esculentus (L.) Moench). Some isolates, including B.t-64 reduced the number of galls and egg masses. B.t-64 reduced gall formation up to 70% under greenhouse conditions. However, 29% of decrease was observed in field conditions. Similarly, B.t-64 treated plants showed a 56% decreased in eggs/egg mass in a field experiment. Population of root-knot nematodes in the rhizosphere was decreased up to 61% in the field experiment as compared to control

Assessment of Growth Inhibition of Eugenol-Loaded Nano-Emulsions against Beneficial Bifidobacterium sp. along with Resistant Escherichia coli Using Flow Cytometry

The intestinal tract microbiota influences many aspects of the dietary components on colon health and during enteric infections, thus, playing a pivotal role in the colon health. Therefore, the eugenol (EU) nano-emulsion effective concentration reported in our previous study against cancer cells should be explored for safety against beneficial microbes. We evaluated the sensitivity of Bifidobacterium breve and B. adolescentis against EU-loaded nano-emulsions at 0, 300, 600 and 900 µm, which were effective against colon and liver cancer cells. Both B. breve and B. adolescentis showed comparable growth ranges to the control group at 300 and 600 µm, as evident from the plate count experimental results. However, at 900 µm, a slight growth variation was revealed with respect to the control group. The real-time inhibition determination through flow cytometry showed B. breve viable, sublethal cells (99.49 and 0.51%) and B. adolescentis (95.59 and 0.15%) at 900 µm, suggesting slight inhibition even at the highest tested concentration. Flow cytometry proved to be a suitable quantitative approach that has revealed separate live, dead, and susceptible cells upon treatment with EU nano-emulsion against Escherichia coli. Similarly, in the case of B. breve and B. adolescentis, the cells showed only live cells that qualitatively suggest EU nano-emulsion safety. To judge the viability of these sublethal populations of B. breve and B. adolescentis, Fourier transforms infrared spectroscopy was carried out, revealing no peak shift for proteins, lipids, DNA and carbohydrates at 900 µm EU nano-emulsion compared to the control. On the other hand, EU-loaded nano-emulsions (900 µm)-treated E. coli showed a clear peak shift for a membrane protein, lipids, DNA and carbohydrates. This study provides insights to utilize plant phenols as safe medicines as well as dietary supplements

A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT

A large number of smart devices in Internet of Things (IoT) environments communicate via different messaging protocols. Message Queuing Telemetry Transport (MQTT) is a widely used publish–subscribe-based protocol for the communication of sensor or event data. The publish–subscribe strategy makes it more attractive for intruders and thus increases the number of possible attacks over MQTT. In this paper, we proposed a Deep Neural Network (DNN) for intrusion detection in the MQTT-based protocol and also compared its performance with other traditional machine learning (ML) algorithms, such as a Naive Bayes (NB), Random Forest (RF), k-Nearest Neighbour (kNN), Decision Tree (DT), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRUs). The performance is proved using two different publicly available datasets, including (1) MQTT-IoT-IDS2020 and (2) a dataset with three different types of attacks, such as Man in the Middle (MitM), Intrusion in the network, and Denial of Services (DoS). The MQTT-IoT-IDS2020 contains three abstract-level features, including Uni-Flow, Bi-Flow, and Packet-Flow. The results for the first dataset and binary classification show that the DNN-based model achieved 99.92%, 99.75%, and 94.94% accuracies for Uni-flow, Bi-flow, and Packet-flow, respectively. However, in the case of multi-label classification, these accuracies reduced to 97.08%, 98.12%, and 90.79%, respectively. On the other hand, the proposed DNN model attains the highest accuracy of 97.13% against LSTM and GRUs for the second dataset

HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles

Internet of Vehicles (IoV) is an application of the Internet of Things (IoT) network that connects smart vehicles to the internet, and vehicles with each other. With the emergence of IoV technology, customers have placed great attention on smart vehicles. However, the rapid growth of IoV has also caused many security and privacy challenges that can lead to fatal accidents. To reduce smart vehicle accidents and detect malicious attacks in vehicular networks, several researchers have presented machine learning (ML)-based models for intrusion detection in IoT networks. However, a proficient and real-time faster algorithm is needed to detect malicious attacks in IoV. This article proposes a hybrid deep learning (DL) model for cyber attack detection in IoV. The proposed model is based on long short-term memory (LSTM) and gated recurrent unit (GRU). The performance of the proposed model is analyzed by using two datasets—a combined DDoS dataset that contains CIC DoS, CI-CIDS 2017, and CSE-CIC-IDS 2018, and a car-hacking dataset. The experimental results demonstrate that the proposed algorithm achieves higher attack detection accuracy of 99.5% and 99.9% for DDoS and car hacks, respectively. The other performance scores, precision, recall, and F1-score, also verify the superior performance of the proposed framework

Serology based disease status of Pakistani population infected with Hepatitis B virus

<p>Abstract</p> <p>Background</p> <p>The infection rate of hepatitis B virus is continuously increasing in Pakistan. Therefore, a comprehensive study of epidemiological data is the need of time.</p> <p>Methods</p> <p>A total of 1300 individuals were screened for HBV infection markers including HBsAg, anti-HBsAg, HBeAg and anti-HBcAg. The association of these disease indicators was compared with patients' epidemiological characteristics like age, socio-economic status and residential area to analyze and find out the possible correlation among these variables and the patients disease status.</p> <p>Results</p> <p>52 (4%) individuals were found positive for HBsAg with mean age 23.5 ± 3.7 years. 9.30%, 33.47% and 12% individuals had HBeAg, antibodies for HBsAg, and antibodies for HBcAg respectively. HBsAg seropositivity rate was significantly associated (<it>p </it>= 0.03) with the residing locality indicating high infection in rural areas. Antibodies titer against HBsAg decreased with the increasing age reflecting an inverse correlation.</p> <p>Conclusion</p> <p>Our results indicate high prevalence rate of Hepatitis B virus infection and nationwide vaccination campaigns along with public awareness and educational programs are needed to be practiced urgently.</p